Project description
Helping to save the bees with computer algorithms
Scientists have been warning us for years of the bees’ impending demise (bee colonies have declined to 2.5 million from 6 million in 1947) and how catastrophic their extinction would be. Bees pollinate more than 80 % of all the food we eat and are vital to sustaining Earth’s ecosystem. To help save the bees, the EU-funded HIVE-TECH project is using artificial intelligence (AI) algorithms to optimise beekeeping management. It developed an IoT data-driven decision support system that can analyse a colony’s main life parameters, such as honey production and amount of feed stock during winter. The system’s predictive algorithms can identify anomalous conditions such as lack of feed stock, and suggest what actions to take.
Objective
Bees are essential for human life, environment health and food production, with more than 80% of the world's food supply depending on pollination activity. Honeybees’ population is threatened by extensive use of pesticides, pathogens/parasites, trauma related to poor beehive management and climate changes. The yearly mortality rates of bees are in the range of 26% in Europe, reaching 40-50% in some countries and seasons. To reduce the incidence of bees’ mortality and improve profitability of the operators, it is essential to have tools to support efficient management of treatments and of beekeeping practices. HIVE-TECH is an IoT data-driven Decision Support System based on Artificial Intelligence algorithms for optimized beekeeping management. HIVE-TECH allows reducing the use of medical treatments and optimizing the beekeeping practices by analyzing the main life parameters of a colony: production of honey, amount of feed stock during winter, temperature and air quality in the hive, buzzing sound spectrum, integration with images from satellite and weather data. Thanks to proprietary predictive algorithms, HIVE-TECH can identify anomalous conditions (swarming, brood-less colony, queen stopping egg-laying, reduction in production, lack of feed stock, etc) and provide proactive suggestions for efficient management, acting as a Decision Support System. The use of HIVE-TECH was proven to reduce the mortality of bees of 20%, reduce operation costs of 20% and increase the yield of production of honey of 30%. Thanks to Data Analytics algorithms on Big Data collected, HIVE-TECH will also provide services to chemical and pharma companies, research institutes and authorities, assessing health status of bees connected to the use of new treatments, nourishments and pesticides. This represents a breakthrough solution with high potential business and huge environmental and social impact, allowing the creation a new paradigm that we name the “Internet of Bees”.
Fields of science
- natural sciencescomputer and information sciencesartificial intelligence
- social sciencessociologydemographymortality
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- engineering and technologyenvironmental engineeringair pollution engineering
- agricultural sciencesanimal and dairy scienceapiculture
Programme(s)
Funding Scheme
SME-2 - SME instrument phase 2Coordinator
20056 Trezzo Sull'Adda
Italy
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.