GreatNorthCollective/greatnorth-us-federal-ai-inventory-2024 huggingface dataset:
2_use_case_name: Multi-media Insight Tool
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: The system enhances CBP's ability to monitor and analyze surveillance footage from existing USBP camera technology, enabling real-time detection of anomalies, and tracking of Items of interest within the video frame. It improves situational awareness, streamlines the identification process, and supports faster, more accurate decision-making, ultimately enhancing security and operational efficiency.
12_outputs: Outputs include real-time alerts on activities that should be watched, visual annotation to identify items of interest.

16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 3/1/2024
2_use_case_name: Position Description Generation and Evaluation
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Faster and more accurate creation of PDs, reducing admin burden on field and HQs as well as HR specialists, allowing agency to get more done with less staff.
12_outputs: Creation of accurate position descriptions, verified by Human Resources Specialists
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 11/8/2024
2_use_case_name: Source Code Development Tool
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: This capability will enable end users to develop software faster and more efficiently through the use of a generative artificial intelligence coding assistant.  

12_outputs: This capability will provide functional software code for end users.

16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 11/1/2024
2_use_case_name: AI Curated Synthetic Data
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: The availability of rare event/outlier data or labeled data that can be used to train and automate detection is severely limited. The technology enhances available libraries of true positives and normal scans from CBP Non-Intrusive Inspection (NII) systems and supports development of Automated Threat Recognition (ATR) algorithms designed to quickly identify items of interest.
12_outputs: Through the technology the end user will have access to enhance existing, deployed algorithms to increase detection performance.
16_dev_stage: Retired
18_date_initiated: 10/1/2022
21_date_retired: 10/1/2024
2_use_case_name: Integrated Defense and Security Solutions (IDSS)
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Law & Justice
10_commercial_ai: None of the above.
11_purpose_benefits: The systems improves the screening efficiency and accuracy of contraband detection in international express consignment and mail inspection.

12_outputs: The system provides a segmented image, highlighting anamolies for further inspection by CBP personnel.
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 1/1/2019
2_use_case_name: Advance RPM Maintenance Operating Reporter (ARMOR)
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: ARMOR will shorten time to service/repair/maintenance of radiation portal monitors by two weeks. ARMOR will allow better distribution of resources (travel, spare parts, etc.) and expected cost decrease could be 25-50%. Through decreased outage time, and prediction of equipment degradation, ARMOR will increase radiological/nuclear (R/N) security on US borders.
12_outputs: The system will provide a listing of malfunctioning RPMs categorized by issue severity and predicted date of failure. The outputs will be used to create service tickets.
16_dev_stage: Acquisition and/or Development
17_impact_type: Safety-Impacting
18_date_initiated: 10/1/2021
19_date_acq_dev_began: 10/1/2021
2_use_case_name: RAPTOR (Rapid Tactical Operations Reconnaissance)
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Law & Justice
10_commercial_ai: None of the above.
11_purpose_benefits: RAPTOR will significantly increase domain awareness and the agency’s ability to engage in intelligence-driven operations.  The AI capability acts as a force multiplier and saves personnel from analyzing video feed from a stationary camera and manually noting all boat identifiers, improving their ability to respond quickly to potential threats and gather critical intelligence for law enforcement and border control operations.
12_outputs: Text transcription of vessel registration/documentation data and photographs of the vessel.
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 4/1/2023
2_use_case_name: Vessel Detection
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Law & Justice
10_commercial_ai: None of the above.
11_purpose_benefits: Current surveillance technology does not have machine assisted classification of targets on screen, making it harder for human operators to decipher legitimate from illegitimate traffic in times of high volumes of legitimate traffic.  Project intends to support human operator identification and classification of potential illicit vessels.  Benefits would be more efficient detection and resolution of IOIs, especially during times of high-volume traffic.        
12_outputs: Alerts and tracks of detected Items of Interest (IOI)s to human operator workstations.  
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 10/1/2021
2_use_case_name: AI for Autonomous Situational Awareness
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Law & Justice
10_commercial_ai: None of the above.
11_purpose_benefits: The AI for autonomous situational awareness system is intended to use IoT sensor kits to covertly detect and track illicit cross-border traffic in remote locations. The system will leverage a motion image/video system enhanced with Artificial Intelligence that is capable of vehicle detection and direction determination, to allow for more active monitoring of remote camera feeds that prompt operators to review the items of interest once detected.  This will reduce the overall operator burden of camera monitoring and allow users to accomplish other tasks or system management. 


12_outputs: Detections of items of interest being displayed with bounding boxes around the IOI in the image frame and an initial determination of "human, animal, vehicle""
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 10/1/2020
2_use_case_name: RVSS Legacy Overhauled System Project
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: Video Computer Aided Detection (VCAD) (also known as Matroid AI) is software that enables CBP end users to create and share vision detectors. VCAD detectors are trained computer vision models that recognize objects, people, and events in any image or video stream. Once a detector is trained, it can monitor streaming video in real time, or efficiently search through pre-recorded video data or images to identify objects, people, and events of interest. Users can view detection information via a variety of reports and alert notifications to process and identify important events and trends. Detection data is also available through VCAD's powerful developer Application Programming Interface (API) and language specific clients, so CBP applications can be integrated with the power of computer vision.
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
18_date_initiated: 10/1/2019
19_date_acq_dev_began: 10/1/2020
20_date_implemented: 6/1/2023
21_date_retired: N/A -Consolidated into another use case.
2_use_case_name: Agent Portable Surveillance
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: The agent portable surveillance system is a backpack mobile unit meant for single agent deployments. The system identifies border activities of interest by using AI/ML to analyze data from Electro-Optical/Infra-Red cameras and radar. When an activity is detected, the system sends the information to agents through the Team Awareness Kit (TAK). Detections are shared with CBP TAK users to enhance efficiency and agent/officer safety.
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
21_date_retired: 10/1/2024
2_use_case_name: Open-Source News Aggregation
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: The platform enables users to make better decisions faster by identifying and forecasting emerging events on a global scale to mitigate risk, recognize threats, greatly enhance indications and warnings, and provide predictive intelligence capabilities. The AI/ML models enable rapid access to automated intelligence assessments by fusing, processing, exploiting and analyzing open sources of data (including news, social media, economic indicators, governance indicators, travel warnings, weather and other sources). This system is an immediate and substantial force multiplier that shifts the traditional approach of monitoring and assessing the operational environment to focus on the forecast of the future geopolitical, socio, and economic environment.
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
21_date_retired: 10/1/2024
2_use_case_name: Autonomous Aerostat
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: Aerostat capability that uses three tethers instead of the traditional single tether, coupled with advanced weather sensors, analytic capabilities, and powerful winches. The AI/ML model is used to detect the need to launch and land based on weather. It also leverages AI and robotics to autonomously launch and recover the aerostat during inclement weather events without the need for on-site staffing, allowing the aerostat to operate autonomously, saving time and manpower. 
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
18_date_initiated: 10/1/2019
19_date_acq_dev_began: 10/1/2018
21_date_retired: 10/1/2024
2_use_case_name: Geospatial Imagery Utilizing Annotation
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: Leverages a commercial constellation of Synthetic Aperture Radar (SAR) satellites with readily available data, capable of imaging any location on Earth, day, and night, regardless of cloud cover. Utilizes AI, including machine vision, object, detection, object recognition, and annotation to detect airframes, military vehicles, and marine vessels, as well as built-in change detection capabilities for disaster response missions.
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
18_date_initiated: 10/1/2021
19_date_acq_dev_began: 1/1/2022
21_date_retired: 10/1/2024
2_use_case_name: Use of technology to identify proof of life
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: Mobile applications rely on product for liveness detection to avoid use of spoofed or fraudulent images by bad actors. Being able to accept submitted data with confidence that the submitting individual is who and where they claim to be is critical to the functionality of the app within the agency environment.
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
18_date_initiated: 10/1/2020
19_date_acq_dev_began: 10/1/2020
20_date_implemented: 10/1/2023
21_date_retired: N/A -Consolidated into another use case.
2_use_case_name: Integrated Digital Environment
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: The Integrated Digital Environment provides managers with a better understanding of end user workflows, most and least used applications, and opportunities for improvement. The AI/ML model applies to end user activity data (e.g., use of applications, flow between applications) to help CBP identify opportunities for more efficient or effective configuration of interfaces, use of resources, or development and deployment of CBP’s applications. It tailors analytics and insight generation to allow metrics gathering, usage recording/observation, dashboarding, and workflow experimentations/suggestions to support analysts utilizing the entire suite of agency and open-source data systems. It also customizes existing capabilities to allow the exact automations needed for agency applications and systems, creating an integrated digital environment for greater connectivity and security between applications, and better ability for CBP administrators to manage and optimize use of applications by end users. 
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
18_date_initiated: 10/1/2021
19_date_acq_dev_began: 4/1/2022
21_date_retired: 10/1/2024
2_use_case_name: Data and Entity Resolution
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Entity resolution for ES multiple independent valid requirements that may be similar or able to be consolidated.
12_outputs: "Uses machine learning and human input to leverage all data attributes to resolve entities, rather than traditional brute force rules
Automates process of unifying data sources and resolving entities at enterprise speed"
16_dev_stage: Retired
18_date_initiated: 10/1/2021
19_date_acq_dev_began: 4/1/2022
20_date_implemented: 10/1/2019
21_date_retired: 11/30/2024
2_use_case_name: Port of Entry Risk Assessments
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: CBP utilizes AI to develop, inform, and augment risk assessment processes that evaluate trade and travel data in real-time.  AI methods are applied to CBP data holdings, and the results are used to inform decision making.  These tools are continuously evaluated to ensure accuracy and precision, and support CBP’s core mission as part of the layered risk assessment strategy. 
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
21_date_retired: 10/1/2024
2_use_case_name: Traveler Verification Service (TVS)
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: The Traveler Verification Service (TVS) provides CBP a biometric entry/exit system to record arrivals and departures to and from the United States. CBP uses TVS as its backend matching service for all biometric entry and exit operations that use Facial Comparison. CBP creates localized photo "galleries" from images captured during previous entry inspections, photographs from U.S. passports and U.S. visas, and photographs from other DHS encounters. The images are converted into templates and the actual photograph is discarded. The templates are securely stored, and are what make up the TVS gallery. The templates are then used by the Facial Comparison system to verify a traveler's identity when they arrive or depart the U.S. When the traveler presents him or herself for entry, or for exit, the traveler will encounter a camera connected to TVS. This camera matches live images with the existing photo templates from passenger travel documents. Once the camera captures a quality image and the system successfully matches it with historical photo templates of all travelers from the gallery associated with that particular manifest, the traveler proceeds to inspection for admissibility by a CBP Officer, or exits the United States.
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
21_date_retired: N/A - Deconsolidation of several use cases
2_use_case_name: I4 Viewer Matroid Image Analysis
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
10_commercial_ai: None of the above.
11_purpose_benefits: Matroid is a software that enables CBP end users to create and share vision detectors. Matroid detectors are trained computer vision models that recognize objects, people, and events in any image and in video streams. Once a detector is trained, it can monitor streaming video in real time, or efficiently search through pre-recorded video data or images to identify objects, people, and events of interest. Users can view detection information via a variety of reports and alert notifications to process and identify important events and trends. Detection data is also available through Matroid’s powerful developer Application Programming Interface and language-specific clients, so CBP applications can be integrated with the power of computer vision. 
12_outputs: This use case is inactive. Please see the "intended purpose and expected benefits" for a full description of this use case.

16_dev_stage: Retired
21_date_retired: 10/1/2024
2_use_case_name: Autonomous Maritime Awareness
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Law & Justice
10_commercial_ai: None of the above.
11_purpose_benefits: The technology is equipped to operate in low temperatures, ice, and snow enable real-time surveillance for continuous monitoring of maritime activity, even in harsh conditions, while providing enhanced detection capabilities to identify threats such as unauthorized vessels or smuggling activities in difficult-to-navigate regions.

12_outputs: The system provides real-time notifications of suspicious activities, continuous tracking data on vessel locations and movements, and detailed threat assessments to support enforcement actions in cold-weather environments.

16_dev_stage: Retired
18_date_initiated: 10/1/2020
19_date_acq_dev_began: 10/1/2020
20_date_implemented: 1/30/2024
21_date_retired: 6/21/2024
2_use_case_name: Advanced Trade Analytics Platform (ATAP)
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: To create efficiencies and unlock key insights in CBP's trade mission execution through the application of data analytics, machine learning, and AI.
12_outputs: Model output is provided in dashboards and other visualization mechansims for operator assessment and action determination.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 7/1/2019
19_date_acq_dev_began: 12/1/2019
20_date_implemented: 3/7/2022
22_dev_method: Developed with contracting resources.
23_contract_piids: BPA: 70B06C20A00000036  Call Order 1: 70B06C20F00000895 Call Order 2: 70B06C21F00000842 Call Order 3: 70B06C22F00000700 Call Order 4: 70B06C23F00000819 Call Order 5: 70B06C24F00000450
24_hisp_support: No
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: ATAP relies on CBP source system information from CBP's ACE, ATS, and SEACATS systems, including import/export filing information, compliance reviews, targeting, seizure, and fine/penalty information.
34_data_docs: Documentation has been partially completed: Some documentation exists (detailing the composition and any statistical bias or measurement skew for training and evaluation purposes), but documentation took place within this use case’s development.
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: Yes
41_system_name: ATAP
42_dev_tools_wait: 6-12 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Re-use production level code from a different use-case: This use case re-uses production level code and/or internally developed code libraries for model development from existing AI systems or repositories inside the agency.
50_internal_review: Documentation has been developed: Complete documentation detailing model performance across a range of benchmarks, architecture, relevant features and information regarding the appropriate use of the model for predictive tasks has been created.
2_use_case_name: CBP Employee Experience
3_agency: Department of Homeland Security
3_abr: DHS
4_bureau: CBP
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: CBP Employee Experience is intended to ingest, interpret, and operationalize employee experience data originating from survey results and operational data to deliver real time insights related to the experience of USBP recruits, applicants, and employees. These metrics inform HRM leadership of opportunities for process improvement in order to meet congressionally mandated hiring targets and retain a qualified workforce.
12_outputs: Real time insights related to the experience of USBP recruits, applicants, and employees.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 12/1/2023
19_date_acq_dev_began: 5/1/2022
20_date_implemented: 10/1/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 024-000005282
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: User input is captured in feedback surveys.
34_data_docs: Documentation is complete: Documentation exists regarding the maintenance, composition, quality, and intended use of the training and evaluation data, as well as any statistical bias across model features and protected groups. 
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: MASS
42_dev_tools_wait: 6-12 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
50_internal_review: Documentation has been developed: Complete documentation detailing model performance across a range of benchmarks, architecture, relevant features and information regarding the appropriate use of the model for predictive tasks has been created.