Abstract
Nowadays going out anywhere, especially in urban areas is becoming more and more of a headache. Going out during peak hours to go to work or from leaving work, and being stuck for a long time in traffic is just frustrating. Having traffic lights on the road during peak hours sometimes do not really help. Traditional traffic lights do not really account for the difference of vehicle density on the different lanes. Thus police officers are tasked to take responsibility to control traffic at junctions which, if not controlled, can be chaotic. Furthermore, the police officers, while controlling traffic are exposed to harmful gas emission which can be disastrous for health. Commuters who are stuck in the traffic are also exposed to notorious gas emission. As a consequence the problem is that traditional traffic lights do not react dynamically to the change in traffic density at different point of time and also they do not take into account the amount of pollutants which drivers are exposed to. To try and solve these two problems, this paper proposes a smart traffic light which takes into account the density of vehicle in a lane as well as the level of vehicle emission within each lane. Such that if the level of vehicle emission is notorious for the health within a lane, the traffic light will go green otherwise it will remain red up until a threshold number of vehicle has been reached within a lane. The smart traffic light, through the use of Internet of Things, works with sensors such as magnetic and gas to detect the amount of vehicles and gas emission levels on each lane, respectively. Each lane has a set of these sensors connected to an Arduino which in turn are all connected to a central Raspberry Pi. The Raspberry Pi, being connected to the Internet, will do all the processing via Node-RED. Node-RED is a graphical interface for node.js. All data captured by the sensors are sent to the IBM Bluemix Cloud for analysis. With this system it is envisaged a more fluid and dynamic traffic which takes vehicle emission into account at the traffic light.
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Mungur, A., Bheekarree, A.S.B.A., Hassan, M.B.A. (2019). Smart Eco-Friendly Traffic Light for Mauritius. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol 887. Springer, Cham. https://doi.org/10.1007/978-3-030-03405-4_33
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