DIY Dog-Seeking IoT Edge Computing Platform

This project aimed to create a user-installable IoT platform to assist families in reuniting with lost pets. The platform consists of a high-definition camera housed in a waterproof enclosure and utilizes edge computing principles to analyze data locally before sending it to the cloud.

Motion detection: The camera system detects movement and uploads potentially relevant multimedia to the cloud for further analysis.

Cloud-based image processing: Dove IO's image processing technology automatically identifies objects and scenes in the uploaded media, generating various tags.

User-friendly platform: The Dove IO platform allows users to search and interact with these identification tags.

Customizable notifications: Users can configure the system to send SMS or email alerts upon detecting a dog in the scene.

Secure data access: The platform provides secure credential login for users to view and search historical data captured by the system.

Simple hardware design: The platform utilizes a Raspberry Pi running Debian Linux and a Python script to control the camera system and analyze video frames using OpenCV and scikit-image libraries.

This prototype demonstrates the potential of DIY IoT solutions for addressing real-world problems. By offering a cost-effective and user-installable solution, it empowers families with a potentially lifesaving tool to help locate their lost pets.

Future iterations could focus on:

Improving object detection accuracy: Further refinement of the image processing algorithms for enhanced pet identification.

Facial recognition integration: Implementing facial recognition for potentially identifying specific lost pets.

Mobile app development: Creating a mobile app for easier and on-the-go access to the platform and notifications.