# 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
#### 3.2.2 Optimization Techniques: MPPT, Solar Tracking, and Cleaning Systems  
Despite the growth of global solar power generation capacity, the widespread adoption of PV systems remains limited due to high initial costs and the variability of energy output. Factors such as solar irradiance, ambient temperature, dust accumulation, and load conditions significantly impact PV performance. To address these challenges and ensure optimal operation under varying environmental conditions, a combination of Maximum Power Point Tracking (MPPT), solar tracking, and automated cleaning systems is essential. The MPPT control system optimizes the performance of PV systems by dynamically adjusting their operating points to extract the maximum possible power. By continuously \begin{table}
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**Study** & **IoT Technology Used** & **Data Acquisition** & **Communication Protocol** & **Monitoring Features/Additional Functions** & **Low Cost** \\ \hline [PERSON] et al. [153] & IoT-based real-time system with ZigBee generation data & DC output, AC output, and power generation data & ZigBee for node communication, 4G for data transmission to cloud & Fault diagnosis, remote monitoring via web/mobile interface & Yes monitoring via web/mobile interface & Yes \\ \hline [PERSON] et al. [154] & IoT solar panel management & Voltage, current, and generated electricity & Wireless & Automatic panel orientation adjustment & Yes \\ \hline [PERSON] et al. [155] & Smart IoT-based remote sensing prototype & Voltage, current, and temperature & Wi-Fi and Effective remote monitoring and fault identification & Yes \\ \hline [PERSON] and [PERSON] [120] & Smart IoT solar system using Hidden Markov Model & Meteorological data Markov Model & Wireless & Solar energy prediction using time series analysis & No \\ \hline [PERSON] et al. [156] & IoT-based solar PV monitoring & Voltage, current, temperature, irradiance & Wi-Fi & High accuracy (98.49\%) in data capture; smartphone-based monitoring & No \\ \hline [PERSON] et al. [157] & Open-source IoT solution & Environmental and solar power data & Wi-Fi & Real-time alerts for solar power deviations & Yes \\ \hline [PERSON] et al. [158] & IoT dust monitoring framework & Open-circuit voltage data & Wireless & Automatic cleaning trigger for solar panels & Yes \\ \hline [PERSON] et al. [159] & IoT cleaning system for solar panels & Dust sensor, temperature, humidity & Wireless & Automated cleaning system triggered by dust accumulation & Yes \\ \hline [PERSON] et al. [160] & Cloud-based Solar Conversion Recovery System (SCRS) & Light intensity, Temperature, Current, Voltage & MQTT & Optimized PV panel soiling monitoring (4.33\% error rate) & Yes monitoring (4.33\% error rate) & Yes \\ \hline [PERSON] et al. [161] & Energy harvesting IoT network & Power harvesting from surroundings & Wireless & Ensures continuous power for low-powered devices over various distances & Yes \\ \hline \hline \end{tabular}
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Table 8: _Cont._monitoring and fine-tuning system settings, MPPT ensures that solar panels operate at their most efficient levels, enhancing energy generation and preventing underperformance [162]. Several studies focused on the design, performance, and optimization of single-axis solar tracking systems. In their paper, [PERSON] et al. [163] present the design and implementation of an innovative MPPT solar charge controller (SCC) enhanced with IoT capabilities. The system incorporates IoT-based sensors to transmit critical data to the cloud, enabling remote monitoring and control. Utilizing the PIC16F877A microcontroller, it employs the perturb and observe (P&O) algorithm along with a customized buck-boost converter for efficient power management. Validation is performed through MATLAB/SIMULINK simulations and laboratory testing. The MPPT-SCC supports a maximum current of 10 A at 12 V, achieving an efficiency of up to 99.74% over a month-long testing period. [PERSON] et al.