Data Analytics and Algorithm Development for Remote Monitoring

The contract seeks the development of predictive algorithms designed to enable early detection of respiratory compromise through the analysis of multimodal sensor data, with a strong emphasis on reducing false alarms and leveraging advanced time-series analysis techniques. The work is focused on enhancing remote monitoring capabilities by creating robust machine learning models that can identify subtle, early indicators of respiratory deterioration before clinical symptoms become apparent, thereby improving patient outcomes in care settings reliant on continuous physiological surveillance. This is a subcontract under the Department of Veterans Affairs, categorized under NAICS code 511210, which pertains to software publishing and data analytics services. Responses are due by May 26, 2026, and the opportunity was posted on May 11, 2026. The performance location is not specified, and no set-aside provisions are indicated. The project aims to support remote patient monitoring systems used within VA healthcare infrastructure, requiring technical expertise in sensor fusion, algorithmic optimization, and real-time data processing to deliver accurate, reliable, and clinically actionable insights.