Browsing by Author "YAKUBU, OSMAN"

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    A NOVEL SOIL MOISTURE, TEMPERATURE AND HUMIDITY MEASURING SYSTEM- AN IOT APPROACH
    (Journal of Theoretical and Applied Information Technology, 2021-03) AKPALU, 1 LARRY ELIKPLIM KODJO; Gyening, Rose-Mary Owusuaa Mensah; YAKUBU, OSMAN; 0000-0002-8087-5207
    The world is currently experiencing a rapid population growth resulting in increased food demand. To avoid the risk of famine in especially low-income countries, effective and efficient agricultural practices that will enhance food production at a lower cost is desired. For effective food production, soil quality is very important. There should be improved techniques to determine precise soil moisture, humidity, and temperature measurement to guide farmers to be efficient. In Sub-Saharan African countries such as Ghana, farmers use conventional methods to check how good the soil is for cultivating crops; they examine the soil with their bare hands. This approach has proven to be ineffective as it requires significant amount of human effort. To address this challenge, an IoT based soil moisture, humidity, and temperature measurement system is proposed. It consists of a moisture probe to determine the moisture percentage of the soil, a temperature and humidity sensor for measuring the temperature and humidity of the soil, and a Wi-Fi module for transmitting the data to a data repository for analysis. A prototype is developed based on a conceptual framework which is tested under live conditions. Based on ideal parameters for the cultivation of certain crops which are stored in the data repository, and the live data captured by the sensors, the farmers are alerted electronically on the most suitable crops to plant. The system was tested in five different locations and based on the data gathered, it recommended the products that are suitable for cultivation in a particular field. The proposed system outperformed other referenced models in identifying soil suitability for the cultivation of crops. The system was able to recommend suitable crops for planting based on data on soil parameters, a feature that made it novel.