Railway Track Crack Detection & Railway Bed Elevation Measurements

It is seen many times that we take a long time to detect cracks in the track in railways, as well as today we do not have any such instrument, as well as during the survey of track cracks and track beds, we spend a lot of human power. In such a situation, it currently costs a lot to the railway, so in such a situation, the focus of the railway today is to reduce man power and move towards automation, in such a way, according to me, if we track detection and track bed surveying If we complete it in less time then it will be very beneficial for us To reduce the time taken to detect track cracks as well as to level the track bed in minimum time using UAV and Li-Dar.

• Li-Dar, 

• UAV/ Drone, 

• Thermal Scanner, 

• Aeromeg Analysis (For Levelling)

Light Fault Alarm System V1

We often see that in some areas in the railway, the lights are turned off automatically due to some minor fault or major fault. But it has been seen many times that its information does not reach the railway personnel, in such a situation that the repair of those lights is not done at the right time, in such a situation, sometimes due to the closure of the lights at that place, some accidents happen. , and if we pay attention to the attack in Mumbai, then we will come to know that terrorists attacked the power supply center of lights at many places and damaged it, but the information could not reach the office at the right time, so it’s try to design a system so that if the information reaches the Railway Electrician Office as soon as the lights are off, then in such a situation that lights can be rectified immediately If something is found wrong like the Mumbai attack, then this matter will reach the police immediately and that's why I try to design a circuit system. 

GPS Module for High Accurate Position of the Lights Tower and with the Integration of A6 GSM GPRS Module we can send the link of live location via message to any number of Control Room by using AT command in reverse case of sensor data.