Data were collected for 6 months period in order to train and evaluate predictive AI models. The system described in section 2 was operated, anddata were collected in the Khataba region in Elsadat, Beheira Government in Egypt. 110022 records were collected.The dataset collected consisted oftwo categories: the weather data and the inverter motor data. The weather data comprises:1. UV index measured by (W/m2)2. Air temperature measured by degree Celsius (◦C)3. Wind speed measured by (m/sec)4. Wind direction measured by degrees from North5. Humidity measured by percentage6. Gust measured by (m/sec)7. Cloud cover measured by percentage.The energy generated by solar power is influenced by various environmental factors. For example, a higher UV index generally increases energy output since solar panels rely on sunlight, though prolonged exposure can degrade materials over time. Air temperature, on the other hand, has a negative impact on the energy generated. However, while solar panels need sunlight, excessive heat reduces efficiency due to increased electrical resistance, therefore, wind speed can be beneficial in cooling the panels, helping to counteract temperature-related losses, but strong gusts may stress mounting structures. Wind direction indirectly affects performance by influencing cooling efficiency, depending on how air flows around the panels. On the other hand, humidity reduces energy output because water vapor scatters sunlight, limiting the amount of radiation reaching the panels, and over time, excessive moisture can degrade panel components. Similarly, cloud cover reduces the effect of direct sunlight, leading to lower energy production. Overall, optimal conditions for solar energy include high UV levels, moderate temperatures, steady cooling winds, and minimal humidity or cloud cover.The weather data were collected daily using the stormglass.io API given a certain position in terms of longitude and latitude. This data representsthe parameters that affect the solar energy, hence the input power to the inverter motor. Data related to the inverter motor are:1. Frequency reference2. Output frequency3. Output current4. DC bus voltage5. Output power6. Output frequency fault7. Heatsink temperature8. Proportional-Integral-Derivative (PID) controller output9. PID inputFor more information about the dataset or the system please read and cite our publication: "AI-Driven Digital Twin for Solar-Powered Submersible Pump Systems: A Machine Learning Approach for Performance Optimization"

Data were collected for 6 months period in order to train and evaluate predictive AI models. The system described in section 2 was operated, anddata were collected in the Khataba region in Elsadat, Beheira Government in Egypt. 110022 records were collected.The dataset collected consisted oftwo categories: the weather data and the inverter motor data. The weather data comprises:1. UV index measured by (W/m2)2. Air temperature measured by degree Celsius (◦C)3. Wind speed measured by (m/sec)4. Wind direction measured by degrees from North5. Humidity measured by percentage6. Gust measured by (m/sec)7. Cloud cover measured by percentage.The energy generated by solar power is influenced by various environmental factors. For example, a higher UV index generally increases energy output since solar panels rely on sunlight, though prolonged exposure can degrade materials over time. Air temperature, on the other hand, has a negative impact on the energy generated. However, while solar panels need sunlight, excessive heat reduces efficiency due to increased electrical resistance, therefore, wind speed can be beneficial in cooling the panels, helping to counteract temperature-related losses, but strong gusts may stress mounting structures. Wind direction indirectly affects performance by influencing cooling efficiency, depending on how air flows around the panels. On the other hand, humidity reduces energy output because water vapor scatters sunlight, limiting the amount of radiation reaching the panels, and over time, excessive moisture can degrade panel components. Similarly, cloud cover reduces the effect of direct sunlight, leading to lower energy production. Overall, optimal conditions for solar energy include high UV levels, moderate temperatures, steady cooling winds, and minimal humidity or cloud cover.The weather data were collected daily using the stormglass.io API given a certain position in terms of longitude and latitude. This data representsthe parameters that affect the solar energy, hence the input power to the inverter motor. Data related to the inverter motor are:1. Frequency reference2. Output frequency3. Output current4. DC bus voltage5. Output power6. Output frequency fault7. Heatsink temperature8. Proportional-Integral-Derivative (PID) controller output9. PID inputFor more information about the dataset or the system please read and cite our publication: "AI-Driven Digital Twin for Solar-Powered Submersible Pump Systems: A Machine Learning Approach for Performance Optimization"

Data were collected over a year to develop AI models. The system, operating in Marsa Matrouh, Egypt, gathered two data categories: weather and inverter motor data.Weather data includes:UV index (W/m²)Air temperature (°C)Wind speed (m/s)Wind direction (° from North)Humidity (%)Gust speed (m/s)Cloud cover (%)Solar energy generation is influenced by these factors. A higher UV index generally increases power output, though prolonged exposure degrades materials. Excessive heat reduces efficiency due to electrical resistance. Wind speed cools panels, mitigating heat-related losses, but strong gusts may stress structures. Wind direction affects cooling efficiency, humidity scatters sunlight and degrades components, and cloud cover reduces direct sunlight but may occasionally enhance scattered light collection. Optimal conditions include high UV levels, moderate temperatures, steady cooling winds, and minimal humidity or clouds. Weather data was collected daily via the Stormglass.io API at a fixed location.Inverter motor data includes:Frequency referenceOutput frequencyOutput currentDC bus voltageOutput powerFrequency faultHeatsink temperaturePID outputPID inputThe inverter motor drive manages input and output parameters for efficiency and stability. The frequency reference controls motor speed, while the PID controller adjusts performance using sensor data. Output frequency affects motor speed, and output current indicates load. The DC bus voltage stabilizes power supply, while output power reflects energy delivered. Safety features include frequency fault warnings and heatsink temperature monitoring to prevent overheating. The PID output fine-tunes motor speed and torque for optimal efficiency.For more information about the dataset or the system please read and cite our publication:

A 3720 record of data were collected from the prototype mentioned 2 from 61 practitioners (29 Male and 31 Female) with an average age of 38. The data were collected while performing opening cavities for fillings. The data consists of the following: ID, State, Time, Deviation, Roll, Pitch, Yaw, Acceleration, and Velocity. The ID is the practitioner ID that was assigned to him to store his information separately. The second parameter is the state, which is represented by three forms: Lever Range, Alert Range, and Stop Range. The state was determined based on observation. The Device Roll, Pitch and Yaw describe the rotation axis of the device. Finally the Acceleration and Velocity which describes the motion state at the given time.Please reference our work by citing our article: "Artificial Intelligence Operated Dental Handpiece for Dental Students Practice: A Step Towards Precision and Automation"For collaboration about the prototype please contact Dr. Omar Shalash, email: [email protected] or Dr. Esraa Khatab, email: [email protected]

A 3720 record of data were collected from the prototype mentioned 2 from 61 practitioners (29 Male and 31 Female) with an average age of 38. The data were collected while performing opening cavities for fillings. The data consists of the following: ID, State, Time, Deviation, Roll, Pitch, Yaw, Acceleration, and Velocity. The ID is the practitioner ID that was assigned to him to store his information separately. The second parameter is the state, which is represented by three forms: Lever Range, Alert Range, and Stop Range. The state was determined based on observation. The Device Roll, Pitch and Yaw describe the rotation axis of the device. Finally the Acceleration and Velocity which describes the motion state at the given time.Please reference our work by citing our article: "Artificial Intelligence Operated Dental Handpiece for Dental Students Practice: A Step Towards Precision and Automation"For collaboration about the prototype please contact Dr. Omar Shalash, email: [email protected] or Dr. Esraa Khatab, email: [email protected]

A 3720 record of data were collected from the prototype mentioned 2 from 61 practitioners (29 Male and 31 Female) with an average age of 38. The data were collected while performing opening cavities for fillings. The data consists of the following: ID, State, Time, Deviation, Roll, Pitch, Yaw, Acceleration, and Velocity. The ID is the practitioner ID that was assigned to him to store his information separately. The second parameter is the state, which is represented by three forms: Lever Range, Alert Range, and Stop Range. The state was determined based on observation. The Device Roll, Pitch and Yaw describe the rotation axis of the device. Finally the Acceleration and Velocity which describes the motion state at the given time.Please reference our work by citing our article: "Arificial Intilligence Operated Dental Handpieces for Dental Students Practice: A Step Towards Precision and Automation"For collaboration about the prototype please contact Dr. Omar Shalash, email: [email protected] or Dr. Esraa Khatab, email: [email protected]

Data were collected over a year to develop AI models. The system, operating in Marsa Matrouh, Egypt, gathered two data categories: weather and inverter motor data.Weather data includes:UV index (W/m²)Air temperature (°C)Wind speed (m/s)Wind direction (° from North)Humidity (%)Gust speed (m/s)Cloud cover (%)Solar energy generation is influenced by these factors. A higher UV index generally increases power output, though prolonged exposure degrades materials. Excessive heat reduces efficiency due to electrical resistance. Wind speed cools panels, mitigating heat-related losses, but strong gusts may stress structures. Wind direction affects cooling efficiency, humidity scatters sunlight and degrades components, and cloud cover reduces direct sunlight but may occasionally enhance scattered light collection. Optimal conditions include high UV levels, moderate temperatures, steady cooling winds, and minimal humidity or clouds. Weather data was collected daily via the Stormglass.io API at a fixed location.Inverter motor data includes:Frequency referenceOutput frequencyOutput currentDC bus voltageOutput powerFrequency faultHeatsink temperaturePID outputPID inputThe inverter motor drive manages input and output parameters for efficiency and stability. The frequency reference controls motor speed, while the PID controller adjusts performance using sensor data. Output frequency affects motor speed, and output current indicates load. The DC bus voltage stabilizes power supply, while output power reflects energy delivered. Safety features include frequency fault warnings and heatsink temperature monitoring to prevent overheating. The PID output fine-tunes motor speed and torque for optimal efficiency.For more information about the dataset or the system please read and cite our publication: