Smart irrigation system for environmental sustainability in Africa: An Internet of Everything (IoE) approach

Favour Adenugba; Sanjay Misra; Rytis Maskeliūnas; Robertas Damaševičius; Egidijus Kazanavičius; Favour Adenugba; Sanjay Misra; Rytis Maskeliūnas; Robertas Damaševičius; Egidijus Kazanavičius

doi:10.3934/mbe.2019273

Mathematical Biosciences and Engineering

2019, Volume 16, Issue 5: 5490-5503. doi: 10.3934/mbe.2019273

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Research article Special Issues

Smart irrigation system for environmental sustainability in Africa: An Internet of Everything (IoE) approach

1.
Department of Electrical and Information Engineering, Covenant University, Ota 0123, Nigeria
2.
Department of Computer Engineering, Atilim University, Incek 06836, Ankara, Turkey
3.
Department of Multimedia Engineering, Kaunas University of Technology, Kaunas, Lithuania
4.
Department of Software Engineering, Kaunas University of Technology, Kaunas, Lithuania
5.
Centre of Real Time Computer Systems, Kaunas University of Technology, Kaunas, Lithuania

Received: 21 December 2018 Accepted: 30 May 2019 Published: 13 June 2019

Water and food are two of the most important commodities in the world, which makes agriculture crucial to mankind as it utilizes water (irrigation) to provide us with food. Climate change and a rapid increase in population have put a lot of pressure on agriculture which has a snowball effect on the earth's water resource, which has been proven to be crucial for sustainable development. The need to do away with fossil fuel in powering irrigation systems cannot be over emphasized due to climate change. Smart Irrigation systems powered by renewable energy sources (RES) have been proven to substantially improve crop yield and the profitability of agriculture. Here we show how the control and monitoring of a solar powered smart irrigation system can be achieved using sensors and environmental data from an Internet of Everything (IoE). The collected data is used to predict environment conditions using the Radial Basis Function Network (RBFN). The predicted values of water level, weather forecast, humidity, temperature and irrigation data are used to control the irrigation system. A web platform was developed for monitoring and controlling the system remotely.

Keywords:

Citation: Favour Adenugba, Sanjay Misra, Rytis Maskeliūnas, Robertas Damaševičius, Egidijus Kazanavičius. Smart irrigation system for environmental sustainability in Africa: An Internet of Everything (IoE) approach[J]. Mathematical Biosciences and Engineering, 2019, 16(5): 5490-5503. doi: 10.3934/mbe.2019273

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Abstract

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