Predstavitev projekta AIBeeSystem – sodelovanje med IJS in podjetjem Senso4s d. o. o. na pridobljenem projektu DIH4AI
AIBeeSystem je evropski podprojekt, katerega partnerstvo sestavljata mlado, inovativno slovensko podjetje Senso4s d. o. o. in Institut ”Jožef Stefan”. Pri projektu kot zunanji izvajalec sodeluje tudi Zavod Medtem v sodelovanju z Društvom Urbani čebelar.
Cilj projekta je razvoj z umetno inteligenco podprtega čebelarskega sistema, ki spremlja več različnih parametrov znotraj in zunaj panja.
Namen sistema je ponuditi čebelarju podporo pri odločitvah, vezanih na posege v panj (npr. hranjenje družine ali širitev prostora) ter ga obveščati o objektivnem stanju panja in dogajanju v njegovi bližnji okolici (npr. rojenje čebel). Z optimizacijo posegov v panj, je namreč moč zmanjšati stres pri čebeljih družinah, kar pomembno vpliva na njihovo zdravstveno stanje in produktivnost. Dodatno pa lahko čebelar zmanjša svoj ogljični odtis obiskovanja oddaljenih lokacij, kot tudi obremenitev lastnega telesa, ki v primeru dela z nakladnimi panji ni zanemarljiva.
Vzorci sistema se trenutno testirajo na čebelnjaku podizvajalca projekta v Ljubljani. Preliminarni nabor surovih podatkov s čebelarjevimi opombami je javno dostopen na zahtevo (povezava). AIBeeSystem je prejel financiranje programa Evropske unije za raziskave in inovacije, Obzorja 2020, preko drugega javnega razpisa (Open Call 2) projekta DIH4AI, financiranega po pogodbi št. 101017057.
Presentation of the AIBeeSystem project – cooperation between JSI and the company Senso4s d.o.o. on the acquired DIH4AI project
AIBeeSystem is a European sub-project led by the young, innovative Slovenian company Senso4s d. o. o. and the Jožef Stefan Institute, whereas Zavod Medtem participates as a subcontractor in cooperation with Urban Beekeepers’ Association of Slovenia.
The project aims to develop an AI-supported beekeeping system that monitors several parameters inside and outside of a beehive.
The goal of the system is to offer support to a beekeeper in decisions related to beehive interventions (e.g., it is necessary to feed a bee colony or add additional frames) and inform them about the state of the beehive and its immediate surroundings (e.g., swarming occurred). By optimizing beekeepers’ interventions in terms of their frequency and duration, it is possible to reduce stress in the bee colonies, which can have a significant impact on their health and productivity. In addition, beekeepers can also reduce the carbon footprint of their beekeeping and the strain on their bodies, which is not negligible in the case of beekeeping with vertically modular beehives.
The system samples are currently being tested at the project subcontractor’s bee yard in Ljubljana, Slovenia. The preliminary dataset with raw data and beekeeper’s notes is publicly available upon request (link). AIBeeSystem has received funding from the European Union’s Horizon 2020 research and innovation programme under Open Call 2 of DIH4AI project GA No 101017057.
