TY - GEN
T1 - Smart traffic management to support people with color blindness in a Smart City
AU - Ochoa, Alberto
AU - Oliva, Diego
PY - 2019/1/23
Y1 - 2019/1/23
N2 - 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.
AB - 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.
KW - Bat Algorithm
KW - Bioinspired Algorithm
KW - People with Color Blindness
KW - Smart applications in a Smart City
KW - Smart City
KW - Traffic Light Detection
KW - Traffic Management
UR - http://www.scopus.com/inward/record.url?scp=85062519454&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062519454&partnerID=8YFLogxK
U2 - 10.1109/LA-CCI.2018.8625217
DO - 10.1109/LA-CCI.2018.8625217
M3 - Conference contribution
AN - SCOPUS:85062519454
T3 - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
BT - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
Y2 - 6 November 2018 through 9 November 2018
ER -