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Intelligent transportation systems (ITSs) derive significant advantages from advanced models like YOLOv8, which excel in predicting traffic incidents in dynamic urban environments. Roboflow plays a crucial role in organizing and preparing image data essential for computer vision models. Initially, a dataset of 1000 images is utilized for training, with an additional 500 images reserved for validation purposes. Subsequently, the Deep Simple Online and Real-time Tracking (Deep-SORT) algorithm enhances scene analyses over time, offering continuous monitoring of vehicle behavior. Following this, the YOLOv8 model is deployed to detect specific traffic incidents effectively. By combining YOLOv8 with Deep SORT, urban traffic patterns are accurately detected and analyzed with high precision. The findings demonstrate that YOLOv8 achieves an accuracy of 98.4%, significantly surpassing alternative methodologies. Moreover, the proposed approach exhibits outstanding performance in the recall (97.2%), precision (98.5%), and F1 score (95.7%), underscoring its superior capability in accurate prediction and analyses of traffic incidents with high precision and efficiency. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has significantly altered our way of life, being integrated into many application types. These applications require a certain level of security, which is always a top priority when offering various services. It is particularly difficult to protect the information produced by IoT devices from security threats and protect the exchanged data as they pass through various nodes and gateways. Group Key Management (GKM) is an essential method for controlling the deployment of keys for network access and safe data delivery in such dynamic situations. However, the huge volume of IoT devices and the growing subscriber base present a scalability difficulty that is not addressed by the current IoT authentication techniques based on GKM. Moreover, all GKM models currently in use enable the independence of participants. They only concentrate on dependent symmetrical group keys for each subgroup, which is ineffective for subscriptions with very dynamic behavior. To address these issues, this study proposes a unique Decentralized Lightweight Group Key Management (DLGKM) framework integrated with a Reliable and Secure Multicast Routing Protocol (REMI-DLGKM), which is a reliable and efficient multicast routing system for IoT networks. REMI-DLGKM is a cluster-based routing protocol that qualifies for faster multiplex message distribution within the system. According to simulation results, this protocol is more effective than cutting-edge protocols in terms of end-to-end delay, energy consumption, and packet delivery ratio. The packet delivery ratio of REMI-DLGKM was 99.21%, which is 4.395 higher than other methods, such as SRPL, QMR, and MAODV. The proposed routing protocol can reduce energy consumption in IoT devices by employing effective key management strategies. [ABSTRACT FROM AUTHOR]

Multi-hop Wireless Networks require wireless devices communicating through wireless channels to forward the information from the source to the destination. Therefore, finding an optimal path to route the exchanged data between nodes is a major challenge. In recent years, many researchers are interested in this topic and they are proposing many routing protocols which allow the nodes to learn some multi-hop path to exchange data between them. However, securing these routing protocols is a challenging task due to the various characteristics of the Multi-hop Wireless Networks such as the limited capacity of the nodes and their mobility. Securing a routing protocol is necessary to protect the route discovery phase as well as the data transmission phase against any malicious attacks such as the Man-in-the-middle and the node impersonation. These attacks aim to increase the resource consumption and decrease the quality of services in the networks. In this paper, we propose a secure routing protocol for Multi-hop Wireless Network. The proposed protocol is a tradeoff between the routing performance in terms of throughput, end-to-end delay, the loss rate and the routing security in terms of confidentiality, integrity and authentication. In order to secure the data transmission phase after the routes selection, the nodes of each route contribute in establishing a group key using to encrypt the exchanged data between the source and the destination. Performance evaluation based on Network Simulator 2 (NS-2) and security analysis ensure that the proposed protocol is secure and it improves the routing performance as compared with the Secure Ad Hoc On-Demand Distance Vector (SAODV). [ABSTRACT FROM AUTHOR]