Search results for: A. G. Adesoji

Authors: Adesoji T. Jaiyeola, Josiah Adeyemo

Abstract:

This paper presents an extensive review of literature relevant to the modelling techniques adopted in sediment yield and hydrological modelling. Several studies relating to sediment yield are discussed. Many research areas of sedimentation in rivers, runoff and reservoirs are presented. Different types of hydrological models, different methods employed in selecting appropriate models for different case studies are analysed. Applications of evolutionary algorithms and artificial intelligence techniques are discussed and compared especially in water resources management and modelling. This review concentrates on Genetic Programming (GP) and fully discusses its theories and applications. The successful applications of GP as a soft computing technique were reviewed in sediment modelling. Some fundamental issues such as benchmark, generalization ability, bloat, over-fitting and other open issues relating to the working principles of GP are highlighted. This paper concludes with the identification of some research gaps in hydrological modelling and sediment yield.

Keywords: Artificial intelligence, evolutionary algorithm, genetic programming, sediment yield.

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Authors: O. M. Olanrewaju, F. O. Echobu, A. G. Adesoji, E. D. Ajik, J. N. Ndabula, S. Luka

Abstract:

Nutrients are required for any soil with which plants thrive to improve efficient growth and productivity. Amongst these nutrients required for proper plant productivity are nitrogen, phosphorus and potassium (NPK). Due to factors like leaching, nutrient uptake by plants, soil erosion and evaporation, these elements tend to be in low quantity and the need to replenish them arises. However, this replenishment of soil nutrients cannot be done without a timely soil test to enable farmers to know the amount of each element in short quantity and evaluate the amount required to be added. Though wet soil analysis is good, it comes with a lot of challenges ranging from soil test gargets availability to the technical knowledge of how to conduct such soil tests by the common farmer. The Internet of Things test kit was developed to fill in the gaps created by wet soil analysis, as it can test for NPK, soil temperature and soil moisture in a given soil at the time of test. In this implementation, a sample test was carried out within 0.2 hectares of land divided into smaller plots. The kits performed adequately well, as the range of values obtained across the segments was within a very close range.

Keywords: Internet of things, soil nutrients, test kit, soil temperature.

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