Supporting Compliance with IEEE Std 1808-2024: Gridnostic for Smarter Transmission Line Data Management
< Back to Articles & Case Studies
As electrical utilities face mounting regulatory pressures, aging infrastructure, and rising demands for grid reliability, the ability to collect, manage, and analyze inspection and maintenance data becomes a core operational priority. The IEEE Std 1808-2024, Guide for Collecting and Managing Transmission Line Inspection and Maintenance Data, addresses these challenges by offering a comprehensive framework for designing and implementing modern, computer-based data management systems.
OFIL Systems’ Gridnostic platform is designed to support utilities in meeting the expectations outlined in the standard. By providing a comprehensive digital environment for organizing, analyzing, and sharing multi-sensor inspection data, Gridnostic enables utilities to operationalize IEEE 1808-2024 compliance—transforming inspection insights into actionable decisions.
IEEE Std 1808-2024
IEEE Std 1808-2024 is designed to help utilities transition from fragmented, paper-based inspection processes to efficient, computer-based data systems. Its scope includes the collection, validation, structuring, analysis, and long-term management of inspection data from transmission lines and associated assets. The guide provides a roadmap for implementing solutions that ensure data integrity, usability across departments, compatibility with GIS and enterprise systems, and compliance with regulatory standards.
The guide aims to transform inspection data into a strategic asset—enabling utilities to perform risk-based maintenance, improve grid reliability, and make better, data-driven decisions
What is Gridnostic?
Gridnostic is OFIL Systems’ intelligent inspection data management platform. It supports RGB, thermal, and UV imaging inputs, using artificial intelligence and expert-driven diagnostics to identify, assess, and prioritize issues across transmission infrastructure. Built on real-world utility experience, Gridnostic combines advanced analytics, GIS mapping, AI Copilots, and EPRI-based severity assessments into a seamless workflow—from data collection to insight generation and reporting.
This product was developed based on research and guidelines from the Electric Power Research Institute
Structured Data Collection and AI-Based Analysis
One of the cornerstones of IEEE 1808-2024 is the importance of structured data entry and AI-enhanced analytics. The guide calls for systems that reduce human error, improve repeatability, and support consistent decision-making.
After images and videos are uploaded to Gridnostic, the AI Copilot automatically detects anomalies such as corona discharges and thermal hotspots. These are then reviewed and assessed using the Severity Diagnostic Tool, which converts qualitative imagery into quantified severity scores. This scoring mechanism reduces human subjectivity and allows utilities to prioritize repairs based on risk rather than opinion—exactly the type of decision support envisioned by the IEEE standard.
Geospatial Intelligence and Impact-Based Severity Scoring
IEEE 1808-2024 underscores the need for context-aware data to drive informed, risk-based decisions. Gridnostic leverages GIS mapping and infrastructure metadata to deliver location-specific insights for each inspection finding. By incorporating factors such as asset criticality, network configuration, and surrounding risk conditions, the platform dynamically adjusts severity scores to reflect both the condition of the asset and its broader operational context. This enables utilities to prioritize maintenance and mitigation efforts based on real-world impact and strategic importance.
Multi-Sensor Data Fusion and GIS Compatibility
The IEEE guide outlines the value of integrating data from various inspection tools—UV, IR, RGB, LiDAR—and ensuring compatibility with GIS platforms. Gridnostic is purpose-built to accommodate these needs. It fuses multi-sensor inputs into a unified platform and overlays inspection data onto interactive geospatial map layers and substation diagrams. This GIS integration enhances spatial understanding of asset conditions and supports better planning, visualization, and routing—helping utilities make smarter decisions faster.
Long-Term Data Retention and Trend Analysis
IEEE 1808-2024 also calls for systems capable of storing historical data and using it for trend analysis and predictive maintenance. Gridnostic offers full asset histories, enabling users to track fault development over time and assess the effectiveness of past repairs.
Knowledge Retention in the Face of Workforce Transitions
IEEE Std 1808-2024 highlights the urgent need to preserve institutional knowledge as experienced utility personnel retire at an accelerating rate. This shift creates a gap in diagnostic consistency and decision-making expertise.
Gridnostic addresses this challenge through its structured, EPRI-based severity assessment framework. By guiding users through a standardized evaluation process, the platform ensures consistent interpretation of inspection data—regardless of the technician’s experience level. This approach safeguards the quality of asset assessments while supporting long-term continuity of knowledge across teams and generations.
Conclusion: From Compliance to Competitive Advantage
IEEE Std 1808-2024 sets a clear direction for advancing how electric utilities handle inspection and maintenance data. OFIL Systems’ Gridnostic aligns seamlessly with this standard, offering the capabilities needed to collect structured data, apply AI-driven diagnostics, integrate geospatial and infrastructure context, and support long-term asset management strategies.
Adopting Gridnostic enables utilities to move beyond baseline compliance—embracing a smarter, more responsive approach to infrastructure management. The result is greater operational efficiency, improved grid reliability, and the ability to transform inspection data into a strategic asset.
Contact
