## 5 Future Directions and Research Challenges
In this context, the 6G network and fog computing play a significant role in executing intelligent learning techniques to execute complex computations such as assessing aging properties, soiling effects, fault detection, detection of shading, etc., and transforming the user experience to the near real-time response [70]. The focus of communication will shift from ubiquitous connectivity to intelligent and automated connectivity. In addition to this, fog computing is crucial for the 6G implementation, as fog computing provides effective computation and storage [71]. The fog nodes assist the 6G in enabling ubiquitous connectivity and achieving extremely low latency. * **Edge computing integration in UAV for intelligent automation and detection** The UAV is employed to capture visual data on heights or in the air. The captured data is communicated to the edge device on the ground level, this indeed increases the infrastructure. To overcome this challenge, edge computing technology can be integrated into UAVs to analyze and compute the data gathered from the installed BIPV system through the inbuilt camera, sensors, and AI/ML algorithms [72; 73]. The UAV minimizes the processing time and energy required for operating the whole process. In addition to this, UAVs have been integrated as air-ground equipment to meet the processing and storage requirements at IoT network edges because they provide low latency support for latency-sensitive applications, improve the scalability of massive mobile connectivity, and ease the distribution of big data analysis [73]. The combination of UAV-enabled edge computing with blockchain structure boosts security because the blockchain is a distributed ledger that allows UAVs to record their data as a transaction in a chain of blocks in an immutable, secure, and transparent [74]. This is a promising option for addressing the security and privacy concerns associated with UAV networks. * **Augmented Reality, Virtual Reality, and Digital Twins for virtual BIPV system** Augmented reality, virtual reality, and digital twins are rapidly emerging technologies that facilitate the linking of physical and virtual worlds in real-time, delivering a more real and holistic analysis of unplanned and unpredictable events [75; 76]. The implementation of these technologies in the BIPV system empowers virtual visualization of the system before its installation in real-time. In addition to this, the performance of PV panels can be predicted, and can also visualize preventative measurements to avoid the further degradation of panels. **Research challenges**
* The implementation of AI in edge computing has significant advantages, along with a few challenges that require the focus of researchers, such as computational power, memory, security, and power management of the edge devices. In the area of BIPV, the energy generated by the edge devices will be based on renewable energy, however, the life of edge devices concerning the performance of computational activities is challenging because the replacement of edge devices within a short period also increases the infrastructure and adds another operating cost. * Along with the life of the edge devices, another significant parameter that needs to be considered is the security and privacy of the data. In the context of the BIPV, the building structure data, and the panel details with location are shared on the edge network. The data is comprised during transmission from the edge to the cloud server. Recently, blockchain has been integrated with edge computing to achieve secure authentication and collaboration with trusted distributers [77; 78]. * To perform the high computational activities with AI, there is a need for additional computational hardware and this hardware consumes a lot of energy to perform the computational activities [79].