## 3 Digitalization for BIPV  
Currently, the digitalization of any field is achieved with the assistance of emerging technologies such as IoT, AI, edge computing, UAVs, and drones. The adoption of digital technologies empowers us to create value from new, advanced technologies by exploiting digital network dynamics and the giant digital flow of information. The implementation of digitalization in the BIPV system improves the system performance by establishing automation and a digital network. 1. **IoT:** IoT was first proposed at the end of the twentieth century, and it was developed using radiofrequency technology [20; 21]. The GSMA estimates that the number of IoT connections will reach 25 billion worldwide by 2025 [22; 23]. IoT is a collection of devices with embedded systems connected to the internet's telecommunications network with the ability to generate and send data without the need for human  
Figure 4: Different layers of the encapsulated STPV modules [18]. interaction. IoT consists of machine-to-machine (M2M) networks, in which intelligent devices communicate with one another and make independent decisions based on created and transmitted data [24; 25]. Figure 5 illustrates the IoT-based architecture that is discussed in [26], which comprises four-layers, namely, the perception layer, network layer, cloud computing layer, and application layer. The perception layer is part of IoT architecture, as it is the primary layer for obtaining the data of physical things through sensors, radio frequency identification (RFID), actuators, and camera modules. The different sensors that are suitable for the BIPV system are presented in Table 1. The network layer comprises different wireless communication modules that establish the network with the cloud server. Figure 5: IoT architecture. During the implementation of the IoT network, the wireless communication protocol plays a vital role in connecting the perception layer to the network layer and also in controlling and monitoring [27]. Currently, different wireless communication protocols are used to establish IoT networks as shown in the Table 2. Sigfox, Narrowband IoT (NB-IoT), and LoRa are the wireless communication protocols that establish the low power wide area network (LPWAN) between the perception layer and network layer [28]. These communication protocols are capable of communicating the sensory data over a long range with minimum energy consumption. The previous studies concluded that the LoRa is preferred over Sigfox and NB-IoT in building applications due to the following aspects: long battery life, bi-directional communication, large-scale deployment, and mobility [29]. Bluetooth low energy (BLE) and Zigbee are low-power communication protocols that transmit short-range data. Along with this, wireless fidelity (Wi-Fi) is the communication protocol that enables the perception layer to connect directly over the internet. MQTT (message query telemetry transit) is a machine-to-machine network protocol that is lightweight and publish/subscribe. It is built for communications with remote sites that have limited network bandwidth or devices with resource limits. 2. **AI:** AI is the process of creating intelligent devices out of massive amounts of data [31]. Human-like tasks are performed by systems that learn from previous learning and experiences. Human efforts are improved in terms of speed, precision, and efficacy. To create machines that can make judgments on their own, AI uses complicated algorithms and methodologies. Figure 6 illustrates the subsets of AI, and they are machine learning (ML), deep learning (DL), expert systems, natural language processing (NLP), robotics, vision, and speech recognition [32]. ML is a branch of AI that offers intelligence to computers by allowing them to learn from their experiences without being explicitly programmed [33].