For many organizations, vegetation management (VM) is the largest non-fuel-related operating cost. To prioritize VM work, organizations must capture and merge data from multiple sources, including images, data from work management systems, regulatory requirements, weather information, risk models, geospatial data, and more. They must then be able to use this data to accurately plan and forecast the distance between assets and vegetation by carefully registering and combining 3D models of the network and its surrounding vegetation. By leveraging data from topographic surveys alongside analytics (for example, plant health indices), utilities can optimize their vegetation maintenance resources, budgets, and work routines.
Evaluating tree canopy height, and more generally the height of any type of vegetation, as part of a vegetation management plan is one of the most widely known applications of both light detection and ranging (LiDAR) and photogrammetry. Both techniques, which are often combined, require advanced classification and filtering algorithms to accurately derive vegetation height and condition. Utilities use these techniques to identify structurally unsound trees, analyze climbing vines that might impact wires and switchgear components, and manage vegetation that might attract unwanted wildlife near critical equipment.
The following architecture demonstrates how we can use Oracle Modern Data Platform in conjunction with advanced ML/AI techniques and NVIDIA GPUs to not only derive a two-dimensional picture of vegetation but also add a third dimension that provides finer-grained detail. This detail allows us to determine the type of tree, its growth, and its distance from the infrastructure, as well as other details, more accurately.
Vegetation management logical architecture
There are two main ways to inject data into an architecture to enable utilities to effectively develop a vegetation management strategy.
Data persistence and processing is built on three components.
The ability to analyze, learn, and predict is facilitated by three technologies.
Efficient and timely asset management is always essential, but it’s even more critical when assets include power lines that could spark a fire or outage due to vegetation overgrowth. For power utilities in the United States, vegetation management is the largest preventive maintenance expense, exceeding $100 million annually at many larger utility companies. However, VM is also the greatest contributor to utility system reliability and effective outage management. With Oracle Modern Data Platform, you can gather fine-grained details of your infrastructure and its surrounding vegetation and use this data to help improve your VM strategy and results in the following ways:
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