Intelligent IoT Enabled Pipeline Leakage Detection and Monitoring System Using Machine Learning Algorithm

Pipeline networks are the safest transportation of oil and gas-related products that may be susceptible to failures. These kinds failures due reason manufacturing defects, degradation material, environmental interference third party. issues addressed through Internet Things (IoT) based solutions give promising outcomes in predicting monitoring. The IoT can combine sensor technologies monitor gas flow, pressure, temperature, condition compressor, concentration, other related features inside pipeline. leaks pipe measured as a pin-sized hole is detected by with advanced such deep learning. This project proposed learning meta- heuristic approach-based model detect pipelines sensors. Deep Learning called Auto Encoder Neural network (DAENN) unsupervised accurately classify leaking non-leaking pipeline conditions. detection accuracy further enhanced Bat Optimization algorithm (BOA) which obtained improved while occur monitoring area. observation deploys sensors cover mentioned increase system’s leak reliability reduces false alarm rate.