Smart Farming Monitoring Through Artificial Intelligence for Enhancement of Harvest Quality and Productivity

This research targets the development of the agriculture industry in O man transferring it towards a new level that uses the artificial intelligence and machine learning to improve productivity, health and value. Providing food has always been a great challenge for the Omani people who have developed different methods to improve this industry starting from making Falaj networks and agricultural terraces in the mountains. Considering all the challenges in the agicultural sector in Oman, the need to introduce new technologies and methods is a demand to comply with Oman Vision 2040 which targets to increase the contribution of this sector to the GDP along with other sectors to reach 90 % of the overall GDP according to Oman Vision 2040 document. In agriculture, it has been always depending on specific static understanding and actions in agriculture. For example, amount of water, proper temperature, soil type, fertilizer's types and many other indicators will affect the agriculture industry and the productivity accordingly, yet each farmer uses his own experiences over the years without actively partnering with other farmers to improve the production dynamically. This research aims to make dynamic measures and statistics gathered from different locations to be analysed and maintained by the A I and machine learning that to improve and enhance these values by the means to provide the highest possible productivity with the largest amount of nutrients and health while decreasing the costs. The research will use sensors, actuators, control units Raspberry P i-, database system, A I and machine learning software running in central controlling server deployed in 3 main environments for the experiment to adopt the changes and adjust the outputs accordingly providing the desired results.