Protecting electrical lines, power plants and other utility assets from unwanted vegetation is a matter of public safety: falling tree branches and overgrown brush near power lines can lead to outages, wildfire risk and elevated hazards for people and for property. But traditional methods for decision-making around vegetation control are inefficient and expensive, relying on cyclic scheduling and manual inspections.
IBM Environmental Intelligence Suite® with Vegetation Management utilizes satellite data and Geiger-mode LiDAR predictive analytics combined with weather insights to deliver artificial intelligence driven insights about vegetation growth, so you can make more informed and proactive decisions about utility vegetation management. This cost-effective solution is built on a platform that processes massive, complex geospatial and time-based datasets, applies AI and analytics to calculate and score the impact of vegetation, and helps identify high-risk circuits or corridors that will benefit most from trimming or maintenance operations.
The Environmental Intelligence Suite helps managers and stakeholders better understand the current state of vegetation across a territory, including the average height and maximum tree height of trees that might pose a threat to utility service and summaries of vegetation encroachment in defined buffer zones around assets. The tool scales automatically, assessing vegetation growth across hundreds of miles of power lines and allowing tree pruning and tree removal work to be prioritized by corridors, segments, and zones.
Satellite imagery and LiDAR data is used to evaluate spans of vegetation according to various metrics and KPIs, such as distance to a power conductor or amount of encroachment into a buffer zone, and scores are assigned to help identify and focus brush removal efforts. Users can build an integrated vegetation management plan by combining these insights with other layers of information to design custom dashboards, alerts, and decision-making metrics, and export data as needed.
The tool provides insights on tree species that includes identification of hazard trees that present a fall risk, and predicts areas where tree trimming might protect transmission lines and other assets. With dashboard views and alerts, managers can optimize preventative maintenance and trimming cycles, build proactive asset management strategies, rapidly respond and reduce the need for costly manual inspections.
IBM Vegetation Management leverages artificial intelligence, satellite imaging and LiDAR data, including geiger-mode data and linear LiDAR to assess and monitor vegetation and improve work prioritization.
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