As the world’s population grows, the number of public transport users increases almost at the same rate, which creates a need for a higher offer in terms of the number of public transport vehicles, thus ensuring the best traveler’s experience. However, transportation companies still have the challenge to control the correct money made by their vehicles due to some unfair drivers who steal part of the income for their personal use as a traditional solution, Supervisors are engaged to guarantee that the buses are used properly. Most particularly in Rwanda’s public transportation sector, unfair public transportation drivers have been boarding people after leaving the departure station but before reaching the destination station. In this research, an analysis of the public transportation business in Rwanda has been done to understand the ecosystem of public transportation service providers in Rwanda; key operational difficulties from discussions with public transportation company owners and managers have also been carried out. The findings from an interview with 20 public bus owners and 18 public transportation company managers showed that most drivers claim less income than is actually earned, and the claim is likely much higher, that is according to 98 percent of the bus owners and 90 percent of the managers questioned. An IoT-based seat occupancy monitoring system has now been designed and prototyped for public transport vehicles to improve and facilitate companies to know all their income without being misled by their staff by detecting seat occupancy, computing a passenger’s distance traveled, and calculating the distance fee in real time. Indeed, the system prototyped in this project can be installed in each company’s vehicle to daily monitor and report various events that occur within vehicles during service, allowing an alternative estimation of revenues generated by the vehicle based on seat occupancy as a function of passenger distance traveled.And costs which were spent on paying the supervisors will be spared in the long run by increasing the company’s return on investment. A collection of future works and views has been assessed as a result of this research project, including vehicle mechanical condition monitoring in order to ensure timely vehicle repair. In contrast to the existing literature, this mostly focuses on smart transportation; this study resulted in an innovative use of seat weight sensor and Hall Effect sensor to provide a solution to address the issue. A smart phone’s application that allows passengers to see available free seats as well as their exact location in the coming bus is suggested, and also a leveraged artificial intelligence is necessary after gathering enough data for the system to be smarter than its current version.