We are seeking experienced algorithm developers with expertise in computer vision and radar signal processing to help develop a contactless health monitoring system for correctional facilities. Our system uses radar and video sensors to monitor inmate vital signs and detect distress, alerting officers when intervention may be needed.
This project involves developing and refining algorithms that can extract health and behavioral signals from radar and video data collected during our prototype and pilot deployments.
Timeline
The project timeline is 3 months from prototype to pilot deployment, with algorithm development running in parallel with hardware testing.
Scope of Work
Key responsibilities include
• Develop and refine computer vision algorithms for monitoring movement, posture, and potential distress indicators. • Develop radar-based algorithms capable of extracting vital sign signals such as respiration and heart rate. • Work with multi-sensor data (radar + video) to improve detection accuracy and reduce false alerts. • Process and analyze real-world data collected from our prototype deployments. • Fine-tune algorithms to improve accuracy, robustness, and reliability in a correctional facility environment. • Assist with sensor fusion techniques combining radar and video signals. • Support integration of algorithms into a centralized monitoring dashboard used by facility staff. • Optimize models for real-time processing and alert generation.
Data & Development
During the prototype phase, our hardware system will collect radar and video datasets from controlled testing environments. These datasets will be provided to algorithm developers to train, validate, and refine the detection models.
The goal is to produce algorithms capable of reliably detecting: • Respiratory patterns • Heart rate signals (via radar) • Abnormal movement or inactivity • Potential distress events
Requirements
Ideal candidates will have
• Strong experience in computer vision development • Experience with radar signal processing or RF sensing • Experience working with sensor fusion systems • Background in machine learning, deep learning, or signal processing • Proficiency with Python, PyTorch, TensorFlow, OpenCV, or similar frameworks • Experience developing real-time or near-real-time monitoring algorithms • Ability to work with noisy real-world datasets
Preferred Experience • Healthcare or medical monitoring systems • Contactless vital sign monitoring • Radar technologies such as FMCW radar or mmWave sensors • Human activity recognition • Edge AI or embedded ML
Future Work
Future phases of the project will involve developing advanced medical algorithms, including predictive models for detecting and forecasting distress events and other health risks based on patterns identified in radar and video data. Developers involved in the initial phase may have the opportunity to continue working on these clinical and predictive analytics models as the system evolves.
Project Goals 1. Develop algorithms capable of extracting vital signs from radar signals 2. Build computer vision models for movement and distress detection 3. Combine radar and video data for robust multi-sensor detection 4. Deliver algorithms suitable for pilot deployment in a correctional facility
Skills we are looking for
- Computer Vision Development
- Radar Signal Processing
- RF Sensing
- Python
- PyTorch
- TensorFlow
- OpenCV
- Machine Learning
- Deep Learning
Loading the application form…