The National Institute of Standards and Technology (NIST) is seeking to identify industry and academic efforts of automated data identification and classification of unknown or unlabeled data. In addition, NIST is interested in the availability of certain data that would be relevant for a first responder’s mission (e.g. personal area network sensor data, smart building data, and smart city data) and would be interested to know what types of open data are available in those categories, and who is publishing that data.


Throughout the U.S. today, there are numerous examples of how the analysis of data is being used to improve our lifestyle. From utilizing networked energy meters to reduce the amount of energy consumption in a city, to using artificial intelligence to scan for anomalies in an MRI, the results that can be achieved through the automated analysis of data can be more accurate and more instantaneous than those driven solely by human capacity.

However, even as sensors become integrated into the most ubiquitous household and personal care devices, finding a device that meets the situational awareness needs of a first responder is difficult to come by. A first responder often requires information that spans many market silos. Data from a diversity of sensor types and data types that help first responders safely accomplish their mission includes, but is not limited to:

  • Navigation data (e.g. fastest route to a building)
  • Location data (e.g. building’s ingress/egress points, location of personnel at the scene)
  • Biometric data (e.g. heart rate, blood pressure, positioning data of personnel or victims at the scene)
  • Environmental data (e.g., weather information, wind speed and precipitation, detection of hazardous materials in the area)

Because of the wide breadth of information used, data traditionally used by healthcare, industry, and household commercial applications could all be deemed important depending on the first responder’s mission.

In order to fully articulate a first responder’s environment in the field, multiple systems would need to be utilized. Furthermore, even if several systems could be utilized together, accessing and interpreting data amongst different platforms would be time consuming and potentially overwhelming to an individual who needs their attention focused on life-saving efforts. Therefore, NIST would like to examine how technologies are being used to bring together multiple sources of disparate data for display and interpretation.  Furthermore, NIST would like to identify any existing sources of heterogenous data that could be used to demonstrate a first responder’s environment in the field.

Possible Solution Areas

  • Artificial Intelligence Algorithms
  • Research or solutions that classify information from disparate data sources / systems
  • Research or solutions that identify different types of data
  • Work that is performing classification of real-time or near real-time data (such as sensor data) or that are aiming to reach that eventual goal
  • Open datasets that contain information relevant to a first responder’s situational awareness


Desired Outcome of the Solution

Open to various types of collaborations or partnership opportunities at any development stage, including, but not limited to, partnerships with cities or entities that have available datasets.

Field of Use and Intended Applications

Solutions will provide background into the work that is being done to try to evolve it into a prize challenge for the first responder use case.