Logic20/20 Asset Image Analytics products include suite a of tools that integrate with your existing program or implemented from the ground up. When setting strategy for image analytics programs, we consider top use cases, including asset identification, predictive asset management, vegetation management, and storm response. Successfully deploying asset image analytics demands a robust architectural framework designed to handle vast volumes of data efficiently while also ensuring scalability, performance, and seamless integration with existing systems. Conceptually, this includes an environment in AWS for staging and integrating data from image capture and other relevant sources, well designed programs in LabelOps and MLOps, models trained on accurate data, processing and inference, a portal for human in the loop monitoring, and integration with downstream systems like field management and supply chain systems. Key benefits include: -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. -Streamline 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 and comply with regulatory metrics for downtime, etc.