BeeBetter: A Multi-modal Beehive System for Honeybee Health Monitoring and Hazard Detection

The BeeBetter Project aims to develop viable solutions to counter the increasing decline of honeybee colonies and enhance beekeeping methods using modern technology and design. Automation has enhanced many things in our world, technologies such as IoT systems, AI and robotics are the next step in automation. Honeybees are vital pollinators for the environment, and their protection from numerous threats is crucial for our crops and food security, as the majority of our food source and flora. The current results focus primarily on machine learning implementation and modeling. The research combines tracking hive conditions such as hive temperature, CO2 readings and weight for population estimation, with a multimodal machine learning system, the project seeks to create an early warning system for any threats towards honeybee colonies. This could help beekeepers take timely action to prevent colony collapse, ultimately contributing to the safety of our vital pollinators and protecting our food sources, as a variety of fruits and vegetables.