Descripción del proyecto
Algoritmos informáticos para ayudar a salvar a las abejas
Los científicos nos han estado advirtiendo durante años de la inminente desaparición de las abejas (desde 1947, las colonias de abejas han disminuido de 6 millones a 2,5 millones) y de lo catastrófica que sería su extinción. Las abejas polinizan más del 80 % de todos los alimentos que consumimos y son vitales para mantener el ecosistema de la Tierra. Para ayudar a salvar a las abejas, el proyecto HIVE-TECH, financiado con fondos europeos, utiliza algoritmos de inteligencia artificial (IA) para optimizar la gestión apícola. Este proyecto desarrolló un sistema de apoyo a las decisiones basado en datos del internet de las cosas que puede analizar los principales parámetros vitales de una colonia, como la producción de miel y la cantidad de alimentos almacenados durante el invierno. Los algoritmos predictivos del sistema pueden identificar condiciones anómalas como la falta de alimento, y sugerir qué medidas adoptar.
Objetivo
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”.
Ámbito científico
- 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
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SMEInst-2018-2020-2
Régimen de financiación
SME-2 - SME instrument phase 2Coordinador
20056 Trezzo Sull'Adda
Italia
Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.