Images from drones, fixed cameras, LiDAR, and other sources can elevate utilities’ efforts to prevent wildfires, keep field assets in good working order, and mobilize disaster response teams. With potentially thousands of images flowing in every day, utility providers need intelligent image analytics solutions that can transform this visual data into decision-supporting insights.
Logic20/20 leverages the latest in machine learning and AI, including advanced computer vision, to develop impactful image analytics solutions. We empower utilities to transform a steady stream of raw images into real-time, data-driven insights that help them protect their assets and safeguard their communities.
Building a strong foundation
For image analytics solutions to deliver timely, accurate insights, quality input is essential. That’s why Logic20/20 begins by building a strong data foundation to maximize ROI on your investment, encompassing six integrated pillars:
Utility use cases: where image analytics makes a difference
AI-powered reviews of drone images rapidly identify high-risk overgrowth to help you prioritize interventions.
Evaluate equipment images alongside key inspection, asset, and weather data to enable proactive, analytics-driven maintenance.
Transform photos of damage into data to prioritize restoration efforts and streamline insurance claim reporting.
Enhanced operational efficiency
Process and analyze vast quantities of visual data at a speed and accuracy level unattainable by human effort, enabling quicker decision making and more streamlined operations.
Improved safety and risk management
Identify potential hazards and maintenance issues—like damaged equipment or overgrown vegetation near power lines—before they can lead to outages or accidents.
Cost-effective asset management
Prioritize maintenance tasks and allocate resources based on real-time visual data to extend the lifespan of critical infrastructure.
Rapid disaster response and recovery
Quickly assess damage from events like storms or wildfires to mobilize recovery efforts more effectively, minimizing downtime and expediting restoration of service.
Streamlined regulatory compliance and reporting
Monitor and document compliance with industry regulations such as vegetation management laws to facilitate reporting while ensuring accuracy.
Improved customer satisfaction
By proactively addressing potential issues and minimizing disruptions, utilities can significantly improve customer satisfaction and create a better overall customer experience.
Mitigating wildfire risk with computer vision-aided asset management and machine learningHow one utility uses image analytics to assist and prioritize inspections and maintenance—with up to 80% accuracy in detecting the presence of certain equipment.
Operationalizing machine learning intelligence for a major utilityWe implemented machine learning operations (MLOps) to enable integration of machine learning insights into grid planning, emergency response, public safety, and asset protection efforts.
Drones plus AI: meet the future of utility asset management
Using computer vision to help utilities prevent wildfires
Using machine learning to improve vegetation management
What are your challenges? Let’s talk through the solutions.