Revolutionizing Precision Agriculture Using Artificial Intelligence and Machine Learning

Plant disease mechanization in the agricultural discipline is a major source of concern for every country, since the world's population continues to grow at an alarming rate, increasing the need for food. However, due to a scarcity of necessary infrastructure in various parts of the world, it is difficult to identify them quickly in some areas. In the context of the expanded use of technology, it is now feasible to assess the efficiency and accuracy of methods for identifying illnesses in plants and animals. It has recently been discovered that information technology-based tools, technologies, and applications are effective and realistic measures for the improvement of the whole agricultural field, spanning from scientific research to farmer assistance. The integration of expert systems as a strong tool for stakeholders in agricultural production has enormous promise, and it is now being explored. The suggested effort begins with the collection of disease symptoms and environmental factors by agriculture specialists and plant pathologists, who will then analyze the information gathered. The corrective solution is then recommended to the end user by an expert system, which is accessed through a mobile application. Computer application consisting of an expertise base, inference engine, and a user interface is envisaged as the machine of the future. Integrated inside the gadget is a structured expertise base that contains information on the signs and treatments of various ailments. In order to identify and diagnose plant disorders, the machine must first locate and diagnose the condition. It is accomplished by the analysis of the symptoms of illness on the crop's surface. On the basis of the yield and the surrounding environment, this symptom is utilized to identify the illness and give an entirely unique diagnostic solution. The computer will test the plants and their disordered lives inside the database and provide a set of diagnostic levels in accordance with the condition that the plants are suffering from, according to the database. Farmers may easily identify and manipulate plant diseases with the help of the suggested technology, which is supported by a sophisticated expert system.

Keywords: Plant disease, Expert system, Image-based approach, Knowledge base.