Prospect of Smart Agriculture Using IoT and Data Analytics: A Perspective of Kebbi State, Northwestern Nigeria

Nigeria is an agricultural nation, with majority of its citizenry predominantly relied on it for survival. Recently, the sector is receiving a lot of attention due to the need to diversify and a bit away from an oil-driven economy. The sector is one among the most contributing to the nations` Gross Domestic Product (GDP), recording 21% in the previous year. However, one of the causes of low crop yield is diseases caused by agents such as fungi, bacteria, and viruses. The advent of technology has led to its influence in the agricultural sector. The recent evolution and fusion of IOT, ML and Data Analytics has brought succour for especially plant monitoring and management. This research work investigated the capability of IOT, ML and DA in tomato plant disease classification in Yauri Emirate, Northwestern Nigeria. We further conduct a survey with a view to understanding the knowledge, acceptability or otherwise of the mentioned techniques. The result of our classification using CNN, a DL model achieves a near-optimal accuracy of 98.6% with a loss of 0.03% while recording over 98.3 % for both precision and recall on the predicted labels. We also observed that our target audience for the survey lacks near total knowledge of smart farming, hence the need for the stakeholders in the domain to embark on sensitization and awareness towards reaping its numerous advantages.