Abstract

The influence of automation in the agriculture and construction industry plays a vital role in the development of the economic backbone of any country. The factors such as power, torque and speed are efficiently controlled by automation devices using Internet of things (IoT). The heavy vehicles are the multi-faced application carrier which is been used in construction, agriculture, mining and other heavy-duty fields. This research focuses on developing a IoT integrated sensor-based obstacle detection system for programmed autonomous heavy vehicles which will improve safety in both on-road and off-road construction. The automation process consists of two main categories: Observing the environment and recognizing the activities. The environment in our case is both highways and rural roads. An intelligent- camera is utilised to capture the activities from the captured video and process the data. A LiDAR sensor performs the obstacle detection process using laser reflection technology and an ultrasonic sensor is used to process the vibration and sound produced by the obstacle or upcoming vehicles. These three sensors are integrated with a controller-based device to be powered by the power distribution system in the programmed autonomous heavy vehicle.

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