2_use_case_name: Operational satellite product quality monitoring AI-ready training data
3_agency: Department of Commerce
3_abr: DOC
4_bureau: NOAA - National Oceanic and Atmospheric Administration
8_topic_area: Other
8_question_type: Satellite Data and Product Utility
10_commercial_ai: None of the above.
11_purpose_benefits: NOAA NDE and NESDIS Common Cloud Framework (NCCF) are current and future NOAA satellite product generation environments. There are hundreds of products based on a variety of national/international satellites (US, Europe and Japan) that are generated in near real time. The anomaly detections of the satellite product quality are still manpower intensive and in a traditional way. Nowadays, with the AI technology getting mature, the AI use case can be extended to this area of anomaly detection. In the traditional way, the maintenance programmers eyeball the product maps with 24/7 support which is stressful. On the other hand, AI has the strong capability of pattern recognition with high accuracy. The AI-based technique will relieve manpower and automate the alert system.
12_outputs: Detection/Identification of the satellite product anomalies, e.g. the bounding boxes locate the pre-defined error types. 
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 11/6/2022
19_date_acq_dev_began: 3/29/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 1332KP21DNEEB0011
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: No
33_agency_data: A variety of operational satellite products
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
35_demo_features: Other
35_question_type: Does not use any demographic variables.
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: No
42_dev_tools_wait: More than 12 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Use of existing data platforms: This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.
50_internal_review: Limited documentation for review: Some information regarding the model’s performance on specific benchmarks are available or have been shared with specific stakeholders within the agency.
51_extension_request: No – Agency did not request an extension for this use case.
52_impact_assessment: Planned or in-progress.
53_real_world_testing: No testing: No testing of the model to simulate performance in an operational environment has been conducted thus far.
54_key_risks: Lack of funding for Phase II development and transition from research to operations. 
55_independent_eval: Yes – by an agency AI oversight board not directly involved in the system’s development
56_monitor_postdeploy: No monitoring protocols have been established: Necessary infrastructure needed to perform monitoring of AI systems in production is not available and/or a plan to monitor models has not yet been established.
57_autonomous_impact: No - Some individual decisions or actions require direct human oversight.
59_ai_notice: Email
61_adverse_impact: No
62_disparity_mitigation: Test, assess and feedback collection
63_stakeholder_consult: Direct user testing
65_appeal_process: Yes
67_opt_out: Other
67_question_type: No – This AI use case is not subject to the opt-out requirement because the AI functionality is solely used for the prevention, detection, and investigation of satellite data product quality.