Car congestion is a pressing issue for everyone on the planet. Car congestion can be caused by accidents, traffic lights, rapid accelerations, deceleration, and hesitation of drivers, as well as a small low-carrying capacity road without bridges. Increasing road width and constructing roundabouts and bridges are solutions to car congestion, but the cost is significant. TLR (traffic light recognition) reduces accidents and traffic congestion caused by traffic lights (TLs). Image processing with convolutional neural network (CNN) lakes dealing with harsh weather. A semi-automatic annotation for traffic light detection employs a global navigation satellite system, raising the cost of automobiles. Data was not collected in harsh conditions, and tracking was not supported. Integrated channel feature tracking (ICFT) combines detection and tracking, but it does not support sharing information with neighbors. This study used vehicular ad-hoc networks (VANETs) for VANET traffic light recognition (VTLR). Information exchange as well as monitoring of the TL status, time remaining before a change, and recommended speeds are supported. Based on testing, it has been determined that VTLR performs better than semi-automatic annotation, image processing with CNN, and ICFT in terms of delay, success ratio, and the number of detections per second.
Vehicular ad-hoc networks (VANETs) address a steadily expanding demand, particularly for public emergency applications. Real-time localization of destination vehicles is important for determining the route to deliver messages. Existing location administration services in VANETs are classified as flooding-based, flat-based, and geographic-based location services. Existing localization techniques suffer from network disconnection and overloading because of 5G VANET topology changes. 5G VANETs have low delay and support time-sensitive applications. A traffic light-inspired location service (TLILS) is proposed to manage localization inspired by traffic lights. The proposed optimized localization service uses roadside units (RSUs) as location servers. RSUs with the maximum traffic weight metrics were chosen. Traffic weight metrics are based on speed of vehicles, connection time and density of neighboring vehicles. The proposed TLILS outperforms both Name-ID Hybrid Routing (NIHR) and Zoom-Out Geographic Location Service (ZGLS) for packet delivery ratio (PDR) and delay. TLILSs guarantee the highest PDR (0.96) and the shortest end-to-end delay (0.001 s) over NIHR and ZGLS.
Every person in the world needs documents that prove their identity, graduation from the university, residence, marriage, and other essential records that must be safely handled. The credibility of the documents depends on the stamp seal imprints found in them belonging to the government entity, the source of the credibility. But recently, with the rapid development of technology, the number of forged documents and forged stamp seals imprints has increased tremendously, which has led to significant security and social problems. Most of the world's governments depend on securing documents by securing stamp seal imprints through using Ultra Violets inks and issuing them through a centralized environment, which contains many challenges and problems. Central repositories may have security issues such as a single point of failure challenge, data unavailability due to central system failures, or a Denial of Service (DoS) attack. Therefore, this paper will present a proposal that solves the challenges in electronic systems (complete digitalization) and paper systems (partial digitalization). This manuscript proposes a smart securing model to secure stamp seal imprints by encrypting data with stamp seal image of the seal and storing it as a block through the decentralized Blockchain platform. After that, a quick response code (QR) is created to access that block quickly and securely. Also, the stamp seal's hash image and the details of the stamp seal's data source in the blockchain provide a shared, immutable, and transparent history of the stamp seals without relying on any third party. After several experiments, the results proved an accuracy and security rate of stamp seals and documents that reached 98%, with a high retrieval speed. Thus, a safe, fast, and non-changeable environment was provided to retrieve necessary information and ensure its authenticity.
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