The need for the ability to autonomously maintain persistent surveillance of weather events over a selected region of interest on a continuous basis is greater than ever. The HELIOS project looks to fill the void in weather data dissemination of real-time coordinated ground-based video around a weather event by use of an integrated network of cameras and enhanced geospatial processing algorithms.

The need is stronger than ever to be able to autonomously maintain persistent surveillance of weather events over a selected region of interest on a continuing basis, as well as an automated method of tasking visual assets on weather activity.

This research paper investigates a real-time adaptive surveillance system that provides live, targeted weather event video specific to severe weather events, as well as additional algorithmic capabilities to detect specific weather phenomena from ground video. Additional services include archival and streaming of weather phenomena to customers using existing proprietary systems.

NWS EMWIN rebroadcast data is used to provide storm location, severity, bearing, etc. of a weather event. The Helios system re-fixes or selects appropriate viewing existing camera infrastructure (traffic, etc.) on the progressing storm from multiple vantage points. This data is fed to a video archiving, exploitation and dissemination system and live/archived video products are produced real time. The fusion of coordinated video-based camera networks is provided via the system.

We present the results from our simulations to demonstrate the feasibility of the proposed technique with video collected from a prototype persistent surveillance system. Our approach maintains compatibility with existing GIS databases and provides an integrated solution for multi-source video fusion of localized weather events.