Back to the future: IoT to improve aquaculture: Real-time monitoring and algorithmic prediction of water parameters for aquaculture needs
Lafont, M.; Dupont, S.; Cousin, P.; Vallauri, A.; Dupont, C. (2019). Back to the future: IoT to improve aquaculture: Real-time monitoring and algorithmic prediction of water parameters for aquaculture needs, in: 2019 IEEE Global Internet of Things Summit (GIoTS) Proceedings, Aarhus, Denmark, 17-19 June, 2019. pp. 6 pp. https://hdl.handle.net/10.1109/giots.2019.8766436
In: (2019). 2019 IEEE Global Internet of Things Summit (GIoTS) Proceedings, Aarhus, Denmark, 17-19 June, 2019. IEEE: Piscataway. ISBN 978-1-7281-2171-0 . , meer
Aquaculture is a booming market since several decades and has surpassed fisheries worldwide. Like agriculture, aquaculture has known for some years a technological revolution to meet the challenges of the industry. The development of IoT in this sector will improve its sustainability and profitability and allows to answer to the digitization. Water quality is at the heart of aquaculture and its mastery is the key to success. The integration of sensors able to measure water quality with long-range transmission opens the possibility of real-time monitoring. The generation of a large variety and a large amount of data make it possible to anticipate and predict the evolution of water parameters. The contribution of IoT for artificial intelligence therefore allows aquaculture to take the technological turn necessary for the growth of this area with an environmental sustainability vision. In this paper, we describe a feedback from the use of IoT for the real-time monitoring of water quality and the development of prediction systems in an aquaculture context.
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