## 4 Opportunities and Open Research Areas in VANET Multimedia
### Artificial Intelligence at the Edge for Automotive Internet of Things  
The integration of Artificial Intelligence (AI) into VANETs for multimedia applications presents a myriad of opportunities, especially in the domain of audio-visual enhanced emergency notification systems. These systems have the potential to assist in capturing, comparing, and making decisions regarding the location of wanted fugitives, as demonstrated in Figure 6. This convergence represents a significant advancement in the automotive Internet of Things ecosystem, leveraging AI at the edge. One prominent application involves utilizing AI algorithms to analyze data captured by roadside cameras, specifically focusing on pedestrian and road user detection [58]. This innovative approach, as detailed in the article by [58], places emphasis on the integration of AI for precise pedestrian detection through camera systems. The researchers underscore the pivotal role of C-V2X communication in this context and highlight how AI-powered camera systems can significantly bolster pedestrian detection capabilities. However, this integration is not without its challenges. One of the primary hurdles lies in the need for robust and real-time AI processing capabilities at the edge. Processing complex multimedia data in real time demands high computational power, which may pose constraints in resource-limited edge devices. Additionally, ensuring the security and privacy of sensitive visual data is of paramount importance, necessitating robust encryption and authentication mechanisms. Furthermore, the seamless integration of AI algorithms with existing VANET infrastructure requires careful calibration and synchronization. The models need to be trained on diverse and representative datasets to ensure accurate and reliable performance across varied real-world scenarios. Additionally, addressing potential as shown in Figure 6, biases in AI algorithms is crucial to ensure the fair and unbiased detection of pedestrians and road users from diverse demographic backgrounds. While the integration of AI into VANETs for multimedia applications offers immense potential, it also presents unique challenges. Overcoming computational limitations, ensuring data security and privacy, and fine-tuning AI models for diverse scenarios are key areas of focus. With diligent research and development  
Figure 6: AI to support multimedia in the automotive Internet of Things. efforts, the convergence of AI and VANETs stands poised to revolutionize transportation safety and efficiency. In the context of VANET, there are opportunities to utilize the information obtained from roadside units (RSUs) along with images captured by roadside cameras, employing AI algorithms to search for wanted persons and wanted license plates. By comparing the information from both RSUs and roadside cameras, the system can contribute to the apprehension of criminals. Another relevant study, presented in [62], introduces an analysis system that assesses the risk level of pedestrian-vehicle interactions using drone videos. The research focuses on leveraging drone technology to capture videos of these interactions and subsequently analyzes them to determine the associated risk level. The authors propose an automated system that extracts pertinent features from the videos and employs machine-learning techniques to classify and evaluate the risk level of each interaction. This research emphasizes the potential of using drone videos and data analysis to enhance pedestrian safety, providing valuable insights into the risk factors inherent in pedestrian-vehicle interactions. Further exploration is needed to investigate how AI can be utilized to compare drone-captured videos with roadside videos and audio-visual received from roadside units within the VANET framework. Such integration of AI capabilities would facilitate the classification and detection of individuals, thus aiding in their swift apprehension within the DSRC emergency notification system.