GeoSol

Intelligent platform for the design, monitoring, and maintenance of photovoltaic plants using AI, drone and satellite imagery, terrain modeling, and predictive analytics to optimize energy production and detect anomalies.

Year
2020
Industry
Critical Infrastructure
Status
Completed
Leading Applied Innovation
The Digital Twin Platform for Smarter Solar Plant Performance
A Platform for Solar Intelligence at Every Stage

The GeoSol Platform is an intelligent, cloud-native system that supports the entire lifecycle of photovoltaic plants—from site identification and construction tracking, to predictive maintenance and energy performance optimization. Offered as an AI-as-a-Service (AIaaS) model, it adapts to the needs of solar plant owners, installers, and operators through mobile-first, pay-per-use access. Leveraging very high-resolution satellite imagery (15–50 cm/pixel) and up to 16 multispectral bands, the platform can automatically generate parcel maps, analyze optimal irradiated zones, and detect early-stage anomalies. Its core mission: to deliver actionable, high-value geospatial insights that improve installation precision, operational efficiency, and production reliability.

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Integrated Analytics and Predictive Maintenance

The platform integrates Big Data, machine learning (ML), and real-time IoT sensor data to enable predictive maintenance, performance monitoring, and operational optimization. With tools for terrain modeling (DTM/DSM), drone-based thermal analysis, and multispectral processing, GeoSol supports:

  • Automated image processing for digital twin creation
  • Real-time performance estimation via SCADA integration
  • Dynamic fault detection with CNN, RNN, and DNN models
  • Mobile app for field task tracking and augmented reality diagnostics
Objetives

Project Objectives:

  • Analyze and predict solar panel performance using AI and high-resolution imagery
  • Automate maintenance through fault detection and anomaly prediction
  • Digitize solar parcels and model terrain impact for site optimization
  • Forecast production with DSS tools and 3D visualization
  • Integrate real-time data from SCADA systems and on-site sensors

Use Cases Include:

  • Automated panel fault detection (drones + AI)
  • Environmental impact modeling and site optimization
  • Real-time IoT monitoring of energy yield
  • Mobile AR tools for field diagnostics
  • 3D site surveys and digital twin creation
[ INSIGHTS ]

Tutorial: Masked Portfolio Splitscreen Scroll Animation

In this Webflow tutorial, Jonas Arleth shows how to create a masked scroll animation with a split screen effect over the text. He explains how to analyze and recreate the animation. He covers various elements such as navigation, text shift and background color. He also shows how to move the text in the animation and gives tips for optimization.  
Seen at: https://pioneer-portfolio.webflow.io

Technologies Used

  • Artificial Intelligence (AI) for performance and fault prediction
  • Satellite & Drone Imagery for high-precision visual analysis
  • 3D Terrain Modeling (DTM/DSM) for optimal panel placement
  • IoT & SCADA Integration for real-time monitoring and control
  • Digital Twin Generation for simulation and optimization
  • Key Results

  • Predictive analysis of solar panel efficiency
  • Fault detection using drone thermography and ML
  • Digital twins and 3D terrain models
  • Real-time monitoring with IoT and SCADA
  • Mobile and web-based AI platform
  • Scalable and modular deployment
  • Impact

  • Improved solar plant productivity and uptime
  • Reduced inspection costs and maintenance downtime
  • Enhanced planning accuracy and installation ROI
  • Proactive environmental compliance
  • Greater data-driven operational transparency
  • Scalable, replicable model for other renewable sectors
  • Collaborators
    [ in collaboration with ]
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