v0.1.0-beta: Initial Beta Release of the vespCV Asian Hornet Detection System - Empowering Biodiversity Through Computer Vision

Overview

This beta release of the vespCV project introduces the core functionality of the automated Asian hornet detection system. The application leverages computer vision technology to assist beekeepers, volunteers, and researchers in monitoring and managing hornet populations effectively, contributing to the preservation of biodiversity.

Key Features

• Automated Detection: Utilizes the YOLOv11s model for real-time detection of Asian hornets.
• Image Capture: Captures images using the Raspberry Pi camera and processes them for detection.
• Email Notifications: Sends alerts via email when an Asian hornet is detected, configurable through user credentials.
• Logging: Comprehensive logging of system activity and detection events for troubleshooting and analysis.
• User-Friendly Interface: A graphical user interface (GUI) for easy interaction with the detection system.

Biodiversity Impact

The vespCV project aims to support biodiversity by providing a reliable tool for detecting the invasive Asian hornet (Vespa velutina), which poses a significant threat to honeybee populations and local ecosystems. By enabling early detection and monitoring, the application helps protect native species and maintain ecological balance.

Installation Instructions

Follow the installation instructions in the README to set up the vespCV application on your Raspberry Pi. Ensure that all hardware requirements are met and that the necessary software dependencies are installed.

Known Issues

• Application Closure Error: After closing the application, users may encounter errors related to invalid command names for LED timer and status updates, indicating issues with the shutdown process.
• As this is a beta release, users may encounter other bugs or unexpected behavior. Feedback is encouraged to help improve the application.

Feedback

We welcome any feedback, bug reports (not only related to Asian hornets), or feature requests. Please open an issue in the GitHub repository or contact us directly.

Future Plans

• Fix the Application Closure Error.
• Address any identified bugs and improve system stability based on user feedback.
• Enhance the detection algorithm with the captured images from the detectors.
• Expand functionality based on user needs (e.g., modern UI and desktop icon to start the application).