SERA United States Office of Research and EPA/600/R-22/065 Environmental Protection Development July 2022 Agency Washington, D.C. 20460 www.epa.gov/emergency-response-research Data Management for Wide-area Responses: Technology Evaluation and Operational Expert Feedback by Timothy Boe1, Erin Silvestri1, Jamie Falik1 Matt Blaser2, Jim Mitchell2, Brian Cooper2, Leroy Mickelsen3, Lieutenant Commander Clifton Graham4, Katrina McConkey5, Molly Rodgers5 ^.S. EPA Office of Research and Development (ORD) Center for Environmental Solutions and Emergency Response (CESER) Homeland Security and Materials Management Division (HSMMD) Durham, NC 27709 2U.S. EPA Region 5 3U.S. EPA Office of Land and Emergency Management (OLEM) Office of Emergency Management (OEM) Consequence Management Advisory Division (CMAD) 4U.S. Coast Guard (USCG) 5Eastern Research Group, Inc. (ERG) Morrisville, NC 27560 Contract EP-C-16-015 to Eastern Research Group, Inc. ------- DISCLAIMER The U.S. Environmental Protection Agency (EPA) through its Office of Research and Development (ORD) directed and managed this work. This study was funded through the Analysis for Coastal Operational Resiliency (AnCOR) Project by the U.S. Department of Homeland Security Science and Technology Directorate under interagency agreement IA 70RSAT18KPM000084. This report was prepared by Eastern Research Group, Inc. under EPA Contract Number EP-C-16-015. This report has been reviewed and approved for public release in accordance with the policies of the EPA. Mention of trade names or commercial products does not constitute endorsement or recommendation for use of a specific product. The contents are the sole responsibility of the authors and do not necessarily represent the official views of EPA, DHS S&T, or the United States Government. Questions concerning this document, or its application should be addressed to: Timothy Boe U.S. Environmental Protection Agency Office of Research and Development Center for Environmental Solutions and Emergency Response 109 T.W. Alexander Dr. (MD-E-343-06) Research Triangle Park, NC 27711 Phone 919.541.2617 ------- FOREWORD The U.S. Environmental Protection Agency (EPA) is charged by Congress with protecting the Nation's land, air, and water resources. Under a mandate of national environmental laws, the Agency strives to formulate and implement actions leading to a compatible balance between human activities and the ability of natural systems to support and nurture life. To meet this mandate, EPA's research program is providing data and technical support for solving environmental problems today and building a science knowledge base necessary to manage our ecological resources wisely, understand how pollutants affect our health, and prevent or reduce environmental risks in the future. The Center for Environmental Solutions and Emergency Response (CESER) within the Office of Research and Development (ORD) conducts applied, stakeholder-driven research and provides responsive technical support to help solve the Nation's environmental challenges. The Center's research focuses on innovative approaches to address environmental challenges associated with the built environment. We develop technologies and decision-support tools to help safeguard public water systems and groundwater, guide sustainable materials management, remediate sites from traditional contamination sources and emerging environmental stressors, and address potential threats from terrorism and natural disasters. CESER collaborates with both public and private sector partners to foster technologies that improve the effectiveness and reduce the cost of compliance, while anticipating emerging problems. We provide technical support to EPA regions and programs, states, tribal nations, and federal partners, and serve as the interagency liaison for EPA in homeland security research and technology. The Center is a leader in providing scientific solutions to protect human health and the environment. Through this effort, candidate tools were exercised and evaluated to assess the current state of technologies to enhance the United States Coast Guard (USCG) and EPA's ability to respond to and recover from a chemical, biological, radiological and nuclear (CBRN) incident. The technologies and software recommended will be exercised through a complete data management workflow during the Analysis for Coastal Operational Resiliency (AnCOR) field study that was held in May 2022. The operational considerations illuminated through this study provided invaluable information to ensure increased preparedness and, ultimately, more efficient, and successful field data acquisition and management activities. Gregory Sayles, Director Center for Environmental Solutions and Emergency Response 111 ------- ACKNOWLEDGMENTS Contributions of the following individuals and organizations to this report are acknowledged: U.S. EPA Technical Reviewers of Report John Archer (EPA/ORD/CESER/HSMMD) Elise Jakabhazy (EPA/OLEM/OEM/CBRN CMAD) U.S. EPA Quality Assurance Eletha Brady Roberts Ramona Sherman iv ------- TABLE OF CONTENTS Disclaimer ii Foreword iii Acknowledgments iv List of Tables vi List of Figures vi Acronyms and Abbreviations viii Executive Summary ix 1 Introduction 1 2 Quality Assurance/Quality Control 3 3 Data and Technology Assessment Demonstration Overview 3 4 Tools for Supporting Sampling Design and Implementation 7 4.1 MicroSAP 7 4.2 Trade-Off Tool for Sampling (TOTS) 7 4.3 Simple QUIck REad Label (SQUIREL) 8 5 Field Data Aquistion Software Evaluation 9 5.1 Esri's ArcGIS Field Apps Suite 10 5.1.1 ArcGIS Pro Linear Referencing (Create Routes) 10 5.1.2 ArcGIS Field Maps 11 5.1.3 ArcGIS Dashboards 12 5.1.4 ArcGIS Tracker 13 5.2 CBRNResponder 14 5.2.1 Event Management and Configuration 15 5.2.2 Field Data Collection 17 5.2.3 Event Dashboard and Map 19 5.2.4 Reports 20 5.3 Android Team Awareness Kit (ATAK) 21 5.4 EPA Scribe 22 6 Technology Evaluation 22 6.1 Global Positioning System (GPS) Devices 22 6.2 Mobile Devices 27 7 Data Management and Real-time Quality Control Measures 28 7.1 ArcGIS Field Maps Data Storage 28 7.2 CBRNResponder Data Storage 29 7.3 Real-Time Quality Control Measures 29 7.3.1 ArcGIS Field Maps QC 29 v ------- 7.3.2 CBRNResponder QC 30 8 DATA DAY Demonstration Participant Observations and Findings 30 8.1 General Observations and Participant Feedback 30 8.1.1 Demo Implementation 30 8.1.2 Operational Feasibility 31 8.1.3 Technol ogy Evaluati on 31 8.1.4 Mobile Devices 32 8.1.5 Software 33 8.2 Data Manager Observations 37 8.2.1 Operational Feasibility Considerations 37 8.2.2 ArcGIS Field Apps Suite 38 8.2.3 CBRNResponder 38 8.2.4 Other Noted Observations 39 9 Conclusions and Recommendations 39 10 References 44 LIST OF TABLES Table 1. GPS Test Locations 23 Table 2. Average Horizontal Error (ft) by Location and Unit 27 Table 3. Additional Observations and Feedback 42 LIST OF FIGURES Figure 1. Map of sampling, control, and test points throughout the RTP campus 4 Figure 2. Progression of stations 4 Figure 3. Priority evaluation criteria 5 Figure 4. Example TOTS screen illustrating a random sample design 8 Figure 5. Example TOTS screen illustrating a 20x20 foot grid-based sample design 8 Figure 6. Simple QUIck REad Label (SQUTREL) interface 9 Figure 7. Assigned team sampling routes 10 Figure 8. AnCOR DATA Demo Field Maps field data capture form 12 Figure 9. AnCOR DATA Demo ArcGIS dashboard 13 Figure 10. Example of misplaced samples 13 Figure 11. Example tracking route 14 Figure 12. CBRNResponder data fields 15 Figure 13. CBRNResponder sampling location import template 16 Figure 14. CBRNResponder assignment import template 17 Figure 15. CBRNResponder App screens for field data capture - Part 1 18 Figure 16. CBRNResponder App screens for field data capture - Part 2 19 Figure 17. CBRNResponder App event map for monitoring activities 20 vi ------- Figure 18. CBRNResponder App supports generating sample labels 20 Figure 19. CBRNResponder chain of custody form example 21 Figure 20. Screenshot of ATAK viewer showing samples and route with aerial image overlay. 22 Figure 21. Leica Nova MS50 multi-station and associated prism marker 23 Figure 22. National Geodetic Survey benchmark 24 Figure 23. Horizontal error for test location A 25 Figure 24. Horizontal error for test location B 25 Figure 25. Horizontal error for test location C 26 Figure 26. Horizontal error for test location D 26 Figure 27. Horizontal error for test location E 27 Figure 28. Table showing a sample of ArcGIS Field Maps data collection results 28 Figure 29. Table showing a sample of CBRNResponder data collection results 29 Figure 30. AnCOR Data management tasks and supporting tools 41 vii ------- ACRONYMS AND ABBREVIATIONS AnCOR Analysis for Coastal Operational Resiliency API application programming interface ATAK Android Team Awareness Kit CBRN chemical, biological, radiological, or nuclear CESER Center for Environmental Solutions and Emergency Response CMAD Consequence Management Advisory Division COTS commercial off-the-shelf COVID coronavirus disease CSV comma-separated value DHS Department of Homeland Security DoD U.S. Department of Defense DOE U.S. Department of Energy EPA U.S. Environmental Protection Agency ERG Eastern Research Group, Inc. ERT Emergency Response Team FEMA Federal Emergency Management Agency FFR full-face respirator GIS geographic information system GOTS government off-the-shelf GPS Global Positioning System HSMMD Homeland Security and Materials Management Division ICS incident command structure OEM Office of Emergency Management OLEM Office of Land and Emergency Management ORD Office of Research and Development PPE personal protective equipment QR quick response RCRA Resource Conservation and Recovery Act S&T Science and Technology Directorate SQUIREL Simple QUIck REad Label TOTS Trade-off Tool for Sampling USCG U.S. Coast Guard viii ------- EXECUTIVE SUMMARY In the event of a chemical, biological, radiological, and/or nuclear (CBRN) wide-area incident, the U.S. Environmental Protection Agency (EPA) has the authority to take actions to respond to releases of hazardous substances, pollutants, and contaminants, including leading the response. This response includes cleanup and waste management, which needs data collection, and data quality checks to advise decision-making. The U.S. Coast Guard (USCG) shares this responsibility for certain incidents in the maritime domain. This research aims to streamline and improve the capabilities of USCG and EPA responders to a wide-area incident. Specifically, the research aimed to identify and recommend user-friendly tools that more easily facilitate the acquisition and subsequent management of field sampling data following a wide-area incident. Tools identified through this research were then further evaluated during a technology demonstration day hosted by EPA's Homeland Security Research Program, in association with the Department of Homeland Security (DHS)/EPA-sponsored Analysis for Coastal Operational Resiliency (AnCOR) Data Project. Phase 1 of this project evaluated currently available commercial off-the-shelf (COTS) or government off-the-shelf (GOTS) that appeared to have features that would meet the largest number of needs. A subset of tools evaluated were recommended for further evaluation, including Esri's Survey 123/Collector/Field Maps Suite, Android Team Awareness Kit (ATAK), EPA's Scribe, and RadResponder. While RadResponder was specifically identified during Phase 1, the Federal Emergency Management Agency (FEMA) sponsors a suite of "responder apps" collectively referred to as CBRNResponder that includes access to both RadResponder and ChemResponder (and soon, BioResponder). Phase 2 of this project focused on exercising and evaluating the candidate tools recommended in Phase 1. Specifically, this study evaluated the current state of technologies through a demonstration event and documented observations and recommendations to enhance the USCG and EPA's ability to respond to and recover from a CBRN incident. Through this project, EPA gained invaluable experience in understanding how to apply advances in technologies and software to improve field data acquisition tasks. Important technological issues were identified to inform future planning and training efforts. Based on the expressed needs of EPA and DHS/USCG and the experiences of participants in the AnCOR DATA Demo, the project team recommends using Esri's suite of tools and ArcGIS Field Maps to support field data acquisition efforts for the AnCOR program. Consistent with the findings from a related effort to assess data visualization and analysis tools, the Esri suite has the most features that meet the largest number of needs, is familiar to and accepted by target stakeholders, and is generally viewed as easy to customize and tailor to meet the specific needs of the operation. CBRNResponder, and a forthcoming BioResponder, offer many promising features. At present, however, several key requirements for EPA's AnCOR program cannot currently be met namely, alignment with required data fields/types that will be collected and integration with real- time geospatial assets. The project team recommends that EPA continue engagement attempts with FEMA to convey EPA's needs regarding biological sampling (and other agents), and IX ------- closely monitor FEMA's progress and tool enhancements to determine whether the tool could better meet EPA's needs in the future. The AnCOR project will conclude with a Wide Area Demo (WAD) that consists of a field-level biological remediation study. The primary purpose of the AnCOR WAD is to operationally test and evaluate options for decontamination, sampling, data management, and waste management for areas impacted by a wide-area biological agent release in a USCG or urban environment. A secondary goal of this project was to document a repeatable, transparent, and stable workflow to support the WAD data management needs. To address this need, the project team developed a Data Management Task/Workflow that identifies when and how various data management tools can be used across the response. Specific tasks that have a related data management component, the various tools that are available to support activities, and the established workflow among the tasks and tools were documented. Important additional considerations resulting from experiences gained through completing Phase 2 of the project were also identified and generally centered on the following topics: Quality Control Procedures/Objectives, Field Data Capture Form, Training, Operational Logistics, and Managing Devices. Through this effort, candidate tools were exercised and evaluated to assess the current state of technologies to enhance the USCG and EPA's ability to respond to and recover from a CBRN incident. The technologies and software recommended were exercised through a complete data management workflow during the AnCOR WAD field study held in May 2022. The operational considerations illuminated through this study provided invaluable information to ensure increased preparedness and, ultimately, more efficient and successful field data acquisition and management activities. x ------- 1 INTRODUCTION The U.S. Environmental Protection Agency (EPA) is designated as a coordinating agency, under the National Response Framework,1 to respond to discharges or releases of oil and hazardous substances. As such, EPA's role is to prepare for, respond to, and recover from threats to public health, welfare, or the environment posed by oil and hazardous materials incidents. Hazardous materials incidents can include accidental or intentional releases of chemical, biological, and radiological or nuclear (CBRN) substances. EPA can also have responsibilities to address debris and waste through decontamination, removal, and disposal operations. Following a wide-area CBRN incident, from initial characterization sampling to evaluate the contamination event through clearance sampling and waste disposal processes, a substantial amount of data will need to be collected, checked for quality, and maintained to support decision-making. Depending on the size and scope of the hazardous contamination, data management could result in a significant technological undertaking that could continue for many years. Types of data collected during the response could include: Sample location, Sample matrix, Sampling method, Time and date of sample collection, Image of sample location or sampling surface, Sample collection personnel or team, Laboratory processing the analysis, Analysis results, Mapping data (e.g., Global Positioning Systems [GPS], light detection and ranging [LiDAR], photogrammetry), Documentation of quality assurance activities, and Decontamination method. Tools and technologies that might be used during characterization and clearance sampling include computers or tablets, software applications, mobile devices, databases, data models, geographic information system (GIS) applications, laboratory reporting tools, and auxiliary tools such as GPS. Understanding the capabilities of these tools and technologies, identifying how they connect and work together, and evaluating the usability of various technologies is critical to advancing EPA's and the Department of Homeland Security's (DHS's) data management capabilities. Data management frameworks are plans that are developed to help address practically every part of the data management process including the individual tools, technologies, and processes that are used to collect, store, retrieve, and visualize data. Integrating a suite of technologies to support a comprehensive data management framework is necessary to effectively organize, document, quality assure, and communicate data during a wide-area CBRN incident. 'The National Respoi nework is a guide to how the Nation responds to all types of disasters and emergencies. 1 ------- This project supports the Analysis for Coastal Operational Resiliency (AnCOR) program. AnCOR is a multi-agency program with the purpose of developing and demonstrating capabilities and strategic guidelines to prepare the U.S. for a wide-area release of a biological agent, including mitigating impacts to United States Coast Guard (USCG) facilities and assets [1], This project evaluated the current state of technologies for conducting site surveys and managing sampling data following a wide-area incident and correlated supportive technologies with specific field sampling activities to describe how tools and technologies are applied within an overall decision framework. This project aims to streamline capabilities and identify improved data management tools to better fit the needs of DHS, USCG, and EPA responders following a wide-area contamination incident. The project does so by evaluating the current state of tools and technologies that facilitate the acquisition and subsequent management of field sampling data. This project had four (4) primary objectives: 1. Conduct a literature review and market research to identify relevant articles, reports, and other information describing research, ongoing initiatives by regional and state partners, and available commercial-off-the-shelf products that streamline and modernize field data collection activities; 2. Solicit subject-matter expert feedback from the response and research community on important functionality that field data acquisition and/or data management tools and technologies should have for responding to a wide-area incident; 3. Identify and evaluate technology to support response personnel based on recommendations provided by the response community; and 4. Conduct a field-scale demonstration to further evaluate operational aspects of selected technologies for the potential to enhance preparedness. Due to COVID-19 (coronavirus disease 2019) restrictions postponing field exercises, this project was divided into two phases. Phase 1 addressed objectives 1 and 2 and part of objective 3 where candidate tools were identified for further evaluation. From Phase 1 of this project, EPA gained a better understanding of users' needs and identified available candidate tools to evaluate [2], Phase 2, the subject of this report, addressed objectives 3 and 4 in which candidate tools were exercised and evaluated. Specifically, this study evaluated the current state of technologies through a demonstration event and documented observations and recommendations to enhance the USCG and EPA's ability to respond to and recover from a CBRN incident. The findings that resulted are described in the remainder of this report, which is structured in the following manner: Chapter 2 discusses quality assurance/quality control activities, Chapter 3 provides an overview of the demonstration event, Chapter 4 describes several additional tools that are available to support sampling design and implementation, Chapter 5 describes the field data collection software that was evaluated and used during the demonstration, 2 ------- Chapter 6 summarizes the technology that was evaluated, including GPS and mobile devices, Chapter 7 discusses data management and additional real-time quality control measures that were evaluated, Chapter 8 presents participant observations and findings that resulted from the technology demonstration and evaluation, as well as observations related to configuring technology and software to support the demonstration, and Chapter 9 summarizes the conclusions and recommendations resulting from Phase 2 of this research. 2 QUALITY ASSURANCE/QUALITY CONTROL The purpose of this study was to synthesize existing knowledge and research related to data management applications that could be used following a wide-area CBRN incident. The work and conclusions presented as part of this study were empirical and observationalno scientific experiments were performed. Technical area leads evaluated candidate tools and provided feedback on their experiences. 3 DATA AND TECHNOLOGY ASSESSMENT DEMONSTRATION OVERVIEW EPA conducted the AnCOR Data And Technology Assessment (DATA) demonstration (AnCOR DATA Demo) at EPA's Campus in Research Triangle Park (RTP), North Carolina on September 15th-17th, 2021. The AnCOR DATA Demo evaluated and operationally exercised tools and supportive technologies for use in supporting sampling activities and data management workflow and processes following a contamination incident. The study took place outdoors (over a 200- acre test area) and involved approximately 20 volunteers from EPA and DHS/USCG. Participants completed a series of controlled tests using a variety of technologies to identify, locate, and document mock biological surface samples. As shown in Figure 1, 200 sampling points (point color indicates team association), five control points, and one test point were established to support exercising technology and software. 3 ------- Figure 1. Map of sampling, control, and test points throughout the RTP campus. Below is a list of the events that were completed throughout the two-day period: Welcome, Objectives, and Methods Briefing, Health and Safety Briefing, Technology Overview Presentation, Sampling Method Demonstration (sponge and microvac), Stations/Teams Processing, and Phases 1 through 3 of Field Testing. Teams exercised different technology and field data collection software (consisting of three separate iterations) over two days. During each iteration, individuals were paired and assigned to team s to test different configurations of technology/software. Prior to beginning a sample collection phase, each team proceeded through a series of stations, as shown in Figure 2, and returned to report feedback following completion of the sampling activity. Figure 2. Progression of stations. 4 ------- Following the completion of an iteration, participants reported their observations and feedback. Participants evaluated key criteria that were established as high priority during Phase 1 of the study. During Phase 1, project team members consisting of federal responders, data management subject matter experts, and researchers, were asked to rank the importance of each criterion to prioritize essential attributes. The rankings were analyzed to identify the top evaluation criteria that were designated as a high priority for consideration (see Figure 3) [2], 1. Web-based System 12. Allows Data Capture of Notes 2. Ease of Use In Personal Protective 13. Ease of Customization Equipment 14. Database Compatible Export Format 3. Easy to Maintain 15. Long Battery Life 4. GPS Enabled/Capable 16. Rugged Device 5. Functions with or without Wireless 17. Flexible Data Export Formats Connectivity 18. Flexible Export Formats to Support Easily 6. Image Capture Capability Formatting Data for Representational 7. Few Clicks for Data Entry State Transfer (REST) Services 8. Ease of Configurability 19. Compatible with Other EPA Systems 9. Includes GIS Capabilities 20. Current Availability 10 Capable of Accurately Locating Indoor 21. Minimal Components with Capability to Sampling Locations (X, Y, Z) Expand (USB/Bluetooth) 11. Mobile Compatible Figure 3. Priority evaluation criteria. In addition to general observations and feedback, participants (including data managers) were asked to observe and report on their experiences using the technologies evaluated during the demonstration. For the Phase 2 evaluation, priority evaluation criteria were organized into the following four over-arching categories: Software, Hardware, Technology Configuration, and Operational Feasibility: Software Use of touch-sensitive data capture forms while wearing personal protective equipment (PPE); note: garden gloves were used as a substitute during testing, Toggling online or offline mode, Capturing an image using the camera feature, Capturing a video, Entering text using a finger and/or stylus, Using onscreen maps, Scanning a quick read (QR) code (for tracking samples), Synchronizing data from mobile application to centralized data storage, and Using navigational and GIS features. Hardware GPS performance, Battery capacity, Capability to expand (USB/Bluetooth), and Ruggedness of device (i.e., performance related to excessive heat, light). 5 ------- Technology Configuration In advance of the exercise, AnCOR DATA Demo project team members were responsible for acquiring devices and configuring field data collection software. Observations related to the ease of implementing the acquired technologies and field data collection software were also captured and documented, including: Compatibility with other EPA systems, Database-compatible export formats, Ease of configurability, Ease of customization, Ease of maintenance, and Flexible data export formats. Operational Feasibility The AnCOR DATA Demo project team also evaluated the feasibility of several important considerations related to technologies and data management operations in the field. The following considerations were evaluated: Span of Control: The number of individuals or resources that one person can effectively manage during an incident according to the Incident Command System (ICS). Just-in-Time Training: Training personnel only when it is needed rather than in advance or on a predetermined frequency. These training opportunities are typically used as refresher courses prior to emergency response teams utilizing procedures or technologies. Offline Operation: Communications might be inoperable following a large-scale biological incident; therefore, the AnCOR DATA Demo evaluated the use of data acquisition tools without access to internet. PPE Limitations: The use of PPE can limit the dexterity of personnel, especially when using tablets that are touch sensitive. Teams were randomly (via injects) asked to use thick garden gloves (to mimic PPE) and equipped with a stylus. Teams were then asked to interface with the software. Protecting Sensitive Equipment: The decontamination of expensive electronic equipment for reuse is essential. Previous field studies have successfully demonstrated that electronic tablets (e.g., Apple iPads) can be successfully decontaminated by encapsulating them in a water-resistant case and dunking them in a bleach solution [3], The use of external GPS equipment, however, complicates this process. Chapters 4 and 5 describe the software tools and technology that were evaluated during the AnCOR DATA Demo, including several tools that EPA created to support designing and implementing a sample plan. Chapters 6 through 8 summarize observations from the project team and demonstration participants. 6 ------- 4 TOOLS FOR SUPPORTING SAMPLING DESIGN AND IMPLEMENTATION As discussed, following a wide-area CBRN incident, from initial characterization sampling to evaluate the contamination event through clearance sampling and waste disposal processes, a substantial amount of data will need to be collected, checked for quality, and maintained to support decision-making. Depending on the size and scope of the incident, sampling activities might require a significant effort. Phase 1 research efforts of this project identified candidate field data acquisition software tools to further evaluate and exercise during the AnCOR DATA Demo. In addition to evaluating the candidate software, EPA also maximized this opportunity to evaluate several other tools and technologies that can support implementing sample designs and data management needs during an event. An overview of other tools and technologies that can support this phase of the response is provided below. 4.1 MicroSAP EPA's Sampling and Analysis Plan Template Tool is available to assist planners in developing a sampling and analysis plan (SAP) needed to collect data that are suitable for decision-making and/or determinations of existing conditions for all phases of a contamination incident involving pathogens in which EPA would be responsible for conducting sampling and analysis [4], While the project team did not use MicroSAP for the demonstration, the framework/guidance is a resource that can be used to support documentation of the sample collection and analysis procedures or methods to be used, sampling design, quality control procedures, and data reduction and visualization planned. The tool supports documenting user inputs related to an incident while associating those inputs with their respective data quality objectives. EPA is also developing an online tool to support plan creation, and in the meantime a template and user's guide are available that provide the framework for capturing information needed to complete the SAP. 4.2 Trade-Off Tool for Sampling (TOTS) The Trade-Off Tool for Sampling (TOTS) allows users to create sampling designs and estimate the associated resource demand through interactive point-and-click tools to visually develop sampling plans for biological contamination incidents [5], Users can plot sample locations in conjunction with externally developed indoor or outdoor imagery that can be imported into the tool. Users can configure and include custom sampling methods, visualize sampling plans, and share sampling plans. Based on the plans designed, TOTS estimates the total time and cost necessary for implementation, which includes preparing sampling kits, conducting the sampling campaign, and analyzing the samples in the laboratory. The resulting sampling plan can be used to consider trade-offs in the sampling design (i.e., cost-benefit analysis), alternate sampling approaches (i.e., traditional versus innovative sampling methods), and sampling coverage. TOTS also operationalizes sampling plan maps by enabling response field personnel to leverage a web- based map, real-time navigation, and field data capture while sampling in the field. TOTS outputs include geospatial assets that can be saved and shared for reuse. TOTS was used by the AnCOR DATA Demo project team to create sampling designs for the AnCOR DATA Demo and to determine whether the proposed designs could be successfully 7 ------- executed within the allotted timeline of the demonstration. Figure 4 shows a screenshot of TOTS with an active random sampling design. Figure 5 illustrates a 20x20 foot grid-based approach that could be implemented by the AnCOR planning team. Both the random and grid-based designs were exercised as part of the AnCOR DATA Demo. The sample designs were exported and used with field data capture software evaluated for the demo. Trade-off Tool for Sampling (TOTS) Basemap Legend Logout Contact Us $ Add Data a Publish ฆฆ Output Resource Tally Total Cost: $98,414 *3r S27.014 A 571,400 Max Time day(s): 2.9 Limiting Factor A Analysis Create Plan O Training Mode Q Auto Zoom c Start Over Delete All Samples An empty sample layer is loaded by default. Use the "Active Sampling Layer" controls to link, add, modify, and/or delete the sampling layer associated with the active plan. You may associate multiple layers with a plan by selecting sampling layers from the menu and clicking the link icon. The menu will display linked layers and indicate other layers available for linking. Use the "unlink" control to remove a layer from a plan. Specify Plan AnCOR DATA Demo Bf + Active Sampling Layer CD 28 Bf + Default Sample Layer oo o V " ฐฐ % o o o O n CP ฐฉ Oo 0. o o Oo00 o ฐCPOo oO o Oฎ _.o fiCP n o<, cp ฉ jy oo ฃฐo-*ฐjjr o%0 Figure 4. Example TOTS screen illustrating a random sample design. Figure 5. Example TOTS screen illustrating a 20x20 foot grid-based sample design. 4.3 Simple QUIck REad Label (SQUIREL) Field data capture applications can leverage QR code technology to minimize data entry requirements while in the field. Operational personnel consistently emphasize the desire to record data with as few clicks as possible and leverage technological advances that streamline data entry and minimize data transposition errors. In support of this need, EPA developed the Simple QUIck REad Label (SQUIREL) tool [6], SQUIREL is a lightweight tool that can be used to create sample label designs that are rendered in a QR code format that can be used with field data capture applications and/or laboratory 8 ------- systems; therefore, reducing human error when documenting sampling identifiers and other relevant information. Users can generate labels by entering study-specific nomenclature into text fields. Additional columns can be added to expand the format of each label. Rows can be added to include multiple label designs within a single instance. Alternatively, QR codes can be generated by directly importing a comma-separated value (CSV) file. Once the label nomenclature is established, SQUIREL generates a portable document format (PDF) document specific to the chosen label sizes. Labels can then be attached to sampling bags and other containment apparatuses for quick scanning in the field or in the lab. Figure 6 displays the SQUIREL interface. Q SQUIREL Simple QUIck REad Label (SQUIREL) piacenoiaers ai any location in any column, or in us own column: 1. #num_seq - Adds a sequentially incrementing number starting from 1 (ex. 1,2, 3...) 2. #num_rand - Adds a randomly generated number between 1 and 1000, no repeats 3. #alpha_seq - Adds a letter sequentially increasing from A-Z (ex. A, B, C...) 4. #alpha_rand - Adds a random letter combination between A and ZZ, no repeats Credits: Taha Karimi, Timothv Boe. Worth Calfee Figure 6. Simple QUIck REad Label (SQUIREL) interface. 5 FIELD DATA AQUISTION SOFTWARE EVALUATION Phase 1 research efforts of this project identified software tools and technologies to further evaluate and exercise during the AnCOR DATA Demo. Emphasis was placed on tools that are currently available commercial off-the-shelf (COTS) or government off-the-shelf (GOTS) and appeared to have features that would meet the largest number of users' expressed needs. Tools recommended in Phase 1 for further evaluation included: Esri's ArcGIS Field Apps Suite - field data capture and mapping capabilities, RadResponder2 (CBRNResponder) - field data capture capabilities and aggregated reporting, Android Team Awareness Kit (ATAK) - increased situational awareness and offline communication needs, and EPA Scribe - storing field and laboratory data. An overview of how the tools were configured and insights gained from exercising them during the AnCOR DATA Demo is discussed in the sections that follow. The project team utilized the 2 While RadResponder was specifically identified during Phase 1, the Federal Emergency Management Agency (FEMA) sponsors a suite of "responder apps" collectively referred to as CBRNResponder that includes access to both RadResponder and ChemResponder (and soon, BioResponder). The demonstration evaluated CBRNResponder. 9 ------- outputs from both TOTS and SQUIREL (discussed in Chapter 4) in conjunction with the field data acquisition software. Esri provides a large suite of tools to support geospatially-driven tasks and analyses. EPA provides an enterprise-level offering for Esri's suite of tools. AnCOR DATA Demo participants only evaluated Esri's ArcGIS Field Maps tool during the exercise, whereas the project team utilized Esri routing tools for planning and the ArcGIS Dashboard and Tracking tools during the demonstration. 5.1.1 ArcGIS Pro Linear Referencing (Create Routes) The routing of teams for sampling or decontamination purposes is a significant challenge. Teams could encounter hazardous environments and/or spread contamination to otherwise clean areas. Because many of the tools evaluated in support of the AnCOR DATA Demo are GIS-based, the project used advanced geospatial capabilities [7] to determine optimal paths according to time and distance. Sample designs were transitioned directly from TOTS into ArcGIS Field Maps (TOTS automatically publishes sample designs to an ArcGIS Field Map web map with attributes to customize a data capture template). Using ArcGIS Pro's Linear Referencing (Create Routes) feature, samples were automatically grouped according to proximity, and paths were drawn specific to start and end locations. The results of this analysis were used to determine sample sequence (i.e., the sequence in which samples are collected). The resulting pathways could then be made available to other geospatial tools to support sampling team navigation. Figure 7 shows the resulting pathways teams (point color indicates team association) used to navigate to samples. 5.1 Esri's ArcGIS Field Apps Suite Figure 7. Assigned team sampling routes. 10 ------- 5.1.2 ArcGIS Field Maps To support teams navigating to sampling locations, recording and documenting field data, and managing team assignments, a customized template for ArcGIS Field Maps was developed. ArcGIS Field Maps is an all-in-one application that uses data-driven maps to help mobile workers perform data collection and editing, find assets and information, and report their real- time locations. Field Maps supports both iOS and Android mobile operating systems and can operate in offline mode (for saving data locally) [8], Since Field Maps is based on a full-scale GIS platform, custom aerial imagery and feature layers (e.g., sampling points, paths, and boundaries) can be used to support situational awareness. Field Maps includes an integrated navigation capability that indicates the distance and bearing to the assigned sample. The tool visually prompts the user once they have reached the designated sampling location and documentation can begin. The tool further includes image and video capturing capabilities, a built-in QR code scanner, and conditional inputs for documenting sample types, sampling start/finish times, and observations. The AnCOR DATA Demo project team created tailored data capture templates for use in the demonstration. Figure 8 illustrates the steps that are required to document a sample using the AnCOR DATA Field Maps data capture form: 1) Select Sample (far left): Samples are shown in sequential order according to the most optimal path. The user selects the appropriate sample to initiate navigation. 2) Navigate (left center): The user's current location is displayed with reference to the sample location. The distance and bearing to the assigned sample are shown at the bottom of the screen. 3) Scan Sample Bag (right center): The user scans the QR code attached to the equipped sample bag. The sample ID is then appended to the sample location ID. The tool then provides special instructions regarding the location or sampling procedures. 4) Document/Record (far right): Once the user scans the sampling bag, the remaining input fields are unlocked. The form automatically collects start/end times, information on the surface sampled, and observations. The form was designed to be completed within 60 seconds and is stylus friendly. Once completed, the form is either saved to the device locally when operating in offline mode or saved to ArcGIS Online (the Esri Cloud) when operating in online mode. 11 ------- q Team 1 Sample 1 G3 Team 1 Sample 1 Instruct Take a picture of the ground Figure 8. AnCOR DATA Demo Field Maps field data capture form. x-n Team 1 Sample 10 35.881836*N 78.869953'W 3ซซซn wซ. 5.1.3 ArcGIS Dashboards A customized ArcGIS dashboard was developed to show the status of sample collection activities in real-time. The dashboard is composed of three components: 1) Map (center): the map displays the location and status of each sample (according to team and sequence). The color of the sample changes according to the surface type sampled. The status of samples is updated instantaneously (when operating in online mode); 2) Status (top right): the status counter displays the total number of samples plotted versus the total samples remaining to be sampled; 3) Bag Scans (bottom right): the sampling bag scan section displays the sampling bag ID and sample location ID as they are scanned. This view can be used to detect erroneously scanned sample bags or locations. A screenshot showing the AnCOR DATA Demo dashboard is shown in Figure 9. 12 ------- Data Acquisition Samples Sample Bag Use Team 10 Sample 7 ' Sponge-190-9/15/2021.10:30:26 AM Team 10 Sample 6 SPONGE-186 - 9/15/2021,10:27:12 AM Team 10 Sample 2 Sponge-199-9/15/2021. 10:12:40 AM Team 10 Sample 3 Sponge-198 - 9/15/2021,10:17:18 AM Team 10 Sample 4 Sponge-193-9/15/2021.10:19:13 AM | Lttupdsto * foy fCGrefr ซgo Number of Finished Samples I Lmt updai*: * fov mcc-oj *50 Figure 9. AnCOR DATA Demo ArcGIS dashboard. The dashboard can also be used to indicate the location where the sample was taken compared to its intended location. Figure 10 shows a few instances in which the sample diverged from its intended location (the white dot indicates the intended sample location, and the colored dots indicate where the sampling team was located when they recorded the sample). This information is also shown in real-time and could be used to identify samples taken in the wrong location. Figure 10. Example of misplaced samples. 5.1.4 ArcGIS Tracker In addition to optimizing navigation, the AnCOR DATA Demo also evaluated Esri's ArcGIS Tracker solution for tracking teams in real-time. Teams that were assigned cellular-activated tablets were tracked throughout the duration of their sampling activities. The functionality can be 13 ------- combined with the dashboard to improve situation awareness, health and safety, and the potential for plotting new samples in-situ depending on a given team's location. Figure 11 shows a screenshot of a team's completed route (the top of the figure indicates true north). The teal- colored line indicates the precise path they traveled. The circle containing the letters "TB" indicates their current location. This information can be relayed back to the command post to provide situational awareness and mission status updates. ฉ Sep 16, 2021 8:00 AM - Sep 16,2021 11:00 AM & 1 User * m m W if* Figure 11. Example tracking route. 5.2 CBRNResponder While the AnCOR program was designed to address a biological agent contamination incident, Phase 1 research identified RadResponder (a collaborative tool for responding to radiological or nuclear emergencies) as a candidate tool to evaluate, along with a new tool, BioResponder, to assess potential applicability/expansion to support a biological event. The BioResponder tool was under development during the project study period but is expected to aid with the collection of biological samples and laboratory analyses [9], Following the completion of Phase 1 research, a single platform for accessing all CBRN event types was launchedCBRNResponder. CBRNResponder is a free application for emergency response organizations that is sponsored by the Federal Emergency Management Agency (FEMA) and other federal partners [10], As of September 2021, the full scope of data fields was unknown, and the applicability to the biological sampling events in this context (versus an epidemiological context) could not be assessed at that time. Nonetheless, the project evaluated the overall CBRNResponder framework that was available to determine potential applicability to support the AnCOR program. Similar to the Esri Field Apps suite, AnCOR DATA Demo participants only evaluated the CBRNResponder Field Data Collection application during the exercise, whereas the project team utilized the CBRNResponder website to access Event Management and Dashboards for planning and oversight during the demonstration. 14 ------- 5.2.1 Event Management and Configuration The AnCOR DATA Demo project team established an account with the CBRNResponder support team. A test event, DATA Day Test, was created to facilitate exercising the application. The project team evaluated the different data types that are included to support field data collection. For the demonstration, the team focused on the "Sample" and "Observation" data types. Figure 12 below illustrates many of the available data types available for selection. Prescribed data fields that are tied to specific data structures present some challenges given the need for flexibility to nimbly respond to changing data needs. Depending on the phase of an event, event type, and primary sampling objectives, what needs to be collected/characterized could change, and there does not appear to be a way to easily tailor sampling methods (only an "other" "sample type" can be created for an organization). Therefore, for the AnCOR DATA Demo the project team selected representative data types that most closely represented what data needed to be collected. Participants were instructed to ignore other irrelevant data fields and to only focus on a subset of fields to collect, including: Sample Type (Swipe), ID/Barcode (Scan sample bag QR Code), Surface Area/Units, Comment, and Photograph (via Attachment). A sample type of "swipe" (e.g., wipe sample) was selected for demonstration purposes. The types of sampling methods that will likely be needed for the AnCOR program (i.e., swab, microvac, aggressive air, or other innovative methods) do not currently align with the methods that are available for selection within the CBRNResponder application. The ability for users to add user-defined sample types or other "flexible" user-defined fields on an ad hoc basis is needed to meet EPA's needs. Once the field survey form to support data collection was defined, the project team defined the sampling locations for the event. A "Facility" was established to permit an association with Restore visibility Select All Figure 12. CBRNResponder data fields. 15 ------- sampling locations. The EPA RTP campus was used as a surrogate facility. Sampling locations can be entered one at a time (search/click on a map, enter latitude/longitude, or enter address) or pre-existing sample locations can be bulk uploaded via an Excel-based format with predefined coordinates using a provided template. While CBRNResponder allows shapefiles to be uploaded for reference during an event, there is not currently a feature that would allow a user to import/integrate geospatially-referenced sample locations from a map (e.g., using TOTS output with sample locations mapped). An additional data transformation would be required to generate and convert a shapefile to a CSV file to facilitate upload within CBRNResponder. For the demonstration exercise, going through this process (or manually transposing the coordinates) was not an issue. However, for a wide-area event that might require taking hundreds or thousands of sample points, the ability to rely on a single data source of geospatially- referenced sampling locations on a map is importantboth to minimize extra processing steps and to avoid data transformation errors. For the AnCOR DATA Demo, sample coordinates from TOTS output, along with sampling instructions, were manually entered into the provided template, and the template entries were bulk uploaded to the event. Figure 13 presents an example of a completed template. Sampling Location Import [This upload is for adding sampling locations to selected facility. **A location is required, enter a latitude/longitude OR address** Name Latitude Longitude Street Address City State Zip Description Sample 1 35.88338 -78.870621 Sample surface using the provided sampling bag; data person should video the process Sample 2 35.883598 -78.870829 Locate and take picture of a spray painted rock Sample 3 35.883251 -78.870548 Switch places: hand the device over to your teammate. You may switch back after completing the next point Sample 4 35.883062 -78.870487 Sample surface using the provided sampling bag; data person should video the process Sample 5 35.882878 -78.870344 Locate and take picture of a spray painted rock Sample 6 35.882193 -78.870162 Sample surface using the provided sampling bag; data person should video the process Sample 7 35.882373 -78.870157 Sample surface using the provided sampling bag; data person should video the process Sample 8 35.882527 -78.870198 Locate and take picture of a spray painted rock Sample 9 35.882702 -78.870273 Locate/scan laminated QR code Sample 10 35.882009 -78.869945 Locate and take picture of a spray painted rock Figure 13. CBRNResponder sampling location import template. Once sample locations were established, the project team then created sampling team assignments to facilitate completing sampling and data collection tasks. Using the CBRNResponder website, assignments could be established one at a time or bulk uploaded by completing a provided template where both individual and team assignments could be made. For the AnCOR DATA Demo a single team was established, and assignments were associated with specific teams and automatically associated with predefined sample locations (latitude/longitude) and instructions. Figure 14 shows a completed sample bulk assignment template. 16 ------- Import Allowed Values Field Team (on event) Facility Sampling Location Team Shed Row EPA Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Sample 8 Sample 9 Sample 10 Figure 14. CBRNResponder assignment import template. 5.2.2 Field Data Collection Several participants used the CBRNResponder application to assess its potential for wide-area incident response. Figure 15 and Figure 16 present the series of steps participants completed to simulate data collection activities (orange boxes illustrate user interface click-events): 1) Select Event (Figure 15, top middle): Events listed for selection. 2) Submit Data (Figure 15, top right): Initiate sample data collection. 3) Choose Assignment (Figure 15, bottom middle): Review instructions and select assignment. 4) Review Assignment and Navigate to Sample Location (Figure 15, bottom right): Review details and select one of several actions. 17 ------- DATA Day Test Respond to Emergency Click here to view all active emergencies. My Events o From My Org Shared w/ Me DATA Day Test US EPA Homeland Security Research Prograi Testing/Training 09/09/2021 0:00 - 9/17/21 DATA Practice US EPA Homeland Security Research Prograr Exercise/Drill 09/02/20210:00 - 09/03/2021 23:ฃ9 Emergency Response US EPA Homeland Security Research Prograi Emergency Response 08/30/2021 9:07 - Ongoing i Routine Monitoring US EPA Homeland Security Ress arch Program Routine Monitoring " y [ Accuracy: 14m Tracking: Off ft ft Collected Data Resources Accuracy: 5m Tracking: On O 4 ft O A Team Shed Row 0 incomplete Sample surface using the provided sampling bag; data person should video the process ฆ Team Team Switch Manage Responder Tracking Click "Enable Tracking" to begin tracking your location. Enable Tracking Cancel Team Shed Row ฉ Incomplete Locate and take picture of a spray painted rock in Team Shed Row ฉ incomplete . Switch places: hand the device over to your teammate. You may switch back after completing | the next point Sample surface using the provided sampling bag; data person should video the process Due Date No due date specified Proximity in meters No proximity specified 35.88338, -78.87062 Navigate to Assignment Assignment Team Shed Row Q incomplete ; Sample surface using the provided sampling bag; data person should video the process ill Team Shed Row ฉ incomplete : Sample surface using the provided sampling bag; data person should video the process Mark assignment complete Record data for assignment El Tracking: Off m i \ Accuracy: 11m Tracking: On O fl Accuracy: 5m Tracking: On ft * c ซ O A * G /Mens Assignments ซ P & Figure 15. CBRNResponder App screens for field data capture - Part 1, 5) Navigate: Opens user's device mapping program to provide navigational support. Requires leaving the CBRNResponder application to toggle between the mapping application and the field data collection application. CBRNResponder's navigation capabilities are limited to vehicle navigation using standard mobile routing platforms (Google/Apple maps). 6) Initiate Data Collection (Figure 16, middle): Users click to record data and specify the data type to record. As previously noted, sample and observation data types were used for the demonstration. The sample detail screen is made available for data entry. 7) Record Data (Figure 16, right): The user can select a sample type and scan the QR code attached to the equipped sample bag to populate the ID/Barcode. Required fields are denoted by an asterisk and photographs can be added and linked to the sample using the 18 ------- Attachments feature. The tool automatically captures basic metadata (user, date/time, and location details). Once data entry is complete, the user can click the save button (shown as a disc icon) in the top right. 10:56 ill ^ ฆ < Assignment 11:03 f < Submit Data 10:58-? a X Create Field Sample Assignment has not yet been completed Details Name No name specified Instructions Sample surface using the provided sampling bag; data person should video the process Due Date No due date specified Proximity in meters No proximity specified Location 35.88338, -78.87062 Navigate to Assignment Location View Assignment Location on Map Mark assignment complete Record data for assignment Accuracy: 5m A 6 Alwtt Assignments Tracking: On 0 Choose a Data Type All Chem Rad t ฉ Survey * Observation Field Screening Radiological Spectrum G. - i.. H ฆ VI Reading Chemical Chemical In.*ฎ Chemical SITREP rri Dose Reading Ad-Hoc Accuracy: 5m Tracking: On 0 Sample Details Sample Type Swipe > Is Background? ID/Barcode * CN-XXX-XXXXX M Surface Area X.XX Surface Area Unit > Comment Attachments O Click the add button to add attachments. Please do not include photos with personnel. Contact Dose Rate Accuracy: 5m r> Alignments Tracking: On 0 o Chat Figure 16. CBRNResponder App screens for field data capture - Part 2. Once data collection is complete, users submit data to an online data repository. Depending on whether the device is operating in on- or offline mode, data will synchronize once a connection is available. Data can then be viewed by event managers, as well as users through the application (Figure 15, top right - Collected Data). Data can be exported from the platform; however, individual data types must be separately downloaded. 5.2.3 Event Dashboard and Map A preconfigured event dashboard is available to support event management. During the AnCOR DATA Demo, data managers could track field personnel using the map and predefined metrics could be arranged on an event dashboard to monitor a variety of metrics (e.g., data/type collected, field teams, assignments, organizational partners). Figure 17 presents an example event map. Available features facilitate interacting with the map and tailoring views depending on the types of questions needing answers. For example, specific responders could be isolated to track status, sample status can be accessed, assignment information can be viewed, and additional GIS files can be viewed. Note, however, that GIS files must be uploaded to the platform and are not directly integrated with any ArcGIS online capabilities. Data captured 19 ------- within the platform can be exported into different formats, including keyhole markup language (KML), shapefile, and CSV. ป DATA Day Test ~ & EPA/HSRP ~ i About ~ ซ5 Our Network ~ ซS Resources ~ Of Contact Search address Filters Layers 0 ฉ T Quick Views - PI Saved Views - Jk Downloads - 9 ฉ \ \\\\ WW Q (J) (-. Road S Event Information Optio... User Data Options (ฉ) ฉ % <0> m % WW \ \Y WW WW vW WW WW Figure 17. CBRNResporider App event map for monitoring activities. 5.2.4 Reports CBRNResponder offers a variety of preconfigured reports that can be generated [11], The AnCOR DATA Demo did not fully evaluate the range of offerings; however, two features that might be of interest include the ability to create barcodes and generating chain of custody forms. Barcodes can be generated for sample labels in advance of a sampling event and scanned using a device's camera. Figure 18 below illustrates a screen for supporting the creation of sample labels. Print Sample Labels Use the drop down boxes to select the quantity of unique labels and number of copies of each you would like to print. Click Generate Labe to generate a PDF of labels for an Avery 5160,30 labels per sheet, template. Organization * us EPA Homeland Security Research Program Print Type' Print New RadResponder Sample Collection # Quantity * 30 Copy Quantity ' 2 Label Prefix Barcode range to be printed: SCN-04D-000001 - SCN-04D-000030 mill Sample PDF417 Barcode I SCN-04D-000001 RadResponder Sample Collection # I SCN-04D-000002 Figure 18. CBRNResponder App supports generating sample labels. EPA also expressed the need for a feature to create chain of custody forms and electronic data deliverables to convey the information required for laboratory analyses. CBRNResponder can 20 ------- support creating Sample Control Forms (SCF) (chain of custody) and Analytical Request Forms; however, the ability to customize and/or tailor elements that are included on the form is currently unavailable. For SCFs, users can select existing samples and general information will be prepopulated, including the barcode. Figure 19 illustrates an excerpt of a system-generated form. JXBRN Responder General Information Sample Type: Swipe Collected By: Boe, Timothy Collected Date: 09/16/2021 09:05 Field Team: Team Shed Row Sample Status: Collected Volume: Weight Comment: Figure 19. CBRNResponder chain of custody form example. 5.3 Android Team Awareness Kit (ATAK) Android Team Awareness Kit (ATAK) is a tool that was developed by the DHS Science and Technology Directorate (S&T) and has been adopted by multiple agencies, including the Department of Defense (DoD). ATAK allows the user to submit and receive real-time spatial awareness information and communicate between responders across multiple agencies [12], The project team had initially planned to evaluate ATAK as part of the AnCOR DATA Demo; however, the team experienced several impediments that prevented its full implementation, including lack of access to a detailed user guide describing how to use the tool. ATAK lacked a centralized dashboard for designing and implementing activities. Points of interest (i.e., samples) were shared directly with test devices using email to send .shp/.kmz files to each individual device. A basic viewer within ATAK was established for locating and tracking samples (Figure 20). Additional limitations included viewing and documenting data associated with a given point (i.e., participants could not easily document information as demonstrated in the Field Maps and CBRNResponder tools). Lastly, at the time of publishing this report, ATAK was limited to Android devices (an iOS application was under development and available for testing, but lacked critical features supported by the Android version). ATAK did feature functionality that was not available in Field Maps and CBRNResponder, including direct messaging, team proximity information, line of sight, and mobile ad-hoc networking. Sample Control Form Chain of Custody 111 MM Sponge-106 Location: 35.882124 /-78.870180 Location Status: 21 ------- Figure 20. Screenshot of ATAK viewer showing samples and route with aerial image overlay. Because essential features necessary to fully investigate this tool could not be fully implemented within a period of time comparable to that of Field Maps and CBRNResponder, the AnCOR DATA Demo project team decided to forgo testing ATAK at the AnCOR DATA Demo. This tool should be fully investigated in the future once additional functionality and guidance are made publicly available for supporting biological sampling. 5.4 EPA Scribe Scribe is a desktop-based software tool developed by EPA's Environmental Response Team (ERT) that is available to EPA personnel. The tool supports storing and managing sampling, observational, and monitoring field data. Scribe allows users to produce outputs for collected samples for analytical data reports. Scribe can import a variety of data, and scripts can be saved to manage import mappings [13], The Scribe tool is routinely used by ERT; however, the AnCOR DATA Demo did not include a full data workflow that integrated analytical data communication to/from laboratories. Therefore, Scribe was not exercised during the demonstration. Data collected as part of exercising field data collection tools and software were instead stored on EPA's GeoPlatform for the AnCOR DATA Demo. 6 TECHNOLOGY EVALUATION The AnCOR DATA Demo also evaluated GPS and mobile devices to document any notable differences among devices that were used to support field sampling data collection activities. 6.1 Global Positioning System (GPS) Devices Sub-meter GPS receivers provide relative positional accuracy (hence the name, accuracy within 1 meter) and are used to determine the user's position, locate objects/areas of interest, and support navigation. The accuracy of these units is largely impacted by end-user experience, atmospheric effects, and multipath effects (i.e., the GPS signal is reflected or diffracted from the 22 ------- local objects). For a biological incident, sub-meter GPS receivers may be used in combination with data acquisition systems to aid navigation when challenged with sampling designs that reference predetermined sample locations. Several commercial sub-meter GPS receivers are available. A select group of participants in the AnCOR DATA Demo evaluated the following sub-meter GPS receivers: 1) Arrow Series GPS, 2) SXblue, and 3) Geode. The demo also evaluated the built-in GPS chip found in Apple's Wi-Fi + Cellular iPad models (iPad Air 2). A survey-grade receiver was used to capture control points in five separate locations (Table 1). Table 1. GPS Test Locations Location ID Description Estimated Signal Blockage A Adjacent to forest 50% B Parking lot 0% C Close proximity (10 feet) to 50-foot structure 50% D Field with trees 25% E Dense forest 100% A multi-station equipped with a laser-based precise long-range scanning capability (LeicaNova MS50) was used to capture precise locations in areas that might introduce multipath interference (e.g., tree canopy coverage, buildings). A picture of the multi-station and the associated prism is shown in Figure 21. Using the parking lot location (i.e., open sky) as a reference point, the multi- station was used to shoot the four other locations. This approach provided a horizontal accuracy of < % in. Figure 21. Leica Nova MS50 multi-station and associated prism marker. 23 ------- The accuracy of these measurements was compared against a known National Geodetic Survey benchmark. Figure 22 shows a picture of the horizontal control used to support this evaluati on. Figure 22. National Geodetic Survey benchmark. Once the control points and horizontal accuracy were determined, personnel equipped with the prescribed GPS devices (Arrow Series GPS, SXblue, Geode, iPad Air 2) navigated to each test location (control points were marked on the ground using orange tape). At each test location, participants would stand directly over the orange marker, wait for 15 seconds, and capture five successive points (using a custom ArcGIS Field Maps template) every 10-15 seconds. The resulting points were then plotted in a GIS application to determine relative distance from the control point for each test location. Figures 23-27 show a scatter plot map for each test location (A-D), respectively. The control (red point) is shown in the center of the circle, and the surrounding buffers represent the distance from the centroid of the circle (i.e., 2D horizontal error). Overall, the Geode consistently outperformed the SXblue, Arrow, and iPad Air 2 (<3 ft of accuracy for this test condition). Table 2 shows the average horizontal error for each device and location. 24 ------- / N20ft / O \ / \ i * " " " *ฆ ซ. \ / /' "" S \ ' x' "v * ' / s / / s 10 ft / / \ F ' ~ \ ' ~ " X ' / - \ 5ft ^ ' ' ^ " - N. V ^ I ' ' \ 3 ft * I I //_<*ป \ \ , I I I ' ~ > 1ft ( I , I I 1 J * J 1 I , t \ *ฐฐ0 / ป , V ' \ ' ' V > ' / V \ / / ^ S ~ / \ N ~ / \ \ / \ \ / \ \ / O Geode \ \ O Arrow O SXblue O'Pad / / Figure 23. Horizontal error for test location A. / \ / ^ \ / ^ ^ \ / ^ s \ ' / \ * / ~ N \ / ' ^ 5ft \ / 7 ^ \ / '%."* \ ' / /' * \3ft N * ' ; / \ \ 1 ' ' ^->ift x 1 i i ,. \ \ i / \ i i 1 1 ' i t / i i 1 v \ ~ - ' II > I \ \ / l I \ x \ / / / I \ / / \ \ v , , ' / / \ S ' / \ N ' / \ N " / >. x* \ ^ ^ ^ ^ / \ / \ O / 0 Geode S ~ . \ / ฎ Arrow N / ฉ SXblue \ ~ \ ~ O iPad Figure 24. Horizontal error for test location B. 25 ------- / 0 \20ft / \ / ฐ V / , " - \ / O \ I ' v V ' ! '' ~ Vvsft \ 1 : 'V-.Vr* \ ' \ ; ' ; ! ' v X ' / ' \ N ^ ' / ' * \ - - / ' v \ ~ / \ v ' / X "v / \ ^ - " / ^ ^ O Geode \ / N ~ O Arrow s ~ x ~ ฉ SXblue s / N ^ ^ ^ ^ O iPad Figure 25. Horizontal error for test location C. ' v 10 ft / \ / \ / \ / \ t N / ^ s \ ' ~ s 1 .: ' /7 - -* \ * / , ' ^ 3ft v t / \ ' / / \ 0 X 1 ' ' ' .-.1ft V o * ' ' I 1 . , 1 I ' ป V / ' I 1 \ V ฆ> _ -' I I 1 I \ \ O / I I \ X s <0 / , I \ \ / / \ \ - ^ , ' / / \ N " ' / \ v ~ / \ > * ' / ^ N X ^ \ # ^ / \ // 0Geฐd= ^ ' O Arrow N ~ \ / O SXblue S N y' O 'Pad Figure 26. Horizontal error for test location D. 26 ------- t O Geode / \ / 3 Arrow \ O SXblue Figure 27. Horizontal error for test location E. Table 2. Average Horizontal Error (ft) by Location and Unit GPS Unit Adjacent to Forest (A) Open Sky (B) Near Tall Structure (C) Field with Trees (D) Dense Forest (E) Average STD Geode 1.35 0.34 1.56 1.60 1.59 1.30 0.57 Arrow 1.07 0.91 10.27 5.43 2.05 3.95 4.07 iPad Air 2 11.78 5.29 8.26 4.14 8.41 7.58 2.74 SXblue 1.84 2.43 15.43 2.82 6.95 5.93 5.33 STD - standard deviation Overall, the Geode outperformed the other devices at all five locations. The Geode had the lowest average horizontal error (1.3 ft) and STD (0.57 ft). It should be noted that horizontal error can also be a condition of satellite geometry, signal blockage, and atmospheric conditions, which can vary by location and time of day/year. These conditions were not evaluated as part of this study. A control point (horizontal control) should be taken to assess conditions and accuracy prior to using a sub-meter GPS. 6.2 Mobile Devices The AnCOR DATA Demo evaluated multiple electronic devices capable of documenting samples, uploading data, and connecting to sub-meter GPS units. The devices evaluated as part of this study included: 1) Samsung - Galaxy Tab S7 tablet (Android, 11), 27 ------- 2) Apple - 7.9-Inch iPad mini (5th Generation) with Wi-Fi (iOS, 10.3.4), 3) Apple 10.2-Inch iPad Air 2 with Wi-Fi + Cell (iOS, 10.3.4), and 4) Apple iPhone XR with Wi-Fi + Cell (iOS, 10.3.4). These electronic devices were evaluated based on general performance and user feedback. Participant feedback is discussed in Chapter 8. Generally, key issues centered on: Battery life, Screen brightness, Bluetooth connectivity, and Proper configuration (e.g., cellular data access, camera access, time out settings). 7 DATA MANAGEMENT AND REAL-TIME QUALITY CONTROL MEASURES Phase 1 research identified important data management needs, including: Addressing secure, bulk data uploads (e.g., once an internet connection is re-established), Storing and processing large quantities of data, and Analyzing results in a collaborative platform. The Phase 2 AnCOR DATA Demo exercised field data capture software capable of capturing data while in the field and submitting and synchronizing data to a consolidated online platform. 7.1 ArcGIS Field Maps Data Storage Esri's ArcGIS Online (EPA's GeoPlatform) was used to store data collected using the Field Maps application. Data that were uploaded through Field Maps were automatically formatted into the appropriate schema and text entries were limited. This approach reduces the risk of generating inoperable data that break the schema specified by the data manager. Furthermore, ArcGIS Online supports adding imagery and video and associates supporting media files with sample data linked to specific geographic locations. An example data view is shown in Figure 28. Q GroupID Team 3 Nav_Seq Q Instruct rg Sample Bag iD Q Texture/Surf... g Start Tirne/D... Q. End Time/Date : Take a picture of 59 you end your teammate Take a picture that Sportge-60 shows the ground and the sun Take a oicture of Sponge-75 Sponge-76 Vegetation Vegetation 9/15/2021, 11:24:03 AM 9/15/2021, 11:27:33 AM 9/15/2021, 11:40:23 AM 9/15/2021, 11:36:20 AM 9/15/2021. 11:24:34 AM 9/15/2021, 11:28:14 AM 9/15/2021, 11 ;40:41 AM 9/15/2021, 11:36:27 AM >ane in way Osne in way. May have duplicated QR code Sherlock Ho'mes Figure 28. Table showing a sample of ArcGIS Field Maps data collection results. 28 ------- 7.2 CBRNResponder Data Storage CBRNResponder data are stored in a Microsoft Azure Cloud environment managed by vetted site administrators from the vendor organization that manages CBRNResponder for FEMA. Data uploaded are owned solely by the collecting organization and are only visible to other organizations if an organizational administrator provides explicit access to the data [14], Uploaded data are formatted according to specific schema defined for various data types. Use of drop-down lists and limited free-form text entry fields is common among the different data types. Image files and documents can be uploaded and associated with a data point using the Attachments feature. Figure 29 illustrates a sample table of CBRNResponder data collection results. Columns to display can be tailored and each data record can be expanded to view the full record, including any attachments associated with the data point. A Samples _ ilmp< d Print - Analytical Results B Update Statuses ฆป | B Assessment Mode | + Create Sample T Filters > Q. sponge E ^ Exact O Choose Visible Columns $ ID it Collected Date/Time it TVpe it ID/Barcode It Source it Status it Team it Recorded By it Latitude it Longitude it Facility it Surface it Material it Latest Assessment Status it 1765252 09/16/2021 8:23 Swipe Sponge-12 iOS Collected Team Shed Row Rodgers, Molly 35.879863 -78.86886 - 1765253 09/16/2021 9:05 Swipe Sponge-106 Android Collected Team Shed Row Boe, Timothy 35.882124 -78.87018 - <21 1765254 09/16/2021 9:09 Swipe Sponge-100 iOS Collected Team Shed Row Rodgers, Molly 35.882026 -78.869977 - GK 1765255 09/16/2021 9:22 Swipe Sponge-101 iOS Collected Team Shed Row Rodgers, Molly 35.882373 -78.870125 - 1765256 09/16/2021 9:25 Swipe Sponge-107 Android Collected Team Shed Row Boe, Timothy 35.882595 -78.870225 1765257 09/16/2021 9:27 Swipe Sponge-102 iOS Collected Team Shed Row Rodgers. Molly 35.882717 -78.870268 1765258 09/16/2021 9:29 Swipe Sponge-103 iOS Collected Team Shed Row Rodgers, Molly 35.882717 -78.870268 Q. 1765259 09/16/2021 9:32 Swipe Sponge-108 Android Collected Team Shed Row Boe, Timothy 35.882609 -78.87026 - GK 1765260 09/16/2021 9:34 Swipe Sponge-105 iOS Collected Team Shed Row Rodgers, Molly 35.883043 -78.870458 - 1765261 09/16/2021 9:37 Swipe Sponge-109 Android Collected Team Shed Row Boe, Timothy 35.882844 -78.87035 - 1765262 09/16/2021 9:38 Swipe Sponge-I07a iOS Collected Team Shed Row Rodgers. Molly 35.883315 -78.870587 : 1765263 09/16/2021 9:42 Swipe Sponge-108a iOS Collected Team Shed Row Rodgers, Molly 35.883556 -78.870822 1765264 09/16/2021 9:43 Swipe Sponge-110 Android Collected Team Shed Row Boe, Timothy 35.883192 -78.870458 - 25 v Showing 1 to 13 of 13 entrie. (filtered from 14 otal entries) Previous Q Next Figure 29. Table showing a sample of CBRNResponder data collection results. 7.3 Real-Time Quality Control Measures Quality control (QC) is an integral part of data collection for any event. For emergency response and recovery activities, it is essential that field data capture forms are designed to minimize data entry errors and that sampling activities are monitored in real-time to identify and correct erroneous entries during a sampling episode if possible. Examples of real-time corrections could include: Reporting an incorrect sample method based on sample bag QR code (swab versus microvac), Reporting an incorrect sample matrix, or Capturing the sample at a distance outside of an established threshold designated by the sample design. 7.3.1 ArcGIS Field Maps QC The AnCOR DATA Demo evaluated data in a two-step process: 1) Error Checking: the Field Maps form was designed to prevent users from entering erroneous data by confirming that input fields contained expected characters or limited free-text entries. If an error in the input menu was 29 ------- discovered or left blank, the tool would notify the user; and 2) Remote Review: since the AnCOR DATA Demo featured the real-time collection of data, the dashboard and associated data layers presented a unique opportunity to review data while sampling was underway. During the demo, two remotely located EPA personnel were asked to review data as they were uploaded to the cloud. Reviewers could either monitor the dashboard or the raw data (shown in Figure 9 and Figure 28, respectively). 7.3.2 CBRNResponder QC While data captured using CBRNResponder were not explicitly reviewed by a dedicated team during the collection event, the applications dashboard and data collection views would enable real time data review (see Figure 17 and Figure 29). CBRNResponder also makes use of controlled data entry elements; however, there appears to be less flexibility to customize data validation rules as users are bound by what the application offers out-of-the box. A feature not exercised, but advertised as forthcoming, is a Chat function. The feature would presumably be very useful to quickly communicate/chat with a responder to convey any issues that might need correction/resolution while out in the field. 8 DATA DAY DEMONSTRATION PARTICIPANT OBSERVATIONS AND FINDINGS A summary of observations and feedback provided by the AnCOR DATA Demo participants is provided. Input is organized first by general observations, followed by specific topics. 8.1 General Observations and Participant Feedback Participant feedback was collected through several different avenues including: Debrief sessions (after Day 1), Field observations (observer who accompanied different teams), Verbal communication with participants, and Populated via an online feedback form. The observations and feedback findings are organized by the following topics: 1) Demo implementation; 2) Operational feasibility; and 3) Technology and software evaluation (GPS, mobile devices, and software). 8.1.1 Demo Implementation Overall, participants felt that the demonstration was well organized and implemented. The following are the major findings: Optimize routes to ensure that distances in-between samples are reasonable (i.e., distance and time necessary to travel between the sampling locations) and make sure routes avoid non-access areas or work zones; Ensure the most current aerial imagery is available to reference; Configure technology pairings in advance (e.g., assign GPS units to tablets and note identifying IDs); 30 ------- Note team associations/assignments to expedite teams moving through initial stations; and Document what team is associated with a specific device ID. 8.1.2 Operational Feasibility The AnCOR DATA Demo project team evaluated the feasibility of several important feasibility considerations related to technologies and data management operations in the field. 8.1.2.1 Just-In-Time Training Just-in-time training was provided to participants prior to entering the field. Participants with limited experience using the prescribed technologies received the same level of training as those who were considered experts (through routine use). Feedback from participants concluded that just-in-time training was inadequate for personnel who had never interacted with the prescribed technologies. The following are findings that could help prepare responders for a sampling event: Provide routine training to both emergency response and surge capacity personnel (including researchers) for both data capture software and technologies that would be used during a response. Offer interactive, step-by-step training (either in person dry-runs or via PowerPoint or MS Teams) prior to sampling in the field. Distribute laminated instruction cards that provide quick tips and troubleshooting solutions to sample teams. 8.1.2.2 PPE Limitations Teams were randomly asked to use thick garden gloves (to mimic nitrile work gloves and/or task-specific gloves representing PPE types B, C, or D; level A or encapsulated B with the thick butyl rubber gloves are not approximated with thick gardening gloves) and were equipped with a stylus. Teams were asked to provide feedback on limitations in dexterity while operating the tablets. Overall, teams found it easy to navigate the devices and enter data on the forms using a stylus while wearing PPE. However, it should be noted that teams did not fully mimic a response requiring full Level C, including respirators, where a reduction in mental and possibly physical acuity might be experienced. 8.1.3 Technology Evaluation The AnCOR DATA Demo evaluated GPS and mobile devices to document any notable differences among devices that were used to support field sampling data collection activities. 8.1.3.1 GPS Evaluation In the AnCOR DATA Demo, built-in GPS on the tablets/phones or sub-meter GPS receivers (Arrow Series GPS, SXblue, Geode) used in combination with tablets were used to locate and navigate to predetermined sampling locations. The following key findings are based on user feedback and observations: Sub-meter GPS units worked better than cellular built-in GPS on all the devices evaluated, and the sub-meter units exhibited a better battery life. 31 ------- o Participants noted frustration with fluctuations of the location point on Samsung devices. Overall, with all receivers, but more so with the built-in GPS, signal seemed to be diffracted from local objects and would not stabilize or showed a decrease in accuracy when near solid structures or tree canopies. The Geode sub-meter GPS receiver mounted on a pole was reported as very accurate (,5 ft). The Arrow Series and SXblue sub-meter GPS receivers positioned on hats were more convenient than the Geode GPS on a pole. Sub-meter units need to be stabilized on the hat and face straight upward for best performance and accuracy. Avoid interference from multiple devices in close proximity where Bluetooth connections can sync with a nearby device. 8.1.4 Mobile Devices Multiple electronic devices capable of documenting samples, uploading data, and connecting to sub-meter GPS units were evaluated. Evaluated devices include: 1) Samsung - Galaxy Tab S7 tablet, 2) Apple - 7.9-Inch iPad mini (5th Generation) with Wi-Fi, 3) Apple 10.2-Inch iPad Air 2 with Wi-Fi + Cell, and 4) Apple iPhone XR with Wi-Fi + Cell. The following are general key findings based on user feedback and observations: Sampling events might require a longer battery life and use of an external battery, particularly when maintaining an active WiFi/cellular link to online data repositories, as well as reliance on GPS signals. Carrying an extra, fully-charged external battery would also impact sampling time requirements to avoid needing to return to the support zone (where personnel would need to also decontaminate and don/doff PPE to acquire additional supplies or charged equipment). Screen visibility was limited due to sun and accumulation of fingerprints (expected to be less of an issue when wearing protective gloves). Participants surmised that it would likely be difficult to see the screen with a full-face respirator (FFR). Additionally, increasing the screen brightness for better visibility rapidly drained the battery. Furnishing the tablets with a hand grip would make for easier operations in the field. Training on how to use the tablet's video feature is necessary. Overheating of devices could present issues such as lagging and decreased battery time. Additionally, usability feedback for specific devices was captured and is summarized below. 8.1.4.1 Apple iPad Feedback for the Apple iPad (iPad Air 2 and Mini) was provided by 12 participants. The ease of using garden gloves (i.e., PPE surrogate) and entering notes with a stylus was noted as very easy to average. The ease of capturing a video varied widely and was reported as very easy to extremely difficult. Many participants reported that they did not know to capture the video using the data capture form's "attach" feature - more likely a function of inadequate software training versus the device's camera function. 32 ------- Mixed responses were received on the acceptability of the device's battery performance. Participants noted that when the screen brightness was adjusted to the highest level (to increase the visibility of the screen), the battery drained rapidly. One instance was noted where the device went directly from "low battery, 10%" to a black screen and the device became unresponsive. One participant noted that the extended use of Bluetooth to interact with the Geode GPS unit on the pole might have drained the battery quicker than expected. Most participants agreed that the device withstood harsh field conditions. Several participants noted that the devices felt hot. One participant reported lagging issues (where up to ten seconds passed before screen would scroll or submit would complete) which they believed to have been caused by the heat. Several participants noted that the screen was difficult to see (especially with fingerprints (which might not be an issue with gloves/PPE) and that it would be difficult to see the screen with a FFR. 8.1.4.2 Samsung Tablet Surveys for the Samsung tablet were completed by three participants. The ease of using garden gloves and entering notes with a stylus was noted as easy to average. The ease of capturing a video was reported as very easy to extremely difficult, and it was noted that capturing a video was not possible while using the data capture application. Mixed responses were received on the acceptability of the device's battery performance. Participants agreed that the device withstood harsh field conditions, and one participant indicated that the Samsung table had better optics than the iPad, but would still be difficult to see with a FFR. 8.1.4.3 Apple iPhone One participant provided feedback related to the use of an Apple iPhone (gloves or a stylus were not used). The ease of capturing a video was reported as average and the device maintained acceptable battery performance. 8.1.5 Software As previously described, the AnCOR DATA Demo exercised two mobile field data acquisition software tools: 1) ArcGIS Field Maps and 2) CBRNResponder. User experience feedback provided by participants is summarized in the sections below. 8.1.5.1 ArcGIS Field Maps The following are key findings for ArcGIS Field Maps based on user feedback and observations: Overall, Field Maps worked well, was easy to use, and was a useful data acquisition tool that participants are very likely to use again. Use of "edit" and "copy/copy all" in the software was confusing to participants. Logging information for each point was not intuitive. Users requested a more explicit/obvious user interface control to enable/start data collection for a sample point. Participants suggested incorporating a "done" button when selecting the collection time/date to denote completion of sampling (tracking sampling times were an ancillary data point and expected to be automated in the future). Sample finish time/date might not be necessary to explicitly collect. 33 ------- Participants suggested that it would be beneficial for a different color point or icon to display on the map when a sampling location status is updated to confirm data were successfully recorded. Older iPad devices (iPad Air 2) appeared to more slowly record data and submission failed on several occasions. Entering notes on the form with both gloved and ungloved fingers was easy on all tablets evaluated. Issues regarding scanning QR codes were more likely associated with the label itself (printer/pixilation issue or misprints where the label was partially cut off) rather than an issue with the software feature and/or device camera. Participants suggested adding an option to enter sampler and/or team in the form (or using a QR code to denote the team collecting the sample). Field Maps was fully compatible with offline collection. Data captured were automatically uploaded to the ArcGIS Online as soon as the tablets established an internet connection. All samples collected in offline mode were successfully captured and uploaded. Additionally, user experience feedback focused on the software is also summarized based on the type of mobile device and field data collection application used. 8.1.5.1.1 ArcGIS Field Maps + Apple iPad Air 2 Ten participants provided feedback using ArcGIS Field Maps with the Apple iPad. Five participants reported ease of use with gloves as extremely easy to average (feedback was not provided by five participants). The ease of entering notes with fingers was noted as extremely easy to easy. It was noted that the iPad keyboard is large enough to enter text without difficulty. The ease of scanning the QR code was rated extremely easy to difficult. Participants mentioned some minor glare issues in cloudy conditions where some codes did not scan; however, as previously noted it is likely that issues stem from the integrity of the printed QR code label itself. Toggling between online or offline mode was rated extremely easy to easy, and participants noted that having a preexisting familiarity with iOS is beneficial. The ease of capturing an image using the camera feature was noted as extremely easy to average. For one participant, it was not intuitive to click the arrow icon (in the top right) after you click edit. It was also noted that taking a video requires using a hidden feature under "attachments." The ease of entering data was rated as extremely easy to average. One participant noted that there was 10-15 second latency when moving through the screen. A participant also noted that the calendar stayed open after entering the date, rather than automatically closing. Additionally, activating the data entry dialog was sometimes difficult (e.g., users had to click on the number of the samples and not on the blue GPS dots). The ease of using navigational and GIS features was rated as extremely easy to average with participants noting that the iPad appeared to be more accurate than the Samsung tablet, but still up to 15 feet off. They noted the drift was sometimes more than expected, making it hard to pinpoint the sampling spot. The ease of synchronizing data from mobile app to centralized data storage was noted as extremely easy to easy (not applicable in six responses). 34 ------- Overall, participants responded that it was very likely or likely that they would use this application in the future and recommended having a dedicated scribe to operate the tool, providing an external battery, and furnishing the iPad with a hand grip. 8.1.5.1.2 ArcGIS Field Maps + Apple iPad Mini Five participants provided input regarding the use of ArcGIS Field Maps and the Apple iPad Mini. Ease of use with gloves was noted as average by two participants (not rated by three participants). The ease of entering notes with fingers was noted as easy to average. It was noted that entering notes was slightly more difficult than a normal iPad due to size of the screen, and that the screen was hard to see sometimes due to glare. Consistent with previous tablet observations, adding a hand grip to the device was noted to be useful for the future. The ease of scanning the QR code was rated extremely easy to difficult, with issues occurring in both sunshine and shade. Again, this was more likely due to the printed QR code labels themselves. One participant noted that more effort was required to activate the camera than when using the standard iPad. The ease of toggling online or offline mode was rated extremely easy to average, and that an existing knowledge of iOS helps. Participants noted that switching between edit and the copy/copy all feature for test points is a bit cumbersome and should be avoided. The ease of entering data and capturing an image using the camera feature was noted as extremely easy to easy, with a participant noting that the keyboard is still large enough for easy typing and reiterating that a hand grip would be useful. The ease of using navigational and GIS features was rated as extremely easy to average. The ease of synchronizing data from the mobile application to a centralized data storage location was noted as extremely easy or not applicable. Participants responded that it was very likely or likely that they would use this application in the future. 8.1.5.1.3 ArcGIS Field Maps + Samsung Tablet Four participants provided input regarding the use of ArcGIS Field Maps and the Samsung tablet. Ease of use with gloves was noted as easy to difficult (not evaluated by two participants); however, the ease of entering notes with fingers was noted as easy by all participants. The ease of entering data, scanning QR codes, and capturing an image using the camera feature was mostly noted as extremely easy to easy, although a user mentioned they could not figure out how to provide the application access to the device's video camera. The ease of toggling online or offline mode was rated as easy to difficult. The ease of using navigational and GIS features was rated as easy to average, but participants noted the tablet was not accurate at getting to the point and would continuously move. One participant noted that when they were offline, they had trouble navigating close to the sampling point, especially near buildings. The ease of synchronizing data from mobile application to centralized data storage was noted as easy to average. It is likely that the users would use this application in the future; however, one user noted they did not like the size of the tablet nor the platform (Android) overall. 8.1.5.1.4 ArcGIS Field Maps + Apple iPhone Two participants provided feedback related to their experience using ArcGIS Field Maps with an Apple iPhone. The ease of use with gloves was not evaluated; however, the ease of entering 35 ------- notes with fingers was noted as extremely easy to average. The ease of entering data, scanning QR codes, and capturing an image using the camera feature was also noted as extremely easy to average, although one user did have to take some time to allow the application to access the device's camera. The ease of using navigational and GIS features was rated as easy to difficult, as the iPhone was not accurate and presented an issue with navigating to the sample point. The ease of synchronizing data from mobile application to a centralized data storage was noted as extremely easy with an internet connection (a user did note that the QR code and submittal stopped working when the phone was in airplane mode). It is very likely that the user would use this tool in the future. 8.1.5.2 CBRNResponder Two participants provided feedback on their experience using CBRNResponder during the AnCOR DATA Demo. The following are key findings based on user feedback and observations: Users noted that reliance on the device's default map (e.g., Apple map or Google Maps) was not as user-friendly as the integrated map offered by Esri's ArcGIS Field Maps. Toggling back and forth between the data collection application and a separate mapping application was frustrating for the users. Additionally, the default "mode of transport" required additional setting adjustments to ensure "walking" directions were enabled each time the map loaded. The mapping interface was cumbersome. Users expressed frustration at having to reload the map to view each sampling location where extra time was required to adjust settings and reorient the map. A participant suggested incorporating a toggle yes/no button to confirm a status change rather than having to manually type "Yes" in "Confirm Status Change." Participants noted difficulty rendering QR codes; however, issues were likely a result of the label resolution. The application did not support videos, only images and documents. In the future, correlate assignment descriptions with sample numbers. 8.1.5.2.1 CBRNResponder + Apple iPad Air 2 A participant reported that they could not get walking directions to work when using a satellite basemap (no sample point was visible). Several sample data collection instances did not correctly render the QR scan; however, the QR code could not be later used because the form would not permit a duplicate ID (indicating it was initially read, but not rendered). Given the repeated issues reported about QR code labels, no conclusive comments/issues can be attributed to the software, and users assume the feature should be QR code compatible. 8.1.5.2.2 CBRNResponder + Samsung Tablet A participant noted unexpected closing of the application and loss of data entry. A participant noted loss of text entry prior to submission when adding a picture. A user noted confusion with a pop-up window where, when a user selects undo, the validation language displayed by the application appeared to confirm the opposite action than the user was attempting to perform. 36 ------- 8.2 Data Manager Observations General observations from a data manager perspective related to oversight of data management tasks and configuring the software that was exercised are described in the sections below. 8.2.1 Operational Feasibility Considerations Several important operational feasibility considerations were reinforced through the AnCOR DATA Demo. Observations and recommendations are listed below: Span of Control: For data mangers actively managing personnel who are equipped with newly introduced hardware and/or software, the span of control is significantly reduced. Troubleshooting might be required to assist inexperienced personnel and/or resolve hardware issues. It is recommended that data managers be associated with no more than four teams during an active response that requires the use of data acquisition tools and GPS hardware. The span of control could be increased through routine training of participants. Just-in-time Training: Just-in-time training was provided to AnCOR DATA demo participants prior to entering the field. Participants who had never interacted with the prescribed technologies received the same level of training as those who were considered experts (through routine use). Following the demo, feedback and observations clearly determined that just-in-time training was inadequate for personnel who had never interacted with the tools and technologies that were exercised. Routine training should be provided to both emergency response and surge capacity personnel (including researchers) on a regular basis. Offline Operation: Teams were randomly chosen to operate in full offline mode (both field data collection applications exercised have offline data collection modes). Once the tablets resumed internet connectivity, results were automatically uploaded to the dashboard. All the samples collected in offline mode were successfully captured and uploaded. PPE Limitations: Overall, teams found devices and data capture forms easy to navigate using a stylus while wearing limited PPE (garden gloves to simulate nitrile gloves). Protecting Sensitive Equipment: While previous field studies have successfully demonstrated that electronic tablets (e.g., iPads) can be successfully decontaminated by encapsulating them in a water-resistant case and dunking them in a bleach solution, there are currently no water-resistant cases available for GPS systems. Furthermore, the GPS systems typically consist of multiple parts (e.g., control unit, wires, and antenna). The current recommendation would be to keep the GPS system in the field (i.e., hot zone) for the duration of the daily sampling activity (<12 hours). The GPS antenna and control unit can be contained in Ziplock bags. The bags should be sealed using a durable adhesive tape. The wire portion can remain exposed. At the conclusion of the sampling day or every 12 hours, the GPS equipment should be removed, decontaminated, and charged (or charged in the field if conditions allow). The GPS equipment should be routinely checked against known control points to ensure operability. The steps to protect GPS equipment 37 ------- were not evaluated as part of the AnCOR DATA Demo but should be evaluated as part of the AnCOR wide-area field demonstration. 8.2.2 ArcGIS Field Apps Suite EPA maintains an enterprise-level license for Esri products. Gaining access to the GeoPlatform (EPA's ArcGIS Online instance) for both the desktop-based application and mobile application was straightforward. Geoservices was responsive to inquiries and requests. Ample guidance and training materials are available to support learning how to configure various tools for use. ArcGIS Field Maps directly integrates with EPA's TOTS tool output, as well as other geospatial assets that can be shared from EPA's GeoPlatform portal (e.g., surface classification/ characterization spatial analyses, building footprints, landcover, and operational zones). Field data capture forms can be easily tailored to meet stated data collection needs that are informed by site-specific data quality objectives. While not fully exercised during the AnCOR DATA Demo, EPA Regions have demonstrated creating sophisticated data entry validation measures to support real-time validation to prevent erroneous data entry and resolution of errors while still in the field [15, 16], Several other specific lessons-learned and best practices were noted: Use black text with a white outline when adding labels to features in maps to ensure visibility on different basemaps. Configure the original sampling map to the desired position for viewing sample points, enable the appropriate layers, and save the map. Doing so creates a default view for both the Dashboard map and Field Maps application map. Only create the "Offline View Area" in the offline map after all layers are added and properly configured. Overall, the project team found the suite of Esri ArcGIS Field applications easy to configure and tailor to meet the stated needs. Changes that could be easily incorporated as additional needs were identified. This provides important flexibility to EPA where conditions in the field might change, and the data management team needs to be able to quickly respond with any necessary adjustments. Using an online platform that can easily distribute and synchronize updates facilitates staying current with and responding to changing conditions. 8.2.3 CBRNResponder Gaining access to the platform (both the desktop-based application and mobile application) was straightforward, and the support team was responsive to inquiries and requests. Ample guidance and training materials are available to quickly begin using the tool. The underlying framework for the suite of applications is robust, including user administration (i.e., pre-establishing sample collection assignments and pushing notification of assignments to users' devices), team/event management, and a built-in operational dashboard. The administrative-related features provided are powerful, including push notifications, assignment status updates, and syncing capabilities. Tremendous benefit can be added by leveraging "routine management" functions without having to "build" the capacity for each event. The overall user administration and event tracking tools are very useful. 38 ------- This platform has potential; however, there are limitations related to the current alignment of relevant data fields and reporting needs. EPA's field data capture needs related to a biological contamination sampling event would best be met if the platform added data fields important to EPA biological sampling operations and/or provided users with the ability to define custom data fields and lookup values, as well as custom report options. Another beneficial enhancement would be better integration with ArcGIS Online and/or map services or layers that could be sourced from other online platforms. The need to separately upload (potentially large) geospatial data files, rather than incorporate by way of reference to an online URL, hinders EPA's ability to leverage other important operational geospatial assets. Additionally, unlike ArcGIS Field Maps, the application cannot directly integrate an operationalized map generated through EPA's TOTS tool. For a wide-area event that could require hundreds or thousands of sample points, the ability to rely on an authoritative/single data source of geospatially-referenced sampling locations on a map is importantboth to minimize extra processing steps and to avoid data transformation errors. Furthermore, the ability to navigate to geospatially-referenced sampling locations in real-time (e.g., heading, distance) is essential to implementing probabilistic sampling designs. CBRNResponder's navigation capabilities are limited to vehicle navigation using standard mobile routing platforms (Google/Apple maps). Overall, the platform is easy to use and offers many robust features for the use cases on which design decisions were made. Enhancements related to custom data types, reporting, and better integration with other commercial GIS platforms would expand CBRNResponder's usefulness to meet EPA's AnCOR program needs. 8.2.4 Other Noted Observations Following the AnCOR DATA Demo, the project team held several additional meetings and discussed other important topics that should be addressed, but for which uncertainty exists related to implementation plans. Key issues identified include: Define whether and how EPA's Scribe tool will be used in support of the AnCOR program; Address and document internal QA procedures that will occur prior to transferring samples for analysis by the laboratory; Define data auditing procedures and document explicit rules that will govern QA activities; Determine how chain of custody forms will be generated (i.e., what tool will be used) to generate required documentation; and Address how chain of custody forms will be shared with labs. 9 CONCLUSIONS AND RECOMMENDATIONS More streamlined applications are needed for collecting, storing, analyzing, and visualizing field and laboratory data in support of decision-making. This project had four primary objectives to address this need: 39 ------- 1. Conduct a literature review and market research to identify relevant articles, reports, and other information describing research, ongoing initiatives by regional and state partners, and available commercial-off-the-shelf products that streamline and modernize field data collection activities; 2. Solicit subject-matter expert feedback from the response and research community on important functionality that field data acquisition and/or data management tools and technologies should have for responding to a wide-area incident; 3. Identify and evaluate technology to support response personnel based on recommendations provided by the response community; and 4. Conduct a field-scale demonstration to further evaluate operational aspects of selected technologies for the potential to enhance preparedness. Phase 1 of this project addressed objectives 1 and 2 and part of objective 3 where candidate tools were identified for further evaluation. From Phase 1 of this project, EPA gained a better understanding of users' needs, candidate tools, and opportunities to improve wide-area data management capabilities. Candidate software tools that were recommended for further evaluation during the AnCOR DATA demo included: Esri's Survey 123/Collector/Field Maps Suite, RadResponder (CBRNResponder), Android Team Awareness Kit (ATAK), and EPA Scribe. Phase 2 of this effort addressed research objectives 3 and 4 in which candidate tools were exercised and evaluated. Specifically, this study evaluated the current state of technologies through a demonstration event and documented observations and recommendations to enhance the USCG and EPA's ability to respond to and recover from a CBRN incident. Through this project, EPA gained invaluable experience in understanding how to apply advances in technologies and software to improve field data acquisition tasks. Important technological issues were identified to inform future planning and training efforts. Based on the expressed needs of EPA and DHS/USCG and the experiences of participants in the AnCOR DATA Demo, the project team recommended using Esri's suite of tools and ArcGIS Field Maps to support field data acquisition efforts for the AnCOR program (and potentially future biological contamination sampling events). Consistent with the findings from a related effort to assess data visualization and analysis tools, the Esri suite has the most features that meet the largest number of needs, is familiar to and accepted by target stakeholders, and is generally viewed as easy to customize and tailor to meet the specific needs of the operation. Additionally, the Esri product suite is widely adopted among the response community and has been used by the USCG in support of various missions including search and rescue, pollution response, and response to natural disasters [17], CBRNResponder, and a forthcoming BioResponder, offer many promising features. At present, however, several key requirements for EPA's AnCOR program cannot currently be met namely, alignment with required data fields/types that will be collected and integration with real- time geospatial assets. The project team recommends that EPA continue engagement attempts with FEMA to convey EPA's needs regarding biological sampling (and other agents), and 40 ------- closely monitor FEMA's progress and tool enhancements (i.e., CBRNResponder and BioResponder) to determine whether the tool could better meet EPA's needs in the future. In pursuit of an additional project goal to document a repeatable, transparent, and stable workflow to support AnCOR Wide Area Demonstration (WAD) data management needs, the project team also developed a Data Management Task/Workflow that identifies when and how various data management tools can be used across the response. Figure 30 illustrates specific tasks that have a related data management component that require input and support from the data management team. Tools available to support activities and the established workflow among the tasks and tools are illustrated, and specific tools recommended to support the AnCOR WAD are highlighted in blue. Design Sampling Plan Guidance Biological Sampling Framework Data Quality Objectives Methods Visual Sampling Plan (Probabilistic) Judgmental (Targeted) Tools MicroSAP TOTS Operationalize Sampling Plan Designate Sampling Teams Define Sampling Assignments Prepare Sampling Kits Configure TOTS Export Geospatially-referenced sample locations Define Samples Number of Samples Sample ID Nomenclature Create QR Code Labels SQUIREL Correlate with sample IDs and Team ID Capture Sampling Data Monitor Sampling Event Store and Manage Sampling Data Analyze Laboratory Data Prepare Field Survey ArcGIS Field Maps Configure Devices GPS Cellular Field Maps app Location Services On . Camera/ Video Access Generate Electronic Data Deliverables Assess Sampling Team Status ArcGIS Operational Dashboard Real-Time Data Acquisition QA * ArcGIS Operational Dashboard Acquire Database Space GeoPlatform (likely for natural disaster events) ER Cloud (likely for CBRN events) Scribe Define Data Storage Location Configure Access Privileges Import/export data ปScribe ป GeoPlatform ER Cloud Conduct Analyses GeoPlatform ArcGIS Insights ArcGIS Operational Dashboard Figure 30. AnCOR Data management tasks and supporting tools. 41 ------- Recommendations resulting from Phase 1 of this study emphasized the need to create "a well- documented workflow, articulating desirable decision-making driven features, and defining required metadata and features needed to support data workflows." Further, enabling the response community to quickly adapt to new technology implemented using proven workflows will advance preparedness levels [2], Additional considerations resulting from experiences gained through completing Phase 2 of the project generally centered on the following topics: Quality Control Procedures/Objectives, Field Data Capture Form, Training, Operational Logistics, and Managing Devices. Table 3 summarizes important observations and feedback and identifies several actionable outcomes to further advance preparedness. Based on input from the project team, actions that should be prioritized are designated accordingly. Table 3. Additional Observations and Feedback Topic Observations/Feedback Quality Control Procedures /Objectives Closely integrate sampling and data management plans to ensure the right data are collected to inform decisions. Relate/define appropriate validation and QC checks that would be required based on identified data needs. Compare sample matrix to sample method (via QR code scan); prevent data entry unless appropriate match. Check acceptable proximity to pre-established sampling point. Automate as many checks as possible through smart forms to prevent the entry of erroneous data from the start. Identify real-time checks (via a checklist) for data management team monitors to assess during the event and define the process for communicating any issues that might arise. Consider creating specialized views/queries that would support quickly identifying questionable entries. Field Data Capture Form Optimize forms to facilitate completion in less than one minute. Minimize free-form text entries. Maximize the use of "auto-collected" data to require fewer entries by a user (e.g., individual/team performing entry, day/time of entry, location of entry, sample status following entry). Incorporate visual cues on the digital map to illustrate the status of sample points. Training Clearly define specific objectives related to sampling event and data collection to ensure participants understand what, why, and how for each task they are asked to perform. Provide routine training to both emergency response personnel and surge capacity personnel (including researchers) for both data capture software and technologies that would be used during a response. Offer interactive, step-by-step training (either in person dry-runs or via PowerPoint or MS Teams). Train participants in advance on both the equipment (technology) and the software that they will use while in the field. 42 ------- Table 3. Additional Observations and Feedback Topic Observations/Feedback Training (Continued) Provide a classroom-based exercise to demonstrate tasks, discuss common ""gotchas." and answer questions well in advance of the exercise. Strategically pair teams to ensure whoever is charged with collecting data has the appropriate skills and training to successfully accomplish the tasks. Distribute laminated instruction cards and electronic versions that are pre- loaded on devices that provide quick tips and troubleshooting solutions to sample teams. Identify potential issues and corresponding course of action (e.g., if device overheats, if battery capacity dips below 10%). Operational Logistics Optimize sampling routes to ensure that distances in-between samples are reasonable and make sure sampling routes avoid non-access areas or work zones. Plan sampling routes to avoid spreading contamination to otherwise clean areas. Prepare QR code labels (for samples or team personnel identification) using high quality printers and labels to support optimal recognition by barcode readers/device cameras. Regarding extending battery life, determine whether samplers can operate in an offline mode for data submission where checkpoints are established (e.g., after completing five samples) to synchronize data or if they should carry battery backups/chargers. Associate data managers with no more than four teams during an active response that requires the use of data acquisition tools and GPS hardware. Leverage real-time location tracking among teams where teams near one another can provide troubleshooting support or assist with resolving immediately known collection errors/conflicts/issues from another team (as long as contamination spreading is avoided). Managing Devices Develop and execute a checklist for configuring and testing all hardware and devices that will be used in advance of the exercise. Implement all operating system upgrades, application updates, device settings (e.g., cellular, WiFi, Bluetooth, application access to camera, location services) to ensure optimal performance and configurations to support the associated data capture form features. Provide extra battery packs (adequately protected from contamination) to extend the capacity of a device's onboard batteries. Consider distributing WiFi source/extenders in the field to support device connectivity. Place and retain a GPS system in the field (i.e., hot zone) for the duration of the daily sampling activity (<12 hours). Consider distributing alcohol wipes to clean screens when in the field. Provide device hand grips to improve usability in the field. Consider having replacement devices on-hand and ready to activate should devices in the field begin to fail (e.g., battery needs recharging, device needs to cool down). Issue and attach a stylus for data entry. Design and implement measures to protect all sensitive equipment that might require decontamination. 43 ------- Several additional issues that were identified that require more information and/or research include: Address and document internal QA procedures that will occur prior to transferring samples for analysis by the laboratory; Define data auditing procedures and document explicit rules that will govern QA activities; Determine how chain of custody forms will be generated (i.e., what tool will be used) to generate required documentation; and Address how chain of custody forms will be shared with labs. Evaluate the impacts of weather (e.g., cold/hot temperatures, precipitation) on the usability and performance of tablets and GPS units. Through this effort, candidate tools were exercised and evaluated to assess the current state of technologies to enhance the USCG and EPA's ability to respond to and recover from a CBRN incident. 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