AI EXPERT SYSTEMS FOR INFRASTRUCTURE ASSET MONITORING

The use of Artificial Intelligence (AI) in the field of infrastructure asset monitoring has gained significant attention todays. The comprehensive review of the literature on AI expert systems for infrastructure asset monitoring. Begins with an introduction to the concept of infrastructure asset monitoring and highlights the challenges associated with traditional monitoring methods. Then focuses on the various types of AI expert systems that have been developed for infrastructure asset monitoring, including rule-based systems, fuzzy logic systems, and neural network-based systems. The strengths and weaknesses of each type of system are discussed, along with their potential applications in the field of infrastructure asset monitoring. The key components of AI expert systems for infrastructure asset monitoring, including data acquisition, data pre-processing, feature extraction, and classification. The paper highlights the importance of each of these components and provides examples of how they have been implemented in existing AI expert systems. We discussion on the current state of AI expert systems for infrastructure asset monitoring and identifies future research directions in this field. The need emphasizes for further research to address the limitations of existing systems and to develop new techniques that can improve the accuracy and efficiency of infrastructure asset monitoring. AI expert systems can improve infrastructure asset monitoring by providing real-time data analysis, predictive maintenance, and risk assessment, leading to reduced downtime and maintenance costs.