Intelligent Vehicle Weight Monitoring and Overload Detection Using ML Algorithms

Abstract

In the face of overburdening, it is critical to differentiate between health and financial issues, which is why the National Division of Transportation has incorporated an anti-overburdening purpose in its Road Safety system. Commercial vehicle overcrowding has a significant influence on the future of street groups. The expense of premature highway breakdown and repair is a significant burden on many states, especially in agricultural nations, where this issue diverts essential monies that could otherwise be spent on health and education. The evolution of a country's automotive structure serves as a barometer of its economic success. As the economy gradually recovers, the transportation industry continues to grow. Overcrowding has become an issue in vehicle transportation. As a result, how easy and advantageous it is to realize the vehicle load, as well as how far it may be overburdened, has become a major source of debate. To solve the issue of overburdening traveler vehicles, a vehicle-mounted overburdening control framework for traveler vehicles was developed. The framework included a sensor circuit, a sensor control circuit, and a connection point circuit with a microprocessor. Vehicle load control framework coordination gadgets can identify vehicle burden to avoid overburdening and promote vehicle security, and it can substantially minimize the arduous work of the vehicle load testing station and increase transportation sector job proficiency.