# Open Radio Access Networks For Smart IoT Systems: State of Art and Future Directions
## 3 O-RAN in Smart IoT Systems
### Smart Transportation Systems  
The smart transportation system leverages advanced information communication technologies (ICT) to enhance transportation systems' safety, efficiency, reliability, and sustainability. It integrates sensors, communication systems, data analytics, and control systems to collect and process data, providing real-time decisions, and optimize transportation operations. Nowadays, the smart transportation system is used to support the automatic control of vehicles, monitor traffic conditions, handle traffic flow, provide real-time information updates to drivers, reduce environmental pollution, and even improve air quality. With the advent of 5G, the next-generation smart transportation system aims to improve  
Figure 3: Problem space. road safety, traffic efficiency, environmental sustainability, and user experience through enhanced communication and data-driven technologies [69]. Just like the _\"ultra-reliable and low-latency communication (URLLC)\"_ capabilities to support real-time applications like autonomous driving, improving the reliability, range, and capacity of V2X communication promotes better coordination among road users [70]. The _\"enhanced mobile broadband (emBB)\"_ applications like in-vehicle entertainment and infotainments require high-quality multimedia streaming, augmented reality navigation, and other entertainment services to passengers in moving vehicles [71]. The _\"massive machine type communication (mMTC)\"_ enables more effective traffic management and congestion reduction strategies using dynamic traffic signal control, adaptive routing, and predictive traffic flow analysis, etc. [72; 73]. At the same time, O-RAN could build on that to promote automation, interoperability, and cost-efficiency in the next-generation ITS by enhancing vehicular communication optimization, traffic management and control, cooperative autonomous driving, etc. For example, [PERSON] et al. [63] presented an improved edge intelligence supporting IoV networks. [PERSON] et al. [74] leveraged the O-RAN concept to implement a centralized training but distributed execution (CTDE) strategy to enable cooperation among diverging agents operating in vehicular networks. In this manner, they addressed the resource allocation problem of V2V and V2I while satisfying their reliability and QoS requirements. Likewise, [PERSON] et al. [64] used the NRT-RIC to create a collaboration area in a network of multiple radios and edges. Their approach can balance computation and communication, translating to a latency reduction in autonomous vehicles network [75]. [PERSON] et al. [76] utilized the RIC to control the proposed fuzzy-based routing protocol. The RIC handles the dynamic network topology and arrives at the optimum traffic route by generating and maintaining the link state database, which guides the multi-hop peer-to-peer (P2P) communication. [PERSON] et al. [60] presented O-RAN as a promising enabler of the next-generation vehicular communication orchestration, together with open research considerations militating against integrating the two technologies. V2X resource allocation, beam selection, relay assignment, and network DTs are among the feasible research directions in their work. **Takeaways from smart transportation systems:** Supported by Table 2, the reviewed efforts in smart transportation covered \(Y_{1}\) and \(Y_{2}\), while \(Y_{3}\) and \(Y_{4}\) are less explored. However, despite O-RAN's achievements in smart transportation, there is a need for smart-transportation-compatible specifications, standards, and tools facilitating the development of robust, secure, energy-efficient, adaptive solutions that operate in real life.