system
The system addresses inefficiencies in renewable energy site selection by analyzing geographical and meteorological data with machine learning and user feedback, enhancing the accuracy and speed of site prediction.
JP2026096480APending Publication Date: 2026-06-15SOFTBANK GROUP CORP
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Patent Information
- Application Number
- JP2024210272
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2024-12-03
- Publication Date
- 2026-06-15
AI Technical Summary
Technical Problem
Conventional methods for selecting renewable energy installation locations are inefficient due to complex data collection and analysis, lack of quick feedback integration, and inaccurate site selection, which hinders the widespread adoption of renewable energy.
Method used
A system that acquires geographical and meteorological data, analyzes it using machine learning, predicts potential sites, and continuously updates the model based on user feedback to improve accuracy and efficiency.
Benefits of technology
Enables rapid and efficient selection of optimal installation locations for renewable energy facilities, promoting their widespread adoption by integrating user feedback and improving prediction accuracy.
✦ Generated by Eureka AI based on patent content.
Abstract
We provide the system. [Solution] Means for obtaining geographical and meteorological data, A means for analyzing the aforementioned data to predict potential sites for power generation equipment, A means for displaying the aforementioned candidate installation sites on a map and presenting them to the user, A means of updating machine learning models based on user feedback, A system that includes this.
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