Challenge
Industrial sites needed earlier warning of unsafe physiological and environmental conditions. The wearable had to analyse time-critical signals on constrained hardware, while central teams still needed history, alerts, and reporting.
Solution
We integrated ECG, respiration, temperature, and movement sensors with on-device sensor fusion, ran inference with TensorFlow Lite, and built digital-twin models with cloud services for alerts, reporting, and risk prediction.
Results
- Working multi-sensor wearable prototype
- Earlier warning may reduce incidents and downtime
- Continuous evidence supports reporting and prediction
- Digital twins plus cloud monitoring and alerts
Technology
TensorFlow Lite · Edge AI · Digital Twin · Cloud
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