A Review on Fault Detection in IOT Sensor using Machine Learning

In order to provide accurate and dependable sensor measurements which are crucial for decision-making and system integrity in today’s data-driven environments this study builds a strong methodology for sensor failure identification utilizing deep learning techniques. Using an extensive dataset of sensor readings under different scenarios, the study compares many state of the art deep learning architectures to find the most effective and precise techniques for real-time sensor defect detection. The results demonstrate how deep learning may be used to improve the accuracy and dependability of sensor data, which can increase the dependability of sensor-driven systems in a variety of contexts.