Paper
21 September 2023 A smart beekeeping platform based on remote sensing and artificial intelligence
Author Affiliations +
Proceedings Volume 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023); 127860C (2023) https://doi.org/10.1117/12.2681866
Event: Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 2023, Ayia Napa, Cyprus
Abstract
Honey bees play an essential role in the food chain, being responsible for one third of the global food supply due to pollination. Thus, preserving the health of beehives is of paramount environmental and economic importance. Unfortunately, at present a decline in bee populations is reported, attributed to factors such as climate change, environmental disasters, use of pesticides, etc. The SmartBeeKeep (https://smartbeekeep.eu/) research project, co-funded by EU and Greek funds, builds on the latest developments in remote sensing and AI technologies to provide a holistic platform (currently at the integration stage) that offers services addressing different needs of beekeepers and associated researchers, facilitating their work and contributing to the study of biodiversity. Specifically, an automated mapping service was implemented that runs periodically in the back end and uses the freely available multi-temporal and multi spectral Sentinel-2 data to estimate and update information regarding beekeeping flora (including blooming detection), based on state-of-the-art AI models for semantic segmentation. Moreover, a web/mobile mapping app and a mobile (progressive web) app were developed, exploiting modern remote sensing and AI technologies. In particular, the mapping app displays freely available data layers that provide crucial information for beekeepers and enables them to view and edit their own data layers, manually entering information regarding beekeeping flora near their apiaries. On the other hand, the mobile app provides two additional functionalities: a) tools for beehive inspection and management, which allow beekeepers to keep track of honeybee colonies development, applied treatments and/or feeding actions, and b) automated AI-based identification of beekeeping plants from photos captured by the mobile phone. An e-marketplace for beekeeping products as well as additional services towards laboratories performing analyses of beekeeping products as well as the general public are also included. Preliminary results for two variants of the automated mapping procedure based on a new dataset including a beekeeping plant are also presented. The final goal is improve current beekeeping practices, reduce costs, and create a new distribution channel for beekeeping products.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nikos Grammalidis, Andreas Stergioulas, Aggelos Avramidis, Konstantinos Karystinakis, Athanasios Partozis, Athanasios Topaloudis, Georgia Kalantzi, Chrisoula Tananaki, Dimitrios Kanelis, Vasilis Liolios, and Madesis Panagiotis "A smart beekeeping platform based on remote sensing and artificial intelligence", Proc. SPIE 12786, Ninth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2023), 127860C (21 September 2023); https://doi.org/10.1117/12.2681866
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KEYWORDS
Inspection

Remote sensing

Artificial intelligence

Image segmentation

Satellites

Microscopes

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