In science museums or centers, exhibits are mostly interactive in nature. Interactive exhibits play a crucial role in engaging visitors by offering hands-on learning experiences. However, ensuring that these exhibits remain functional over time becomes significant challenge, particularly in terms of regular maintenance. It has also been observed that some of the exhibits are having defect in their mechanism for longer periods due to not being identified. In many cases, visitors may not even realize the exhibit is malfunctioning and may be unaware of the exhibit’s intended optimal functioning. This leads to misleading information about the functioning of respective exhibit in the museums or centers. To address the issue of unnoticed mechanical defects, we present an automated defective exhibit identification system using Raspberry Pi and IR sensors. The system continuously monitors exhibit movements and detects abnormalities using a microcontroller called Raspberry Pi and IR sensors. Additionally, it generates a live graph based on the IR sensor readings, with fluctuations indicating potential defects. This approach aims to reduce the burden of maintenance efforts, enhance the overall visitor experience, and ensure that faulty exhibits are identified and repaired in a timely manner. By implementing this system, science museums can maintain a higher standard of operational exhibits and provide visitors with more reliable and accurate learning experiences.