Introduction:

Natural disasters such as wildfires, hurricanes and floods are increasingly in the news.  Communities, businesses, critical services and IT and network infrastructure can be devastated by these events.

Current operational processes are performed manually and are time-consuming. If they’re performed at all. 

IBM Cloud Pak for AIOps (AIOps) includes a topology manager capable of displaying topological data from any source.  By combining data from multiple sources -including external risk data and infrastructure location data - valuable insights can be derived by using proximity analysis to help identify infrastructure and business services at risk of disruption.

Observing environmental hazards:

AIOps gathers and processes topological data using micro-services called observers. In AIOps 4.10.0 a new observer, the External Risks Observer, has been developed to collect and process data related to environmental hazards.

The external risks observer observes data from:

IBM Environment Intelligence Suite (EIS): A cloud-based climate and sustainability platform that integrates proprietary and third-party geospatial, weather, environmental, and IoT data.  The External Risks Observers collects the analyzed data for various hazards and models them as topology resources with geometry and state.  Hazards include:

• Wildfire
• Alert Headlines for floods, extreme heat, strong winds, fog, and more
• Watch and Warnings for floods, winter storms, marine hazards, and more. 

NASA Fire Information for Resource Management Systems (FIRMS):  NASA FIRMS provides data about active fires using satellite observations from the MODIS and VIIRS instruments.  The External Risk Observer observes the raw fire data from NASA FIRMS and models it as topology resources with geometry and state.

Note:  Satellite-derived data may not be near-real-time due to orbital constraints - Even IBM cannot break the laws of physics.

Enhancing the data:

The External Risks Observer performs additional processing to add value to the data collected:

• Geographic Filtering:
  All data sources can be filtered using a geographic bounding window (defined via GeoJSON or WKT) to ensure only relevant hazards are observed.
• Location Enrichment:
  Wildfire data from EIS can be enriched with nearby location names that give better context to AIOps users.
• Polygon Aggregation:
  NASA FIRMS point data can optionally be aggregated into polygons to reduce data volume and provide a clearer picture of affected areas.

Visualizing the external risks:

All resources within AIOps that include geolocation data  (including resources generated by the External Risk Observer) can be exploited using the Geographic Information System (GIS) capabilities in AIOps.

Deriving insights:

After data has been observed for both external risks and infrastructure with geometry, insight can be derived by using the proximity mode.  For example, to answer the question “Is any of my infrastructure within 500 meters of a fire?”, AIOPs uses two filters and a maximum distance.  The first filter identifies the infrastructure of interest and the second filter identifies the environmental hazards.  AIOps subsequently generates a clear, graphical representation to facilitate swift decision making.

Summary:

AIOps enables organizations to assess whether their infrastructure is at risk from wildfires or other external hazards by leveraging topological data from diverse sources and proximity analysis.

The new External Risks Observer integrates with and enhances environmental hazard data, which can then be analyzed to provide proximity-based insights - empowering teams to act more quickly.

GIS capabilities use: https://leafletjs.com/
Screenshot includes map supplied by: https://www.openstreetmap.org/copyright

LANCE FIRMS:
Terms of use: Can be used commercially. Can be used to create derivative works. Can be used to redistribute data.
Citation: IBM® acknowledges the use of data and imagery from LANCE FIRMS operated by NASA's Earth Science Data and Information System (ESDIS) with funding to LANCE FIRMS and ESDIS provided by NASA Headquarters.
Disclaimer: https://earthdata.nasa.gov/earth-observation-data/near-real-time/citation#ed-lance-disclaimer