An IoT Based Smart Farming System Using Machine Learning
Autor: | R. Benameur, Abou El Hassan Benyamina, Bouabdellah Kechar, Amine Dahane |
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Rok vydání: | 2020 |
Předmět: |
Plant growth
Bridging (networking) Data collection Computer science business.industry Distributed computing 010401 analytical chemistry 020206 networking & telecommunications 02 engineering and technology 01 natural sciences Field (computer science) 0104 chemical sciences Data modeling Agriculture 0202 electrical engineering electronic engineering information engineering business Internet of Things Wireless sensor network |
Zdroj: | ISNCC |
DOI: | 10.1109/isncc49221.2020.9297341 |
Popis: | Smart farming allows to analyze the growth of plants and to influence the parameters of our system in real time in order to optimize plant growth and support the farmer in his activity. Internet of Things (IoT) arrangements, based on the application particular sensors data measurements and intelligent processing, are bridging the holes between the cyber and physical worlds. In this paper, we propose the design and the experiment of a smart farming system based on an intelligent platform which enables prediction capabilities using artificial intelligence (AI) techniques. This system is based on the technology of wireless sensor networks and its implementation requires three main phases, i) data collection phase using sensors deployed in an agricultural field, ii) data cleaning and storage phase, and iii) predictive processing using some AI methods. |
Databáze: | OpenAIRE |
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