Sensing Dangers and Threats in Railway Track with Intimation using IoT

Timely detection of dangerous situations involving Lives is vital. Generally, the Railway systems are manually monitored through few people therefore there are many chances to miss or detect an occurring event late which might cause the lives of people or animals on track. In this work an overview of the Object detection method used in a system to detect the obstacles or objects on track which might cause accidents and further communicates through MQTT protocol to the respective railway officers. This paper illustrates the use of machine learning algorithms and IoT along with some embedded tools and technology that can reduce the loss of human and animal lives on railway tracks by utmost 80%.