Smart traffic management to support people with color blindness in a Smart City

Traffic has a significant impact on the viability and efficiency in cities. Smart traffic management aims at making urban driving more seamless and efficient, through the integration of Internet of things (IoT), with a network of interconnected cars and sensors. This paper present a Hybrid Intelligent Application based on Bat Algorithm and Data Mining -in the preparation of data associated with the instances- to help people who have difficulties identifying the colors to drive with safety by a correct interpretation of traffic signals. To do this, it classifies of regions of the traffic light by analyzing images acquired with a camera. The classification of the colors (red, yellow and green) that are presented in the traffic light is done by three straight line equations that delimit the RGB space, which are tuned by a bio-inspired algorithm, using for this images that are previously labeled with the color that corresponds. Once the color of the light has been classified, an audio aid is produced indicating red, green or yellow, as appropriate, so that people who have difficulties identifying the colors or people with color blindness, can drive properly. Current results are encouraging since they show significant improvement to support people to drive with safety by a correct interpretation of traffic signals.