Smart irrigation system for environmental sustainability in Africa: An Internet of Everything (IoE) approach
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Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
Amer inst Mathematical Sciences-aims
Open Access Color
GOLD
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
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.
Description
Misra, Sanjay/0000-0002-3556-9331; Maskeliunas, Rytis/0000-0002-2809-2213; Damaševičius, Robertas/0000-0001-9990-1084; Kazanavicius, Egidijus/0000-0002-4192-3042; Adenugba, Favour/0000-0003-0614-7188
Keywords
smart irrigation, smart agriculture, Internet of Everything, Internet-of-Things, neural networks, decision support, Renewable energy, decision support, smart agriculture, Agricultural engineering, Population, Environmental science, smart irrigation, Engineering, Sociology, Artificial Intelligence, QA1-939, FOS: Electrical engineering, electronic engineering, information engineering, Climate change, internet-of-things, Machine Learning Methods for Solar Radiation Forecasting, Demand Response in Smart Grids, Electrical and Electronic Engineering, Environmental resource management, Irrigation, Biology, Water Science and Technology, Demography, Ecology, Agriculture, artificial intelligence, neural networks, FOS: Sociology, Integrated Management of Water, Energy, and Food Resources, Sustainability, FOS: Biological sciences, Electrical engineering, Computer Science, Physical Sciences, Environmental Science, internet of everything, TP248.13-248.65, Mathematics, Biotechnology, Forecasting
Turkish CoHE Thesis Center URL
Fields of Science
02 engineering and technology, 0202 electrical engineering, electronic engineering, information engineering
Citation
WoS Q
Q2
Scopus Q
Q2

OpenCitations Citation Count
49
Source
Mathematical Biosciences and Engineering
Volume
16
Issue
5
Start Page
5490
End Page
5503
PlumX Metrics
Citations
Scopus : 56
PubMed : 4
Captures
Mendeley Readers : 273
SCOPUS™ Citations
56
checked on Feb 08, 2026
Web of Science™ Citations
33
checked on Feb 08, 2026
Page Views
2
checked on Feb 08, 2026
Google Scholar™

OpenAlex FWCI
5.99109208
Sustainable Development Goals
2
ZERO HUNGER

6
CLEAN WATER AND SANITATION

7
AFFORDABLE AND CLEAN ENERGY

8
DECENT WORK AND ECONOMIC GROWTH

9
INDUSTRY, INNOVATION AND INFRASTRUCTURE

13
CLIMATE ACTION

17
PARTNERSHIPS FOR THE GOALS


