Object Detection using IoT and Machine Learning to Avoid Accident and Improve Road Safety

Abstract

At present situation the human beings are going through many accidents during the road way transportation. Simultaneously they lose their life and significant properties in those accidents. Most of the Indian roads in rural and suburban's are not ideal for driving due to faded lanes, irregular potholes, inappropriate and unseen road signs, which caused many accidents, lost lives and caused serious damage to vehicles. The most difficult task is to detect obstacles on the highway. The basic concept is to design a system that has the effect of detecting the presence of an obstacle in the track of the vehicles. In the proposed work, the Raspberry Pi Camera module is used for object detection and image acquisition. A thorough study is performed on a test image to test the best algorithm suitable for detecting image boundaries. The framework performs preprocessing utilizing the Mean Subtracted Difference Enhancement (MSDE) strategy and afterward segmentation is performed. The classification is done by using proposed Advanced Classifier for the detection of objects. The system can classify objects like vehicles, animals, humans, etc. Once the object is detected the system informs the user to slow down the vehicle through a voice message. A sufficient analysis is carried out to consolidate the results obtained. The result analysis shows that proposed system is more precise and consumes less time than existing system.