Intelligent Hives

Poland, Lodz University of Technology
Intelligent Hives


Profile Image for Sebastian Górecki
Sebastian Górecki
Profile Image for Jakub Felcenloben
Jakub Felcenloben
Profile Image for Konrad Koperek
Konrad Koperek

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Project Overview

The aim of Intelligent Hives is to support beekeepers in managing their apiaries by providing them with an easy-to-use Intelligent Hives system. The system allows monitoring of the condition of bees with graphical representation of data and warnings of anomalies inside the hive to prevent the extinction of bee populations and to avoid exposing the beekeeper to additional costs or losses. In addition, the system increases the efficiency of bee product production. Every season, pollination from honey bees, native bees, and flies deliver billions of dollars (U.S.) in economic value. Between $235 and $577 billion (U.S.) worth of annual global food production relies on their contribution. Apiaries are located in different places in the world. On average, beekeepers spend 28.33 billion PLN on commuting to the apiary and 1.32 billion working hours on inspections of each hive. Nevertheless, on average 30% of bee families are unable to survive until the next season due to diseases, parasites, chemical poisoning and hunger. The loss of bees causes material and environmental damage to beekeepers, which can also affect any of us. Beekeeping is a pleasant profession or hobby, but the beekeeper often has to struggle with: * Time-consuming hive maintenance, * Late detected disease in the apiary, * Theft and sabotage of apiaries, * Not the modern apiary management system, as well as the bees after each inspection of the hive, return to their condition after 48 hours. Intelligent Hives introduce beekeeping in the 21st century. The problems of beekeepers can be solved and beekeepers' working hours better invested.

About Team

Our team consists of 2 Ph.d. students members and one master degree student of different experience and knowledge background that gives us a unique combination of qualities. Sebastian Górecki - Telecommunication and Computer Science Ph.D. student of Lodz University of Technology. Winner of Dean’s Scholarship for the best students and of the grant of the Ministry of Science and Higher Education - "The best of the best 3.0" and “The best of the best 2.0". Active member of the Lodz Solar Team developing the first polish solar-powered car and Gateway The Things Network projects. In Intelligent Hives, Sebastian is the CEO, developing the idea and the vision of the whole project, setting goals both for technical and business departments as well as developing cloud software. Jakub Felcenloben - Ph.D. student at Lodz University of technology. Professionally, an electronics engineer and product owner. He is passionate about electronics. Designs measurement electronics for Intelligent Hives. Konrad Koperek is embedded software developer. In Intelligent Hives, he makes software for bee monitoring devices, which helps analyse sound, temperature, humidity, weight form hive and save it in cloud. We have Assistant Professor - PhD Piotr Korbel - after his studies of Electronics and telecommunications, he joined Institute of Electronics (LUT) in 1999. His research interests (PhD in 2007) include digital signal processing, computational intelligence and radio communications system design. He actively participated in several national (NCRD) and international projects (including 7FP). He is active working in the field of cooperation with industry and standardization bodies (Polish National Committee for Standardization – vice chairman of Technical Committee No. 11 Telecommunications; member of Polish Information Processing Society). Technical coordinator of LUT Campus 5G pilot implementation project. His door are always opened for us and our problems. He consistently allowed this project to be our own work but steered us in the right the direction whenever he thought we needed it.

Technologies we are looking to use in our projects

App Services (Mobile & Web
Artificial Neural Networks
Big Data
Internet of Things (IoT
Machine Learning

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