AI-Powered Embedded Systems: GeoAI Behavioural Pattern Recognition for Smart City Lost-Pet Recovery
Introduction: The Challenge of Contextual Tracking
Pet owners demand reliable lost-pet detection and health anomaly alerts without sacrificing battery life or increasing cost. Traditional geofencing produces too many false alerts, as crucial behavioural context is missing. This required a deep investment in IoT product engineering to deliver a high-value, battery-efficient smart infrastructure solution for consumers.
Solution Overview: Edge AI Embedded Systems for Behaviour Classification
We designed the Felica Pet Tracker as a hybrid BLE + GNSS collar with an IMU. Its core is an AI-powered embedded system that runs a tiny ML inference engine (TensorFlow Lite Micro / Edge Impulse) onboard. This Edge AI embedded system classifies behaviour (resting, roaming, erratic escape behaviour), increasing GNSS duty-cycle only when an enriched "escape" event is detected. This strategy improves detection sensitivity while dramatically reducing useless GNSS wakes.
Technical Implementation: GeoAI, Embedded AI India & Predictive Maintenance AI IoT
The embedded systems development focused on an IMU that sleeps with FIFO gated, waking the MCU only on threshold crossing. ML models, trained on instrumented canine/cat datasets, were compressed via quantisation to fit 64-128 KB RAM devices—a hallmark of Embedded AI India expertise. Server-side, our models fuse historical tracks, owner-provided "known-safe areas," and social-collar sightings to produce a ranked recovery route using GeoAI. This intelligence enables Predictive maintenance AI IoT by providing alerts based on behavioural anomalies, not just simple location.
Results & Impact: Smart City Solutions and AI Engineering
Pilots showed a reduction of false "missing" notifications by ~72% versus geo-fence only, and median time-to-recover improved by ~45% when using the ranked recovery routes. This AI engineering solution confirms EurthTech's ability to successfully deliver complex, consumer-facing AI} products. The underlying technology provides a model for any smart city solutions provider looking to integrate pervasive, low-power geospatial engineering services.
Scalability & Security: Typical battery life is 2-6 weeks for frequent users, with the potential for 3-6 months for low-activity pets. Provisioning uses NFC to write secure keys to the secure element. This device serves as a micro-asset in a future Digital twin smart city, proving that highly optimized IoT technology can be widely deployed for public safety and premium services.