Research
Collect data and ger ready for development.
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SOLAR - AID
Large Scale,Dashboard,Live Data
SOLAR - AID - AI POWERED DASHBOARD
The Solar Farm Monitoring Dashboard Software is a project aimed at developing a software solution that can help solar farm operators to monitor and manage their solar energy production more efficiently. The software will be designed to collect data from various sensors installed on the solar panels, inverters, and other equipment, and present the data in a clear and concise manner on a dashboard interface. The Solar Farm Monitoring Dashboard Software will be able to collect and analyze data related to energy production, weather conditions, equipment status, and other factors that may affect the performance of the solar farm. The software will be designed to provide real-time alerts and notifications to operators in case of any abnormal events, such as equipment failure or low energy production.
DATe
12 July, 2020
Client
MONTESOL
Project Type
Live data processing,computation,
Duration
2 Months 18 Days
Working Process
1
2
Identify Requirement
Then we find the requirement .
3
Resolve Problem
Now it’s time to fix the issue by advance ai
The Challange
The goal of this challenge is to develop a solar monitoring software that can optimize the performance of solar power plants by maximizing their efficiency and reducing downtime. The software should be able to provide real-time monitoring and analysis of solar panels, inverters, batteries, and other components to ensure that they are functioning optimally.
Our Goal
- Develop a solar monitoring software system that can optimize the performance of solar power plants by maximizing their efficiency and reducing downtime.
- Collect and process data from various sensors and devices installed in the solar power plant, such as irradiance sensors, temperature sensors, and power meters
- Analyze the data collected to detect and diagnose issues in real-time, and provide recommendations to address them.
Result
Solar Aid collects and processes data from various sensors and devices installed in the solar power plant, such as irradiance sensors, temperature sensors, and power meters. The data is analyzed using machine learning algorithms to detect anomalies and issues that may impact the performance of the solar power plant.