Modeling and optimizing IoT-driven autonomous vehicle transportation systems using intelligent multimedia sensors

With the rapid development of the Internet of Things (IoT) communication system, a huge number of devices are interconnected to sense the unpredictable environment. These systems are needed to manage a lot of varied data in addition to facilitating human lives. With the use of sensors, vehicles exchange multimedia data in smart transportation applications and subsequently give useful information to the road. Many approaches have been proposed to overcome the route optimization problems in improving the transportation system, but a major study is still needed to address intelligence in the context of autonomous processing with lower route reconstruction. Data privacy and the assurance of its integrity are also crucial components of the transportation system since vehicles use next-generation technology to carry roadway information. To cope with vehicle communication through unreliable wireless infrastructure and effectively use the resources of the communication model, this work proposed a smart vehicular algorithm employing an IoT system (SVA-IoT). Firstly, it guarantees the reliability of the intelligent transportation system (ITS) with heuristic computing and decreases the overhead on the devices. Second, route optimization is carried out to balance the load on parallel routes while transmitting highway information, as a result, it increases the intelligence of smart vehicle systems. In the end, authentic devices are identified to establish a secure and trusted communication structure. The proposed technique is tested through a variety of simulated experiments, and the findings show considerable improvement over existing work.