Falls among elderly residents occur frequently despite strict facility protocols and environmental safeguards.

Falls cause additional complications in elderly demographics, making prevention and rapid response crucial.

Speed of detection and staff response is vital for mitigating serious injuries and improving outcomes.

Accurate, latency-free analysis of multiple video feeds for instant fall detection alerts.

Handle continuous streams from up to four network cameras without frame drops.

Display video feeds while equipped with communication protocols for staff alerts.

The system processes convolutional neural networks and pose-estimation models to deliver high-throughput, low-latency fall detection.

Network-independent digital I/O ensures immediate staff notification through connected TCP devices and alarm systems.

Institutions Deployed

Successfully implemented across Japan with expansion plans to hospitals, factories, and public buildings.

Dramatically reduced response times to falls, allowing immediate staff assistance and better resident outcomes.

Automated monitoring frees staff for complex care tasks without compromising resident safety.

Transferable benefits to factories, hospitals, and post-operative patient monitoring environments.

The AI-Behavia FD system demonstrates how intelligent technology can save lives by bridging the critical gap between fall occurrence and emergency response.

AI identifies falls instantly

Staff alerted immediately

Lives saved through technology