The transportation system has gained substantial growth due to the increase in urban population and growing business demand. Increasing freight mobility and passenger transit have led to anonymous traffic congestion, thereby shooting up worldwide pollution. Managing pollution levels has become the utter priority to reduce the anthropogenic effects on the environment. The transportation industry is aiding to implement an Intelligent transportation system that derives efficiency in operations by cutting down the vehicular emissions. The main thrust of an intelligent system is to improve the safety of transportation, effectively manage incidents, and minimize environmental impact by using leading-edge information and communication technologies. Its adoption has key beneficiaries in applications such as traffic light cameras, electronic toll collection, ramp meters, and traveller information systems. Advancement in digitalization and the need for real-time environmental monitoring to combat earth pollution has led to the incorporation of IoT into the transportation system. IoT-based intelligent systems help automate roadways, airways, railways, and marine, which optimizes the movement of goods and improves environmental safety by computing real-time sensor data. These smart devices are deployed in various areas within the transportation sector, notably in telematics systems, traffic congestion systems, security, and surveillance. Convectional ITS systems deploy well-versed techniques to automate the transportation sector that enables optimized routing systems but still, it cannot be used to predict the real-time routing directions, which is very much needed to maintain competence in today’s logistics systems and deal with tremendous pollution that is being produced due to stupendous use of transport systems.
IoT-based Intelligent transportation system incorporates sensors and monitoring system to connect vehicle location that assist in managing traffic system effectively. Routing algorithm integrated with transportation systems is used to detect the current location and destination to draw the optimized pollution route according to the recorded pollution levels and their effect on ongoing city pollution levels. Fuzzy-based systems and VANET helps in minimizing the vehicle count in a specific area by analyzing the traffic condition based on parameters like vehicle speed and traffic volume. This system reroutes the vehicles to reach their destination without collision, thereby reducing emissions being produced in the highly congested areas. There exist some potential drawbacks in the usage of IoT technology for current operating systems. Security is the major drawback that cannot be overlooked as massive data attack occurs due to cybercriminals targeting IoT devices. Integration of more IoT devices in a single network leads to vulnerability of the network. As IoT devices use multiple sensors, it is a stumbling block for organizations to manage onboarding. In the future, energy-efficient mechanisms can be integrated with the ITS system, and the system efficiency could be made more reliable for handling the ongoing road scenario. Using conjoint analysis, the ITS system can provide uninterrupted travel, which delivers a safe journey without congestion and controlled emissions. IoT devices can leverage data for analysis by implementing a robust cloud system that prevents leakage of data. This special issue enumerates the role of IoT devices in limiting environmental pollution through the proliferation of Intelligent transportation systems and future advancements. We welcome scholars and practitioners of this platform to develop a data security cloud model that provides data protection in the IoT enables ITS system through processing encryption and present submissions that fall under the umbrella of big data technologies and secured wireless communications technologies to enable connected vehicles that prevent congestion and control the emissions that cause environmental pollution.
The topic of interest includes, but is not limited to the following:
- Intelligent vehicle monitoring and assistance using cloud technologies
- A collision avoidance system for emergency traffic situations.
- Role of Big data and Hadoop technologies for seamless communications
- Predictive methodology for accurate analysis of vehicular connected data
- A traffic optimization model using IoT for transportation system
- Artificial intelligence for measuring pollution levels and efficient monitoring
- Use of energy efficiency indicator to control energy usage in vehicles.
- Deep learning techniques to manage transportation collisions.
- Role of an automatic identification system in tracking traffic-congested areas.
- A brief note: Cloud-based pollution tracking and monitoring system.
