Challenges and Solutions of IoT-Enabled Traffic Surveillance Systems: A Comprehensive Survey
Year: 2025
Type: article
Abstract: The demand for effective traffic management solutions has increased due to the fast urbanization and rising vehicle density. IoT-enabled traffic surveillance systems have become a viable way to improve road safety, traffic monitoring, and congestion management. Data security, real-time processing constraints, interoperability problems, and high deployment costs are just a few of the major obstacles these systems must overcome. This survey examines various remedies and offers a thorough examination of these issues. We look at important approaches including 5G-enabled communication frameworks, edge computing, blockchain for safe data sharing, and analytics powered by artificial intelligence. We also evaluate new developments and industry best practices that improve the dependability and effectiveness of IoT-based traffic monitoring. Our results emphasize how crucial it is to combine secure communication protocols with sophisticated data processing methods in order to overcome current constraints. The purpose of this study is to help policymakers and researchers create IoT-driven traffic control solutions that are more reliable and scalable.
Authors: Komal Patel, Keta Patel
Institution: Sankalchand Patel University
Language: English
Topic: IoT and Edge/Fog Computing
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4411968362