SBIR/STTR Research Award

AI Cross-validation of IoT systems to increase Accuracy, Trust, and Mission Readiness

Award identifier 89049ef3d3c883d6a0ffaaa450aa8b2f31689d4c9cf0814a1b8f29e986956d0dAwarding agency Department of Defense · Air Force

Award amount

$74,929

Program and phase

SBIR · Phase I

Award year

2023

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
THERMOAI INC
Proposal award date
2022-11-05
Contract end date
2023-02-04
UEI
LNFRKV1LFNM5
Solicitation number
X22.4
Topic code
X224-OCSO1

Research abstract

Leveraging advanced cyber physical system (CPS) and clustering machine learning can crosscheck the signal in Air Force Internet of Things (IoT) systems increasing accuracy, trust, and mission readiness. Inaccurate signals cause false alarms which dimmish trust in IoT systems and can cause service members to ignore warning systems. Cross-validation of alerts can substantially increase the accuracy and trust in critical Air Force IoT systems - like instruction detection systems. During Phase I, we will work with AFRL researcher Anthony Macera in his IoT living lab in Rome Labs to identify the most mission-critical uses to focus on first.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

5 SBIR/STTR records share this UEI (2020–2024). Reported award amounts total $1,672,378. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation

Agency intelligence

Department of Defense

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