# Artificial Intelligence of Things for Solar Energy Monitoring and Control
## 3 AIoT Applications in PV Systems: A Comprehensive Review
### Applications of IoT in PV Systems
#### 3.2.1 Solar Monitoring Systems  
Solar monitoring systems track real-time data from PV systems, such as solar irradiance, temperature, and power output, to optimize performance. By identifying issues and predicting maintenance needs, these systems ensure efficient and reliable solar energy production. IoT integration enables remote monitoring and proactive maintenance. Several studies focus on IoT-based monitoring and control of solar PV systems. In 2020, [PERSON] and [PERSON] [127] proposed an IoT system that automatically monitors and controls parameters such as voltage, current, and power consumption, sending real-time data to users. The authors enabled users to monitor and control solar panels via their mobile devices, providing an efficient way for users to manage their systems remotely. Also, [PERSON] et al. [128] present a low-cost, open-source SCADA system for monitoring and remote control of solar PV systems, based on IoT architecture. It uses analog current and voltage sensors for data acquisition, an Arduino Uno microcontroller for data reception, and a Raspberry Pi with Node-RED for data parsing. The system stores and monitors data using the Emoncms IoT platform. The developed SCADA system was tested on a 260W solar PV panel, and its data are accessible via dashboards on a cloud server, allowing monitoring through both a computer and a mobile app. [PERSON] et al. [129] propose in their paper an IoT-based solar metering system designed for remote monitoring and analysis of solar setups. The system allows real-time monitoring of solar output, enabling quick identification of any interruptions. It is particularly suitable for remote areas where solar energy is abundant but access is limited and cost-prohibitive. The system uses a Raspberry Pi, MCP3008 (Analog to Digital Converter), DC Voltage Transducer, and a current shunt. The system is developed using the Virtual Instrument Programming Language (LabVIEW), providing an efficient solution for monitoring and managing solar power in remote locations. In 2021, [PERSON] et al. also [130] presented a low-cost, IoT-based data acquisition system (DAQ) for PV monitoring, designed to withstand harsh environmental conditions. Tested over 28 days, the system effectively gathers operational data, detectsperformance degradation, and features Wi-Fi-controlled switches for remote operation, reducing energy consumption by 58%. The study also highlights a 13% decline in PV module output due to dust accumulation, emphasizing the importance of maintenance. Furthermore, [PERSON] et al. [131] propose a Renewable Energy Monitoring System (REMS), which is a real-time cloud monitoring solution for decentralized PV plants. It utilizes Raspberry Pi and IoT technologies to measure PV voltage, current, module and ambient temperature, solar irradiance, and humidity. REMS features remote firmware updates via a custom Analog/Digital Converter Embedded System and communicates with a tailored cloud server using an RPi Embedded Linux System, eliminating the need for a dedicated PC. [PERSON] et al. [132] propose an IoT-based architecture for real-time monitoring and management of large-scale solar PV systems. The system enables remote control and monitoring of solar plants while assessing environmental factors like weather, air quality, and soiling. It uses MQTT for efficient, wide-scale communication with minimal network delay (under 1 s) and low resource consumption (around 3% of the panel's output). The evaluation concludes that this architecture is ideal for deployment with low-cost edge devices, offering a scalable, cost-effective solution for solar and smart grid monitoring systems. Using MQTT and Modbus, [PERSON] et al. [133] focus on their project on using solar power to operate an agricultural motor pump. A Variable Frequency Drive (VFD) controls the motor pump, with solar power as the input to the VFD. The project also involves developing a Remote Monitoring System (RMS) that reads data from the VFD controller, including solar power and motor pump values.