In a mining environment there can be various kind of situations , which needs to be automated for various reasons, such as safety, efficiency, cost saving and many other purposes. One such use case presented by the famous company Vinci Energies, which is heavily involved in automating and maintaining mining processes. The use case is about a specific problem that can occur in monitoring of conveyer belts that is spread across a coal mine. It is currently manually done by an operator on a car. This process is not only inefficient but also unsafe for the operator because it can be sometimes hazardous in case of a fire. We Robominers propose a novel solution for monitoring this conveyer track by automated rail car running over a line. The car can contain various kind of sensors like temperature, moisture , accompanied by a thermal camera. This parameters can act as input and if there is an anomaly, it detects that and sends an alert to the connected software suit, which the operator can monitor safely from an office and take counter measures as necessary. The application suite also has machine learning capabilities, which will learn continuously from the external environment and deliver more accuracy in the results. Presently for the hackathon, we worked and managed to built a small mechanical car mounted with a logitech camera, powered by Intel Edison and built with several sensors. We use the Edison apis to run a motor, a temperature and a sound sensor. The sensor data is feed into an application, which exposes a front end, where we can monitor the data live. We managed to build a very accurate and a great prototype in 24 hours, with technology we have never used before, which is a feat we are proud of, we are really thankful to the Vinci team, who has helped us a lot in our experiments. We learned how to work efficiently under extreme time pressure and also we learned new tools (Edison) to achieve our goals.

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