AI-enabled cameras are widely used for object detection, surveillance, and advanced driver assistance systems, but most existing solutions are bulky, power-intensive, and unsuitable for compact deployments. Applications such as drones, wearables, wildlife monitoring, and small robots demand devices that are not only intelligent, but also small, lightweight, and energy-efficient—a combination that conventional AI cameras struggle to deliver.
This project demonstrates a tiny AI-based wireless streaming camera built using IndusBoard Coin V2 and an OV2640 camera module. Instead of running heavy AI models on the device itself, the system streams live video over Wi-Fi to a browser, where TensorFlow.js with the COCO-SSD model performs real-time object detection. This approach enables advanced visual intelligence while keeping the hardware footprint minimal.
Key Features
- Coin-sized (≈3.3 cm) AI camera platform
- Live wireless video streaming over Wi-Fi
- Real-time object detection using TensorFlow.js and COCO-SSD
- Detection of people, animals, and vehicles in a web browser
- OV2640 camera with JPEG compression
- 4MB PSRAM on IndusBoard Coin for smooth frame buffering
- Browser-based AI processing—no heavy on-device ML computation
- Arduino IDE–based development for ease of programming
Applications
- Drones for obstacle detection and object tracking
- Wearables such as smart glasses or badges
- Compact home security and surveillance systems
- Wildlife monitoring in concealed or space-constrained locations
- Robotics applications in confined environments
- Portable and experimental AI vision prototypes
This project highlights how real-time AI vision can be achieved using minimal hardware by intelligently offloading machine learning to the browser. By combining the compact form factor of IndusBoard Coin with wireless streaming and TensorFlow.js–based inference, the design lays the groundwork for some of the smallest practical AI cameras, opening new possibilities for embedded vision in space- and power-constrained environments.