Work place: Department of Telecommunication Engineering, Federal University of Technology Minna, Nigeria
E-mail: emmanueln.nike@gmail.com
Website:
Research Interests: Analysis of Algorithms, Computing Platform, Computational Learning Theory, Software Construction, Mathematics of Computing, Models of Computation
Biography
Emmanuel N. Holds an M.Eng degree in Telecommunications Engineering from Federal University of Technology, Minna. He is also a Software Engineer with proficiency in backend development and databases. His research interests include cloud computing, Machine Learning, Internet of Things, Software defined networking and microprocessors.
By Supreme A. Okoh Elizabeth N. Onwuka Bala A. Salihu Suleiman Zubairu Peter Y. Dibal Emmanuel Nwankwo
DOI: https://doi.org/10.5815/ijitcs.2023.02.01, Pub. Date: 8 Apr. 2023
UN Department of Economics and Social Affairs predicted that the world population will increase by 2 billion in 2050 with over 50% from the Sub-Saharan Africa (SSA). Considering the level of poverty and food insecurity in the region, there is an urgent need for a sustainable increase in agricultural produce. However, farming approach in the region is primarily traditional. Traditional farming is characterized by high labor costs, low production, and under/oversupply of farm inputs. All these factors make farming unappealing to many. The use of digital technologies such as broadband, Internet of Things (IoT), Cloud computing, and Big Data Analytics promise improved returns on agricultural investments and could make farming appealing even to the youth. However, initial cost of smart farming could be high. Therefore, development of a dedicated IoT cloud-based platform is imperative. Then farmers could subscribe and have their farms managed on the platform. It should be noted that majority of farmers in SSA are smallholders who are poor, uneducated, and live in rural areas but produce about 80% of the food. They majorly use 2G phones, which are not internet enabled. These peculiarities must be factored into the design of any functional IoT platform that would serve this group. This paper presents the development of such a platform, which was tested with smart irrigation of maize crops in a testbed. Besides the convenience provided by the smart system, it recorded irrigation water saving of over 36% compared to the control method which demonstrates how irrigation is done traditionally.
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