![]() The result analysis shows that proposed system is more precise and consumes less time than existing system. A sufficient analysis is carried out to consolidate the results obtained. Once the object is detected the system informs the user to slow down the vehicle through a voice message. The system can classify objects like vehicles, animals, humans, etc. The classification is done by using proposed Advanced Classifier for the detection of objects. The framework performs preprocessing utilizing the Mean Subtracted Difference Enhancement (MSDE) strategy and afterward segmentation is performed. A thorough study is performed on a test image to test the best algorithm suitable for detecting image boundaries. In the proposed work, the Raspberry Pi Camera module is used for object detection and image acquisition. 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. The most difficult task is to detect obstacles on the highway. Most of the Indian roads in rural and suburbans 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. Simultaneously they lose their life and significant properties in those accidents. D.Y Patil School of Engineering Lohegaon, Pune, Savitribai Phule, Pune UniversityĪbstractAt present situation the human beings are going through many accidents during the road way transportation. Object Detection using IoT and Machine Learning to Avoid Accident and Improve Road Safetyĭr.
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