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GeoAI - The evolution of Artificial Intelligence

Leveraging AI for the common good

Effective public health and emergency response requires the right data in the hands of decision makers at the right time. As the available data that informed those decisions grew, geospatial technologies have been called upon to synthesize and visualize broad sets of data. Geo is well designed to do so. 


However, the quantity of data has increased so much in recent years, and is growing at an exponential rate seemingly on a daily basis as new satellites and sensor systems come online, that public health and emergency response managers find themselves inundated with data, and often need guidance on the most critical, time-sensitive decisions that must be made - and be presented with a synthesis of available data informing those decisions.’s GeoAI-powered Health Risk Index does exactly this.


The Health Risk Index identifies a priori the health and medical needs of a disaster impacted population. The GeoAI solution goes one step further to prioritize the most critical actions and decisions emergency response managers must make along with the information necessary to support those actions and facilitates taking quick action.



For example, through a simple interface (shown below left), users can select the area and granularity of interest and immediately receive insights on response needs (below right). The output can be tailored to meet specific needs, and can include a host of shareable online formats, a printed report, and integration in an emergency response workflow, to ensure key response information is sent to specific response personnel.


The Health Risk Index was developed with input from FEMA, the USGS, and with data from authoritative sources, partially including NASA, NOAA, the Census, the CDC, and other federal sources. Data from alternate sources can also be included in the analysis to meet the unique needs of specific disaster scenarios.


The solution also leverages’s proprietary SDOH Risk Index to understand the unique risks to vulnerable populations based on social characteristics and population demographics. This allows emergency managers to ensure an equitable response to the natural disaster.

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