## 4 Progress of Data Processing Modules for Solar PV Monitoring System
### Raspberry Pi-Based Module  
The Raspberry Pi module is a single-board computer with a low-cost package [33,55]. It is a device similar to a fully functional computer manufactured on a single printed circuit board. The size of Raspberry Pi is as small as a credit card but it has the capability of performing a task similar to a computer [56]. The Linux operating system is used to operate Raspberry Pi [57]. The ARM-based CPU embedded in Raspberry Pi draws less power which eliminates the need for a heat sink [58]. The easy-to-use module of Raspberry Pi can be utilized for enabling wireless technology [59] and Arduino interaction [60]. Moreover, many variants of the operating system are supported by Raspberry Pi which only requires power to boot [61]. Due to its numerous advantages stated above, Raspberry Pi modules are now used in real-time monitoring schemes. [PERSON] et al. developed a multi-user remote system-based Renewable Energy Monitoring System (REMS) using Raspberry Pi and the internet of things (IoT) concept as depicted in Figure 7[62]. The REMS was updated by the Analogue Digital Converter Embedded System (ADCES) and the communication was established in Linux and cloud server profiles. The REMS server and online server database had a storage capacity of 84.44 MB and 2 GB, respectively. The data was stored at 1 sample/minute with the size of 150 bytes for 391 days. The experiment was performed on a 50 W load with the following specifications: model YL95P-17b 2/3, a maximum power of 95 Wp, 14.3% efficiency, an open-circuit voltage (Voc) of 22.5 V, and a short circuit current (Isc) of 5.59 A. The developed architecture did not have to unlock ports and/or firewall when using the multi-user cloud service. It was proposed that cryptography to secure data storage and database confidentiality should be implemented. The proposed model could be modified to record data from other types of analog or digital sensors as well as for other types of applications using renewable sources. In addition, the utilization of programming languages such as Basic C language and Linux is preferred. The work by the authors in [35] proposed a Raspberry Pi-based solar PV monitoring system at the module level using the IEC 61724 standard as presented in Figure 8[35]. The monitoring was performed at the module level which gave detailed information about the solar PV plant performance. The system not only monitors the electrical and environmental data, but it also evaluates PV module performance and identifies any abnormal behaviors. The variable parameters of the solar PV were monitored under the environment of LABVIEW. The design was implemented with a 5 kW solar PV consisting of 18 PV modules where each module had a capacity of 310 Wp. The results showed that the error rate was estimated to be less than 2%. The introduced design could be altered to store the data on the cloud/internet for future reference so it can be accessed easily. Figure 7: The block diagram of Raspberry Pi and IoT-based REMS. [PERSON] and [PERSON] [63] designed a cloud-based Raspberry Pi system for solar PV monitoring consisting of four thermocouples connected to the ADAFRUIT MAX31855 processor. Data recorded by the Raspberry Pi were transferred to the cloud system. It was proposed that technological implementation can assist in lowering the fatigue at the panels which could be easily detectable when any fatigue condition occurs. The methodology could be improved by the inclusion of a cryptographic method to secure the data comprehensively. [PERSON] et al. [64] established a system with a Raspberry Pi3 card for the monitoring of a remote solar PV system using Bluetooth and Wi-Fi modules. Bluetooth protocol was implemented by transferring the data from the sensors to the Raspberry Pi module. Wi-Fi protocol was used to transfer data from the gateway to the supervision machine/cloud. The comparative analysis among different Raspberry Pi modules confirmed the superiority of the Raspberry Pi3 module over other modules.