Abstract: Artificial Intelligence (AI) is transforming the agricultural sector, enhancing both productivity and sustainability. This paper delves into the impact of AI technologies on agriculture, emphasizing their application in precision farming, predictive analytics, and automation. AI-driven tools facilitate more efficient crop and resource management, leading to higher yields and a reduced environmental footprint. The paper explores key AI technologies, such as machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, (...) it discusses challenges like data privacy, barriers to technology adoption, and the ethical implications of AI in farming. Integrating AI into agricultural practices holds the promise of greater efficiency and sustainability, paving the way for future innovations. (shrink)

Mango is an economically significant fruit crop cultivated in various tropical and subtropical regions around the world. However, the productivity and quality of mangoes can be severely impacted by a range of pests. This research paper introduces an innovative approach to identify mango pests using an expert system. The expert system integrates knowledge from entomology and plants to provide accurate identification of common mango pests. The paper outlines the development and implementation of the expert system using Clips shell, which utilizes (...) rule-based techniques to analyze symptoms associated with mango pests. By inputting observed symptoms, such as leaf spots, fruit damage, leaf mild and stem cankers the system can accurately identify the specific pest species affecting the mango tree. For each pest, the paper discusses their specific symptoms and Favorable conditions that affect the mango plant. By understanding the identification and symptoms of these pests, mango growers and agricultural professionals can implement appropriate pest management strategies to mitigate the economic losses caused by these insects. The research presented in this paper aims to contribute to the body of knowledge on mango pest management, facilitating sustainable mango production and ensuring the availability of high-quality mangoes in global markets. (shrink)

This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.