# 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
The RMS uses MODBUS communication to collect these data and sends them to a web server using the MQTT protocol. GPS tracking is employed to determine the motor pump's installation location, and GSM technology allows the motor pump to be turned on or off via SMS or call. Real-time data, such as the motor pump's status, frequency, power, voltage, speed, and temperature, can be accessed on the web server anytime. [PERSON] et al. [134] propose an embedded system for remote monitoring of inverters in a solar power plant. The system uses a Raspberry Pi as the controller, with inverters connected in a daisy chain and the final inverter linked to the Raspberry Pi. Key data, such as total power and failsafe parameters (grid fault, PV over, over current, over temperature, and short circuit), are obtained via the Modbus protocol. Additionally, sensors measure temperature, wind speed, and solar irradiance. These data are uploaded to an SQL database over Wi-Fi, and users can remotely monitor the system through a web interface, allowing access to real-time performance data of the solar power plant. Also, [PERSON] et al. present in article [135] a practical and low-cost monitoring system for photovoltaic water pumping systems (PVWPSs) that use lithium-ion batteries. With the increasing use of PV technology and falling battery prices, integrating energy storage into solar-powered systems is becoming more common. The work proposes a quasi-real-time monitoring solution using open-source IoT tools to help manage, operate, and develop these systems more effectively. The system was tested using a setup that includes a solar field, a hybrid inverter, a lithium-ion battery, a variable speed driver, and a submersible pump. Data are collected using commercial hardware with Modbus-RTU communication and processed through a Raspberry Pi. Data is stored in InfluxDB and visualized using Grafana, while a customizable exporter allows users to create Excel or.csv files of selected data. This system shows how IoT and open-source tools can enhance the performance and monitoring of solar energy systems. Using the PROFINET protocol, [PERSON] et al. [136] outline the development of a real-time solar panel monitoring system using a web server and a Siemens S7-1200 PLC, programmed with TIA Portal V17. The system collects key data--voltage, current, power output, temperature, irradiance, and environmental conditions--and transmits them to a web server via the PROFINET protocol for wired communication between the PLC and client devices. Users can access these data remotely through a web browser over WIFI to monitor performance, view historical trends, and receive alerts for any issues. This setup enhances solar energy management by enabling efficient monitoring, quick issue detection, and informed decision-making for maintenance and optimization. [PERSON] et al. [137] present a low-cost energy monitoring system for solar PV setups that uses wired communication through RS-485, a standard industrial protocol. The system integrates an RS-485-to-Serial Converter to collect real-time data from an energy meter and transmit it to an ESP32 microcontroller. This wired communication ensures reliable data transfer between components, making it suitable for consistent monitoring in PV systems. Meanwhile, in their paper, [PERSON] et al. [138] explore how Industrial Internet of Things (IIoT) and Industry 4.0 concepts can be applied in real-life setups, not just in theory. They demonstrate a low-cost practical implementation of an IIoT architecture designed to enhance energy systems, including PV sources. Unlike many works focusing only on theoretical models, their approach is experimentally validated through a pilot microgrid setup combining solar and hydrogen energy. The proposed system is structured into four functional layers: Sensing, Network, Middleware, and Application. The application layer leverages Grafana for real-time visualization and remote access via the web.