Tech FAQ: What data inputs does CRIS use?
We get lots of questions from potential customers. When we get the same question often enough, we create a brief explainer as a reference tool for our internal teams as well as interested visitors to our website. Here’s one about “CRIS,” the AiDash Climate Risk Intelligence System™.
Storms create uncertainty. Where and when will a storm land? How intense will it be? What sort of damage might it cause? How many utility customers will be affected? How long will it take to restore power?
And critically, the big question utilities and customers alike ask themselves: What can I do to prepare?
That’s why we created the AiDash Climate Risk Intelligence System™ (CRIS). The AI-powered system helps utilities and other organizations predict storm and wildfire incidents before storms hit. That in turn enables them to restore any outages faster and more safely and communicate with customers more proactively and accurately.
CRIS uses myriad inputs to generate and feed you insights before, during, and after a major weather event. But which ones?
At a glance: What inputs does CRIS use?
CRIS fuses satellite imagery, real-time weather data, vegetation data, and historic outage and resource usage data to give you insights before, during, and after a major weather event.
These inputs come from a variety of sources, including publicly available data, data from the utility, and AiDash’s own imagery. Here’s the list:
- Historical weather data from the service area
- Historical outage data from the utility
- Current utility company asset data
- Live weather feed
- Vegetation data from AiDash
- Miscellaneous data (whatever additional data utilities wish to offer)
Dive deeper
Historical weather data. We have partnerships with multiple vendors to supply global weather data from satellites and ground sensors. This data undergoes rigorous quality checks to ensure accuracy. Our model cross-verifies information from different sources to detect anomalies and refine predictions, ensuring reliable forecasts.
Live weather feed. In addition to using historical weather data to train the model and understand how weather has historically impacted utility assets, we acquire forecasts for up to a week in advance of a storm. This helps identify areas that are likely to experience incidents, allowing for faster response and restoration. Currently, we refresh this data four times each day, at six-hour intervals.
Historical outage data. AiDash also gets one-time historical outage data from each utility and uses it to improve the AI model. We typically request historical outage data up to 10 years to better identify anomalies in weather changes.
However, in the absence of long historical data, the model can also learn from recent outage data. Our customers also provide us with outage data at the end of every month, allowing the model to continuously learn and improve.
Infrastructure data. This data is crucial to making CRIS work optimally and is provided by utilities. It includes GIS data, the number and location of the utility’s assets (including poles, isolating devices, conductors, age of assets, and the materials used), service territory or district locations, and available human resources at those offices.
The higher the quality and greater the quantity of this data, the better CRIS will perform, delivering more accurate and reliable predictions.
Vegetation data. This is AiDash’s own satellite imagery. We use it to power AiDash Intelligent Vegetation Management System™ (IVMS) to identify vegetation abundance and risk, including tree heights in proximity to distribution conductors. Vegetation and weather-induced outages are inherently correlated, which is why we use it to improve the accuracy and reliability of CRIS predictions.
We also leverage LiDAR (both publicly available LiDAR and LiDAR scans from utilities) to enhance accuracy.
Miscellaneous. Essentially, AiDash can ingest any data a utility has and fuse it with the rest of the data to create more accurate predictions.
Check out this customer story to learn more about how CRIS helps utilities with their storm impact planning.
Click here for more information about our Climate Risk Intelligence System™ (CRIS).
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