Sustainable Dynamic Bus Management System Using Machine Learning and IoT

Sustainable Dynamic Bus Management System Using Machine Learning and IoT

연구 분야: Databases

학회: International Conference on Sustainable Development through Machine Learning, AI and IoT

The abstract provides a concise overview of our comprehensive Dynamic Bus Management System, designed to optimize the operations of a bus fleet for improved efficiency and enhanced transportation services. Currently, buses are an important part of the public transport system. Traveling by bus is an option but in most cases the chance of a bus getting delayed is high, it can be due to various reasons like heavy traffic, engine problems, etc. The objective of this project is to provide real-time locations, and routes of travel, also recommend buses to a particular destination and the best travel options, that ensure available bus routes, available buses to a destination, provide bus timing to reach the bus stop and required time to reach the destination. IoT provides real-time bus location and machine learning to build a recommendation engine. The recommendation is based on most scored, reviewed, budget, travel comments, and similar travels. Cloud-based database is used for storing and manipulating the data. The database stores the location along with the update time. Updating time and location can be used to calculate the time taken to travel and average speed. If the bus is not running on that day, the proper indication is displayed along with the location and the timing of the next bus through the route will be given. Machine learning server uses data in the database to recommend the best route to travel and creates a model for future use. The user interface is provided by using an Android application. This proposed system saves time and increases end-users work efficiency by reducing the user’s efforts to travel for work and avoiding the waiting time for the bus.