# Connected Vehicles: Technology Review, State of the Art, Challenges and Opportunities
## 5 Opportunities  
In recent years, the automotive sector has witnessed rapid growth, innovations, and many technological advancements that have been targeting connected and autonomous vehicle technologies. Many opportunities lie ahead to further enhance and develop different aspects of this technology. CVs incorporate many technologies, and, hence, many opportunities can be envisioned in various aspects of CVs. For instance, innovative solutions for developing and increasing the efficiency of cloud platforms are considered a necessity to gain better insights from the huge amount of data that are produced in the CV environments. Moreover, with the high safety level that CVs provide, equal research opportunities towards innovative applications and services are widely open. One of the promising applications is the shift towards smartphone applications to assist in some of the functionalities of the vehicles. This provides more business opportunities for both automotive and telecommunication companies. Additionally, smart commercialization is today's new market sales tactics where stores, restaurants, and many industrial companies turn to digital commercialization instead of the traditional means in advertising their products and offers. Therefore, utilizing the data dissemination between vehicles for sending offers to drivers and using vehicles as an advertising platform will provide equal profit, opportunities, and revenues for the advertised party, since monetizing data in accordance to the driver's preferences to provide the most convenient services and advertisements are considered promising. Voice-recognition technologies incorporated with modern vehicles are an integral part of the in-vehicle dashboards to help drivers use their voices instead of being distracted by other means, such as texting. Even though in-vehicle voice-control-assistant technology is envisioned with various applications that assist drivers to fully interact with the vehicle to access information, such as emails or map directions by speech, many innovative voice applications are foreseen to further dominate. Hence, they will increase the safety level for drivers by keeping their eyes focused on the roadway. Machine learning algorithms and data analytics can also learn about the driver's preferences and daily routines to offer \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Challenges** & **Potential Research** & **State-of-the-Art Technology** & **References** \\ \hline Integration of communication and computation & Vehicular cloud computing with resource management problems & Vehicular mobile edge computing & [97; 128; 129; 130; 131; 132] \\ \hline Over the Air (OTA) & Methodologies and techniques to decrease the OTA update duration time & Server/client & [133; 134; 135; 136] \\ \hline Privacy and security & Need for lightweight and low overhead privacy and security algorithms & Blockchain technology & [139; 140; 141; 142; 143; 144; 145] \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of the challenges in CV technology. a more personalized driving experience. Therefore, they open up new possibilities and opportunities for unique and customized applications and services. Cooperative perception is foreseen as a potential approach that overcomes and improves the sensing-based technology limitations of CVs by allowing vehicles to exchange their local raw or processed sensor information via V2V communication to improve their visibility and field of vision. In a dense environment, vehicles may redundantly transmit the same perceived data to nearby vehicles, which results in a reduction in V2V communication reliability, inefficient use of network resources, and high network loads that lead to emergency data or critical information being lost or delayed and hence jeopardizing road safety [149; 150]. Developing intelligent schemes to mitigate redundant data and improve network loads and scalability while utilizing network resources efficiently are promising research directions.