Passenger and luggage weight monitoring system based on sensing technology: a case of Zambia

Abstract

The prevalence of overloading, which is exceeding the maximum load weight, on public transport especially buses in Zambia is very rampant. This is attributed mainly to the fact that there is currently no system to measure and monitor load weight particularly at bus stations apart from few weighbridges on few selected roads located far away from the loading points. The phenomenon of overloading leads to damage to road pavements which in turn lead to compromise in road safety, damage to vehicle, higher fuel consumption, and reduces the lifespan of both the motor vehicles and the road infrastructure. The aim of this study was to design, develop, and implement a model prototype of passenger and luggage weight monitoring system to mitigate the challenge of overloading on public buses. To achieve this, a baseline study was conducted to appreciate the challenges of the current system being experienced in the management of passengers and luggage load weight on public buses at bus stations to avoid overloading. It was revealed from the study that the challenge of overloading on public buses was mainly due to luggage at 96 percent while that of passengers was only at 7 percent. It was also revealed that there was a direct proportional relationship between the causes of overloading and risk factors contributing to causes of road traffic accident, and these were the human factors. The risk factors considered to contribute to compromised road safety leading to road traffic accidents were also established from all stakeholders and the following were the outcomes: 54 percent human, 39 percent road/environmental, 6 percent vehicle and 1 percent was attributed to other factors. The results of the baseline study were then used as a basis to design and develop a Load Weight Monitoring System (LWMS) based on sensing technologies of weight and motion. Other emerging technologies like Web-based Mobile Communication, Internet of Things (IoT), and Cloud Computing concepts where also utilized to automate the data capturing and transmission to the main server. The proposed LWMS model prototype employed Load Cells and Motion Sensors to capture the load weight and direction respectively. The data captured by the sensors was then computed by the Arduino microcontroller before sending it to the central data centre for onward forwarding to relevant stakeholders. Keywords: Overloading; Load Weight; Sensing Technologies; Emerging Technologies; Load Weight Management System.