| Title |
Smart irrigation system for environmental sustainability in Africa: an Internet of Everything (IoE) approach / |
| Authors |
Adenugba, Favour ; Misra, Sanjay ; Maskeliūnas, Rytis ; Damaševičius, Robertas ; Kazanavičius, Egidijus |
| DOI |
10.3934/mbe.2019273 |
| Full Text |
|
| Is Part of |
Mathematical biosciences and engineering.. Springfield, MO : AIMS Press. 2019, vol. 16, iss. 5, p. 5490-5503.. ISSN 1547-1063. eISSN 1551-0018 |
| Keywords [eng] |
smart irrigation ; smart agriculture ; internet of everything ; internet-of-things ; neural networks ; decision support ; artificial intelligence |
| Abstract [eng] |
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. |
| Published |
Springfield, MO : AIMS Press |
| Type |
Journal article |
| Language |
English |
| Publication date |
2019 |
| CC license |
|
