
Connecting Cameras to Edge AI for Resident Safety
Stream video from cameras to a local AI box for illegal intrusion and property damage detection.

Positioning solutions often have high deployment costs, poor device battery life, and difficult maintenance. Discontinuous indoor and outdoor tracking requires different devices, posing significant challenges to security management and operational efficiency.
Using low-power modules combined with Bluetooth, Wi-Fi, and GPS technologies, we reduce maintenance costs and eliminate indoor/outdoor tracking blind spots.

When a dangerous situation occurs on campus, the lack of a unified and reliable reporting channel makes it difficult to locate the incident and respond promptly, leading to delayed emergency response and endangering personnel and property.
Campus members can carry a safety badge that allows for one-click, low-latency emergency reporting over a dedicated channel.

Traditional manual video surveillance is inefficient, prone to missing events, and has high labor costs. It struggles to provide 24/7 real-time detection and alerts for anomalies like intrusions, falls, or fires, resulting in slow emergency response.
Edge AI models analyze video streams for behavior recognition, detecting intrusions, loitering, falls, or fires in milliseconds and automatically triggering security system integrations.