Название: Applications of Computational Learning and IoT in Smart Road Transportation SystemАвтор: Saurav Mallik, Hong Qin, Subrata Nandi, Munshi Yusuf Alam, Arup Roy, Tanvir Habib Sardar
Издательство: Springer
Год: 2025
Страниц: 240
Язык: английский
Формат: pdf (true), epub
Размер: 23.3 MB
This book discusses Machine Learning and AI in real-time image processing for road transportation and traffic management. There is a growing need for affordable solutions that make use of cutting-edge technology like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT). The efficiency, sustainability, and safety of transport networks can be greatly increased by implementing an Internet of Things (IoT) and Machine Learning (ML)-based smart road transport system. Install sensors on roadways and intersections to gather data on traffic conditions in real time, such as vehicle density, speed, and flow. Predicting traffic patterns is done by analyzing the gathered data using machine learning algorithms. This can lessen traffic, enhance overall traffic management, and optimize traffic signal timings. Vehicles equipped with Internet of Things devices can have their health monitored in real time. Parameters including lane changes, brake condition, tire pressure, and engine performance can all be monitored by sensors. Based on the gathered data, ML models are used to forecast probable maintenance problems. By scheduling preventive maintenance, failures can be avoided and overall road safety can be increased.
