# Open Radio Access Networks For Smart IoT Systems: State of Art and Future Directions
## 3 O-RAN in Smart IoT Systems
### Smart Manufacturing Systems  
Smart manufacturing applies cutting-edge technology that uses Internet-connected equipment to increase production efficiency and track processes by employing computer controls, modeling, big data, and other automation [15]. The Industrial Internet of Things (IIoT) has specific applications, one of which is smart manufacturing. The IIoT aims to increase the reachability, effectiveness, and decision making in industrial control systems (ICS). It also offers intelligent functions, including energy consumption monitoring, environmental release management, and general safety and security for the ICS network. ICSs are hardware and software-based systems that monitor and manage industrial activities. The networking hardware and protocols that serve the ICS are known as operational technologies (OT). Supervisory control and data acquisition (SCADA), plant distribution control systems (DCSs), as well as programmable logic controllers (PLCs) are some of the common examples of OT employed in ICS [77]. This entails integrating inter-connected IoT devices, technologies, and principles in industrial settings to improve operational efficiency, optimize processes, and enhance productivity. The smart manufacturing system leverages sensors, devices, and intelligent systems to connect and collect data from various industrial assets, machines, and equipment, enabling real-time monitoring, control of environmental activities, analysis, and automation. From the 5G era and beyond, the smart manufacturing system targets improving seamless connectivity, ultra-reliable communication, high data rate, low latency, efficient data processing, and optimal resource allocation for various industrial applications, for example, industrial automation and remote robotics, where minimal transmission latency is the principal objective, video surveillance for real-time monitoring of industrial assets where high-speed data rates are targeted, and industrial assets tracking, where massive machine connectivity is preferred, among others [78; 79; 80]. O-RAN will build on 5G's intervention to yield open, scalable, resilient, cost-effective solutions that lead to a more efficient, productive, resilient, and sustainable industrial setting. This can be achieved in several ways. For example, [PERSON] et al. [67] conducted a _\"SWOT Analysis\"_ to determine O-RAN's areas of strengths that could be leveraged to support the next-generation smart manufacturing applications in satisfying their seamless connectivity requirements. [PERSON] et al. [81] proposed _\"zero-touch\"_ architecture to connect the diverse components of a smart factory together. The RIC was used to control the connectivity using AI/ML in a distributed passion. [PERSON] et al. [34] proposed a flexible and scalable method of slicing the IIoT network in RIC while considering the diverse QoS requirements and the available resources within the network. Their approach reduces the problem's complexity by employing distributed game theory to match each slice to its corresponding cell base stations and then applying actor-critic learning to achieve an optimum resource allocation that facilitates IIoT monitoring and control. [PERSON] et al. [65] proposed an xApp that examines the control plane messages to detect malicious threats targeting IIoT devices. [PERSON] et al. [66] presented IIoT data security as critical for effectively monitoring and controlling the ecosystem, thereby examining O-RAN's readiness towards ensuring the privacy and security of the data. **Takeaways from smart manufacturing systems:** As supported by Table 3, the reviewed efforts in smart manufacturing systems covered \(Y_{1}\), \(Y_{2}\), and \(Y_{3}\) while \(Y_{4}\) still needs further exploration.