URBIM + AI: Transforming Solar Plant Incident Management
On the path towards the digitalization of the photovoltaic industry, URBIM integrates artificial intelligence to revolutionize incident management for solar plant operations and maintenance.
AI-Powered Identification
Automatic detection of key elements in solar plant incidents, drastically reducing manual tasks and improving the traceability of each case.
Streamlined Workflows
Revolutionary process optimization that transforms how teams identify, document, and resolve incidents in photovoltaic installation and maintenance projects.
Complete Digital Ecosystem
Seamless connection with tools like Jira ensures perfect synchronization of information across your entire solar plant management infrastructure.
Discover how URBIM is redefining the standards of efficiency and control in photovoltaic project management with the power of artificial intelligence.
Use Case: Intelligent Incident Management
Value Proposition: Automate incident documentation to focus on solutions, not paperwork
Secure Integration
Smooth connection between URBIM and Jira through credential-based authentication, ensuring data integrity at all times.
AI-Powered Automation
Automatic identification of elements related to the incident through text analysis, recognizing specific Trackers and Blocks.
3D Visualization
Precise localization of incidents in the three-dimensional model, allowing for immediate spatial understanding of the problem.
Advanced Monitoring
Interactive dashboard with key metrics on the status and evolution of incidents, facilitating strategic decision-making.
Transform your team’s focus from documentation to problem-solving, accelerating response times and improving project quality.
This use case demonstrates the transformative potential of URBIM as a gateway to artificial intelligence in the FM sector. By automating the identification and management of incidents, teams can focus on solving problems instead of documenting them, accelerating response times and improving the final quality of the project.
The solution is fully scalable and adaptable to the specific needs of each client, laying the foundations for future implementations with even more advanced AI models.
Technical Implementation: PoC URBIM + Jira with AI
Architecture and system integration for the RESTful API-based Proof of Concept leveraging NLP algorithms
API Authentication Layer
OAuth 2.0 implementation for secure URBIM-Jira integration with JWT tokens, enabling role-based access control (RBAC) to project resources via encrypted REST endpoints.
WebGL Rendering Engine
Three.js-based 3D model integration with custom event listeners for bidirectional data binding between BIM elements and incident tickets, implementing octree-based spatial indexing for rendering optimization.
Dynamic Form Generator
JSON-schema driven form construction with webhook triggers for bidirectional data synchronization, implementing automatic issue type classification via Jira’s API v3 endpoints.
Real-time Analytics Pipeline
GraphQL-powered metrics aggregation with WebSocket connections for live dashboard updates, utilizing D3.js for data visualization and Redux for state management of incident monitoring interfaces.
NLP Model Integration
Integration of transformer-based NLP models (BERT architecture) for entity recognition in incident reports, with 92% accuracy in identifying component references and system elements.
This microservices-based architecture establishes a containerized, horizontally scalable solution deployed on Kubernetes, with CI/CD pipelines for continuous integration and feature enhancement through subsequent ML model iterations.
