SBIR/STTR Research Award
Resilient SP-BSC Sensor Networks for AI-Driven Predictive Maintenance
Award amount
$74,900Program and phase
SBIR · Phase IAward year
2025Award details
- Awarding agency
- Department of Defense
- Branch
- Navy
- Recipient company
- Jeeva Acquisition Company Inc
- Proposal award date
- 2025-07-08
- Contract end date
- 2025-11-06
- UEI
- WD86JC4HN1L8
- Solicitation number
- 24.4
- Topic code
- N244-P02
Research abstract
WaveWorks Technologies is developing Sawtooth, an AI-driven, wireless sensor that monitors equipment to detect potential issues early, providing real-time analytics and predictive maintenance through an intuitive app. On this SBIR effort, WaveWorks will pursue efforts to develop a Standard Protocol Backscatter Communication (SP-BSC) enabled hardware prototype, create a comprehensive dashboard that displays real-time results from the AI model, and further train and refine the model. The adoption of backscatter communication technology can fundamentally revolutionize how the DON communicates, monitors, and operates in various capacities. It’s unique properties address battery life, one of the most critical hurdles to widespread adoption of wireless sensing in vital infrastructure sensor monitoring applications and will also provide a first demonstration of a counter-jamming ability which could be incorporated into future iterations of this sensing platform for added robustness. With this unique blend of power efficiency, interoperability, and security, Sawtooth offers an essential capability for predicting failures, optimizing performance, and ultimately ensuring that Navy assets can be reliably and safely returned to the field as quickly as possible. Addressing these challenges is critical to meet Navy needs regarding sustainment and obsolescence.
Technology keywords
Not reported
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