Smart Lighting and IoT Integration: Pioneering Solutions for Traffic Congestion Management - Case Study

S. K. Lam; Y. K. Chan; C. C. Lee; W. F. Tang; S. L. Mak; K. W. Tsang; Y. Wang; Zhaobin Li

doi:10.1109/IEEM63636.2025.11357742

Smart Lighting and IoT Integration: Pioneering Solutions for Traffic Congestion Management - Case Study

S. K. Lam
, Y. K. Chan
, C. C. Lee
, W. F. Tang
, S. L. Mak
, K. W. Tsang
, Y. Wang
, Zhaobin Li

Construction and Quality Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This study explores the integration of Smart Lighting and IoT technologies to address traffic congestion at drop-off areas of large public facilities. A Traffic Congestion Management System was designed and implemented on a 240-meter-long departure road in Hong Kong. The system utilizes laser-based occupancy sensors for high-accuracy detection, LED signage for dynamic driver guidance, and Power over Ethernet (PoE) technology for simplified installation and energy efficiency. Real-time data communication enables predictive analysis and preventative maintenance, ensuring optimal performance.Preliminary testing showed acceptable accuracy and precision, though a minor 2-4 second delay in LED sign activation was observed. Despite this, the system effectively improves traffic flow, reduces driver confusion, and minimizes delays. This study demonstrates the potential of Smart Lighting and IoT in traffic management and highlights opportunities for future research in Smart City applications.

Original language	English
Title of host publication	IEEM 2025 - IEEE International Conference on Industrial Engineering and Engineering Management
Pages	1185-1189
Number of pages	5
ISBN (Electronic)	9798331525217
DOIs	https://doi.org/10.1109/IEEM63636.2025.11357742
Publication status	Published - 2025
Event	2025 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2025 - Melbourne, Australia Duration: 7 Dec 2025 → 10 Dec 2025

Publication series

Name	IEEE International Conference on Industrial Engineering and Engineering Management
ISSN (Print)	2157-3611
ISSN (Electronic)	2157-362X

Conference

Conference	2025 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2025
Country/Territory	Australia
City	Melbourne
Period	7/12/25 → 10/12/25

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities

Keywords

IoT
Smart Sensor
Traffic congestion

Access to Document

10.1109/IEEM63636.2025.11357742

Cite this

Lam, S. K., Chan, Y. K., Lee, C. C., Tang, W. F., Mak, S. L., Tsang, K. W., Wang, Y., & Li, Z. (2025). Smart Lighting and IoT Integration: Pioneering Solutions for Traffic Congestion Management - Case Study. In IEEM 2025 - IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1185-1189). (IEEE International Conference on Industrial Engineering and Engineering Management). https://doi.org/10.1109/IEEM63636.2025.11357742

@inproceedings{5a6d9c0a9a0d4aada1f647e796ed38ee,

title = "Smart Lighting and IoT Integration: Pioneering Solutions for Traffic Congestion Management - Case Study",

abstract = "This study explores the integration of Smart Lighting and IoT technologies to address traffic congestion at drop-off areas of large public facilities. A Traffic Congestion Management System was designed and implemented on a 240-meter-long departure road in Hong Kong. The system utilizes laser-based occupancy sensors for high-accuracy detection, LED signage for dynamic driver guidance, and Power over Ethernet (PoE) technology for simplified installation and energy efficiency. Real-time data communication enables predictive analysis and preventative maintenance, ensuring optimal performance.Preliminary testing showed acceptable accuracy and precision, though a minor 2-4 second delay in LED sign activation was observed. Despite this, the system effectively improves traffic flow, reduces driver confusion, and minimizes delays. This study demonstrates the potential of Smart Lighting and IoT in traffic management and highlights opportunities for future research in Smart City applications.",

keywords = "IoT, Smart Sensor, Traffic congestion",

author = "Lam, \{S. K.\} and Chan, \{Y. K.\} and Lee, \{C. C.\} and Tang, \{W. F.\} and Mak, \{S. L.\} and Tsang, \{K. W.\} and Y. Wang and Zhaobin Li",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2025 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2025 ; Conference date: 07-12-2025 Through 10-12-2025",

year = "2025",

doi = "10.1109/IEEM63636.2025.11357742",

language = "English",

series = "IEEE International Conference on Industrial Engineering and Engineering Management",

pages = "1185--1189",

booktitle = "IEEM 2025 - IEEE International Conference on Industrial Engineering and Engineering Management",

}

Lam, SK, Chan, YK, Lee, CC , Tang, WF, Mak, SL, Tsang, KW, Wang, Y & Li, Z 2025, Smart Lighting and IoT Integration: Pioneering Solutions for Traffic Congestion Management - Case Study. in IEEM 2025 - IEEE International Conference on Industrial Engineering and Engineering Management. IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1185-1189, 2025 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2025, Melbourne, Australia, 7/12/25. https://doi.org/10.1109/IEEM63636.2025.11357742

Smart Lighting and IoT Integration: Pioneering Solutions for Traffic Congestion Management - Case Study. / Lam, S. K.; Chan, Y. K.; Lee, C. C. et al.
IEEM 2025 - IEEE International Conference on Industrial Engineering and Engineering Management. 2025. p. 1185-1189 (IEEE International Conference on Industrial Engineering and Engineering Management).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Smart Lighting and IoT Integration

T2 - 2025 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2025

AU - Lam, S. K.

AU - Chan, Y. K.

AU - Lee, C. C.

AU - Tang, W. F.

AU - Mak, S. L.

AU - Tsang, K. W.

AU - Wang, Y.

AU - Li, Zhaobin

PY - 2025

Y1 - 2025

N2 - This study explores the integration of Smart Lighting and IoT technologies to address traffic congestion at drop-off areas of large public facilities. A Traffic Congestion Management System was designed and implemented on a 240-meter-long departure road in Hong Kong. The system utilizes laser-based occupancy sensors for high-accuracy detection, LED signage for dynamic driver guidance, and Power over Ethernet (PoE) technology for simplified installation and energy efficiency. Real-time data communication enables predictive analysis and preventative maintenance, ensuring optimal performance.Preliminary testing showed acceptable accuracy and precision, though a minor 2-4 second delay in LED sign activation was observed. Despite this, the system effectively improves traffic flow, reduces driver confusion, and minimizes delays. This study demonstrates the potential of Smart Lighting and IoT in traffic management and highlights opportunities for future research in Smart City applications.

AB - This study explores the integration of Smart Lighting and IoT technologies to address traffic congestion at drop-off areas of large public facilities. A Traffic Congestion Management System was designed and implemented on a 240-meter-long departure road in Hong Kong. The system utilizes laser-based occupancy sensors for high-accuracy detection, LED signage for dynamic driver guidance, and Power over Ethernet (PoE) technology for simplified installation and energy efficiency. Real-time data communication enables predictive analysis and preventative maintenance, ensuring optimal performance.Preliminary testing showed acceptable accuracy and precision, though a minor 2-4 second delay in LED sign activation was observed. Despite this, the system effectively improves traffic flow, reduces driver confusion, and minimizes delays. This study demonstrates the potential of Smart Lighting and IoT in traffic management and highlights opportunities for future research in Smart City applications.

KW - IoT

KW - Smart Sensor

KW - Traffic congestion

UR - https://www.scopus.com/pages/publications/105033913627

U2 - 10.1109/IEEM63636.2025.11357742

DO - 10.1109/IEEM63636.2025.11357742

M3 - Conference contribution

AN - SCOPUS:105033913627

T3 - IEEE International Conference on Industrial Engineering and Engineering Management

SP - 1185

EP - 1189

BT - IEEM 2025 - IEEE International Conference on Industrial Engineering and Engineering Management

Y2 - 7 December 2025 through 10 December 2025

ER -

Lam SK, Chan YK, Lee CC , Tang WF, Mak SL, Tsang KW et al. Smart Lighting and IoT Integration: Pioneering Solutions for Traffic Congestion Management - Case Study. In IEEM 2025 - IEEE International Conference on Industrial Engineering and Engineering Management. 2025. p. 1185-1189. (IEEE International Conference on Industrial Engineering and Engineering Management). doi: 10.1109/IEEM63636.2025.11357742

Smart Lighting and IoT Integration: Pioneering Solutions for Traffic Congestion Management - Case Study

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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