Most people assume object tracking for autonomous flight is very complex, but it doesn’t have to be that way. All you need is a different way of looking at the problem. We built this project to see if ...

What if a device could see the world the same way humans do, seeing objects, recognizing them, and understanding what they are in real time? Just like our eyes capture visuals and our brain instantly ...

City people have been employing spikes, nets, fake owls, and frantic balcony claps to wage an unending battle against pigeons for years. However, an AI-powered automated pigeon defensive system with a ...

Build practical Edge AI applications with Raspberry Pi, from basic concepts to object detection and robotics, using the AI HAT+ and Camera Module 3. Edge AI is bringing data processing directly onto ...

YOLO object detection service for MQTT camera events — subscribes to motion event images from camera bridges, runs inference via YOLO26, and publishes detection results back to MQTT. Designed to work ...

Test and compare multiple YOLO versions (YOLO8, YOLO9, YOLO10, YOLO11, YOLO12, YOLO26) with support for critical object marking, multi-GPU acceleration, and batch processing across diverse hardware ...

What if your Raspberry Pi could do more than just compute, it could see the world like you do? Imagine a tiny device that doesn’t just identify a dog in a photo but tells you whether it’s lounging on ...

Imagine a vehicle cruising at 54 kilometres per hour, roughly the speed of an object moving 0.5 metres per frame at 30 frames per second (0.5×30×3.6=54 km/hr). Mounted on the vehicle’s roof is a ...

こんにちは、Google AI 学生アンバサダーとして活動している大学2年生のKAです。今回は、Raspberry Pi で、本来の目的のYOLOを用いた物体検出をカメラからのリアルタイム映像に対して実行します。