TY - GEN
T1 - Underpinning IoT for Road Traffic Noise Management in Smart Cities
AU - Kazmi, Aqeel
AU - Tragos, Elias
AU - Serrano, Martin
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/2
Y1 - 2018/10/2
N2 - The Internet of Things (IoT) is perceived as a key enabler for addressing the challenges that modern cities face today. IoT has the power to transform cities into Smart Cities. As a consequence, we have been witnessing the proliferation of IoT deployments in Smart Cities that aim to improve processes in various domains such as, energy, transport, health, mobility, etc. Environmental noise is one of the major issues affecting the health and well-being of residents in an urban environment. A major contribution in noise pollution comes from road traffic. This work presents an innovative IoT-based approach to monitor and manage road traffic noise in Smart Cities. Our approach uses an IoT platform for collecting and integrating data streams stemming from multifarious sensing devices. The data are then analyzed in order to identify traffic noise events; if the noise level on a particular road exceeds a specified threshold, the traffic flow is controlled by taking certain measures. In addition to research methodology, we discuss a prototype implementation of the system.
AB - The Internet of Things (IoT) is perceived as a key enabler for addressing the challenges that modern cities face today. IoT has the power to transform cities into Smart Cities. As a consequence, we have been witnessing the proliferation of IoT deployments in Smart Cities that aim to improve processes in various domains such as, energy, transport, health, mobility, etc. Environmental noise is one of the major issues affecting the health and well-being of residents in an urban environment. A major contribution in noise pollution comes from road traffic. This work presents an innovative IoT-based approach to monitor and manage road traffic noise in Smart Cities. Our approach uses an IoT platform for collecting and integrating data streams stemming from multifarious sensing devices. The data are then analyzed in order to identify traffic noise events; if the noise level on a particular road exceeds a specified threshold, the traffic flow is controlled by taking certain measures. In addition to research methodology, we discuss a prototype implementation of the system.
KW - Internet of Things
KW - Smart City
KW - Smart Traffic Management
KW - Traffic Noise Management
UR - https://www.scopus.com/pages/publications/85056451226
U2 - 10.1109/PERCOMW.2018.8480142
DO - 10.1109/PERCOMW.2018.8480142
M3 - Conference Publication
AN - SCOPUS:85056451226
T3 - 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
SP - 765
EP - 769
BT - 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
Y2 - 19 March 2018 through 23 March 2018
ER -
