The project

Our partner developed a machine learning-powered mobile application designed to monitor and forecast bee population growth and hive health using advanced AI-driven technology.

Key Features:

• Intuitive Mobile Application – A user-friendly interface allows beekeepers to efficiently track hive conditions.
• Object Recognition Technology – AI-powered image recognition accurately calculates bee populations within the hive.
• Smart Beehive Inspection – Machine learning enhances hive monitoring and automates inspection processes.
• Cloud-Based Data Processing – Advanced cloud computing capabilities ensure accurate forecasting and data management.

Efficient Hive Inspections With this application, beekeepers can complete a comprehensive hive inspection in under 10 minutes. This efficiency is achieved through an automated photo-taking process that identifies optimal frames and captures high-quality images for analysis. The AI module then applies computer vision techniques to precisely count the number of bees within the hive.

Comprehensive Data Insights The app enables users to upload hive photos to a secure server, where AI-driven analysis is performed. Results are then returned to the user in an intuitive format, including detailed charts and graphs that illustrate population trends and overall hive well-being.

Successful MVP Development Our partner delivered a fully functional Minimum Viable Product (MVP) for the iOS platform, overseeing the entire project lifecycle. This included defining the product architecture, data labeling, and training neural networks to ensure accurate and reliable performance. The result is a cutting-edge solution that empowers beekeepers with real-time, AI-enhanced hive monitoring capabilities.

Technologies

Unity. React Native (Android/ iOS), PHP, PyTorch, Google Cloud Platform, YOLOv3, DiigtalOcean, Python

Team

DDT, 2 developers, 1 ML engineer