Designing an IOT traffic management framework in Kenya: a case Of Nairobi city county

Abstract

Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Nairobi city residents encounter a myriad of problems on the roads every day, thanks to the increasing population in the city and also due to the influx of motor vehicles in the city using a constrained road network. Some of these problems include failure to find parking spaces in the central business district and the lack of enough drop off and pick up points. Traffic index report released by Ynumbeo (2017) revealed that on average, residents of Nairobi spend 62.44 minutes in traffic every day. This research aims to advance an endurable traffic management design framework based on IoT and to help resolve some of the traffic issues of Nairobi City. The specific objectives of the study were: To assess and review current generic design frameworks of IoT sensors available in the market today with regard to traffic management, To analyse the benefits therein associated with the IoT implementation on traffic management as opposed to the Manual traffic management and to develop an endurable IoT traffic management design framework for Nairobi city. The research was cross sectional with analytical component and through simple random sampling, comprising of 21 officers from the city inspectorate and enforcement, 9 from the traffic police department and 162 private drivers. A sample of the respondents was drawn using stratified sampling. Each respondent filled and submitted a structured self-administered questionnaire. The processed data was analyzed using descriptive statistics. Statistical Package for Social Sciences (SPSS) Version 25 and Excel spreadsheet were used to analyse the findings. Private cars spent an average of 1.6 hours in the morning while in the evening they spent an average of 2.0 hours stuck in the traffic jam. This was aggravated by the fact that drivers sometimes fail to identify existing parking slots in town with drivers spending an average of 30 minutes looking for parking slots in the morning. This research provides an analysis of how different sensors can communicate and help improve the current traffic congestion in the city and how other different facets like, smart parking sensors, smart streetlights, smart highways and smart accident assistance can be integrated in the same study. For the full scale adoption of IoT in parking management, the system requires data sensors (RFID tags) to give the location of the cars in the parking lots, WIFI with IPv4 or IPv6 for receiving and transmitting information regarding the cars parked, cloud computing technologitechnologies to process the information as well as back-end management for the entire system.