# Harnessing the Cloud: A Novel Approach to Smart Solar Plant Monitoring
## 4 Our Proposed Architecture for Smart Solar Plant
### Edge Layer  
The edge layer is an intermediate level employed for real-time analysis and big data management. Being an example of distributed computing, it is intended to complement cloud computing rather than substitute it. The end devices (integrated with solar panels, inverters, and batteries) will produce voluminous data for data analysis and predictive fault diagnostics. The idea of the edge layer is to process raw data in order to reduce the volume of data transmitted to the cloud platform, thus resulting in reduced data bandwidth requirements and transmission costs. Furthermore, for historical performance analysis, solar plants' performance parameters are stored to generate periodic reports. Therefore, the problem of logging huge amounts of data has to be taken into consideration in the architecture paradigm design [53]. In the existing literature, RPi has emerged as the most optimum choice for gateway (edge/fog nodes) devices, as presented in Tables 2 and 3. RPi is a credit card-sized single-board computer offering approximately the same functionalities as that of a desktop computer [17]. It is relatively cheaper and easier to operate, as well as supporting various operating systems. It is used extensively in automation and IoT projects because of its ease of operation and built-in support for communication technologies such as Bluetooth and Wi-Fi. For overall cost optimization, the meteorological sensors should be integrated at the edge nodes only, as presented in Figure 5.  
In the existing literature, various wireless communication technologies have been employed for data transmission to remote servers. These technologies range from LoRA [4; 43], LoRaWAN [50], RF [9; 16; 39], and Wi-Fi [3; 7; 14; 20; 21; 42; 45; 46; 47; 48]. However, to reduce network complexity and the ubiquitous presence of cellular towers in remote locations, GSM technology (SIM900) is the most optimum solution for edge nodes. The deciding factor for this choice is based on the range it offers, as solar plants are mostly located in isolated and remote regions. Furthermore, cellular networks offer long-range, affordable, reliable, and scalable data transmission networks. For example, in South Asia, a 6000 MB internet data package is available for USD 5 [52]. In this regard, SIM900 [8; 15; 30; 51] can be employed for intercommunication between edge nodes and requisti  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Modules** & **Cost (USD)** & **Current Consumption (mA)** \\ \hline Arduino Nano & 20 & 19 mA \\ \hline ACS/12 & 1 & 0.05 W \\ \hline Voltage & 1 & \\ \hline LM35 & 3 & 0.24 mW–1.8 mW \\ \hline Total & 25 & \\ \hline \hline \end{tabular}
\end{table}
Table 6: Cost and current consumption of proposed edge device.  
Figure 4: Our proposed system-level architecture is composed of end devices (sensors and a compute board). The data from the end devices are transmitted to the edge layer (fog node) via Bluetooth. The edge layer consists of a few meteorological sensors and communication technology for sending the data to the cloud for further processing.