DISTRIBUTECH, Orlando, Fla. – February 8, 2016 – GeoDigital International Inc., a leader in 3D services and geospatial intelligence software, today introduced GeoDigital Insight, which enables utilities to remotely monitor and optimize their vast networks of transmission and distribution lines. GeoDigital Insight is a proprietary combination of 3D remote-sensing, predictive analytics, artificial intelligence and mobile work software that digitizes business processes for inspecting poles, wires, and the environment that surrounds these linear assets.
GeoDigital serves a number of utilities using the end-to-end components of the GeoDigital Insight platform to manage their transmission networks. Today’s launch extends this capability to distribution networks, supporting asset inspections, as well as joint-use, vegetation-clearance and pole-loading analyses, among other processes. The company is working with a number of leading distribution utilities on pilots of the technology.
“With ‘Energy 2030’ looming, utilities are under tremendous pressure to extract as much productivity as possible from their assets, investing billions to make grids smarter and keep the lights on. But when it comes to understanding the condition of their largest linear assets – the poles and wires grid – utilities are still largely in the dark,” said Chris Warrington, GeoDigital president and CEO. “By gaining better situational awareness and digitally connecting this linear asset network, we believe North American utilities could save around $2 billion. Such total grid visibility would enable utilities to preempt repairs, increase the safety of field crews, and reduce the risk of outages.”
GeoDigital Insight will help utilities move from cyclical to condition-based inspections by remotely inspecting assets with high-resolution imagery and spatial intelligence. A digital record of degrading infrastructure can optimize grid investment decisions, while insights on asset conditions can supplement information from smart-grid-connected equipment in the network.
GeoDigital Insight also predicts and prioritizes outage risks posed by trees and other vegetation.
By digitizing regular vegetation-management inspections, utilities are able to efficiently manage thousands of miles of power lines and reduce human-exposure with labor-intensive field inspection methods that remain largely manual. Similarly, utilities can use GeoDigital Insight to review infrastructure from an engineering perspective and ensure compliance with clearance regulations.
To date, GeoDigital has mapped some 430,000 miles of transmission lines – data that pinpoints the precise location and condition of 1.9 million assets. GeoDigital collects the data via sophisticated sensors aboard helicopters, fixed-wing aircraft, UAVs and ground-based methods. The company’s Autonomous Driving unit is using similar technology to build a digital road map of North America’s multi-lane highways to guide self-driving vehicles.
GeoDigital is a 3D data and spatial intelligence software company. Precision digital blueprints for infrastructure such as energy and roads enable virtual decisions that drive safety, reliability and productivity. This spatial framework enables the Internet of Things to interact with previously disconnected infrastructure, keeping the virtual environment current with real-world conditions using newly sensed and crowdsourced data. Its flagship solution for utilities, GeoDigital Insight, unlocks new levels of situational awareness on the health of linear grid assets and recommends decisions that impact reliability, cost, safety and compliance. GeoDigital is using this proven technology to make safe and smooth autonomous driving a reality with its Digital Driving platform – North America’s largest digital road and cutting-edge on-board spatial awareness software. With a track record for 3D innovation since 2005, Atlanta-based GeoDigital has operations in the United States, Canada, and Australia. Visit geodigital.com to find out more.
Sean Healy, Healy Corporate Communications
201-857-2520 or 201-218-2039 (cell)