Friday, August 30, 2019

Message Quality on Entity Location and Identification Performance

At the recent SPIE Optics + Photonics Conference we had a paper entitled "The Impact of Message Quality on Entity Location and Identification Performance in Distributed Situational Awareness." In the paper we discuss the importance of detecting a person or object in complicated and dynamic environments (such as for search and rescue or law enforcement). However, with the growth in sensors and the resulting information from them, the identification and tracking of objects is becoming more difficult. As a result, in this  paper we provide and assess a method to identify objects and the interactions between agents (human or technological) within a collaborative system for improving situational awareness. Below we provide the abstract to the paper, some images of the system along with some results and a link to the paper.

Location and time are critical to the success of many organizations’ missions. Sensors, software, processors, vehicles, and human analysts work together to accomplish these tasks of detecting and identifying specific entities as quickly as possible for these missions. This work aims to make a contribution by providing a team-based detection and identification performance model incorporating the theory of Distributed Situational Awareness (DSA) and its effect on completing a specific task. The task being the ability to detect and identify a specific entity within a complex urban environment. Conditions to accomplish the task is the utilization of two unmanned aerial vehicles mounted with electro-optical sensors, operated by two analysts, creating a team to execute this task. Our results provide an additional resource on the how technology and training might be utilized to find the best performance given these certain conditions and missions. A highly trained team might improve their performance with this technology, or a team with low training could perform at a high level given the appropriate technology in limited time scenarios. More importantly, the model presented in this paper provides an evaluation tool to compare new technologies and their impact on teams. Specifically, it enables answering questions, such as: is an investment in new technology appropriate if investing in additional training produces the same performance results? Future performance can also be evaluated based on the team’s level of training and use of technology for these specific tasks.

Keywords: Situational Awareness, Identification, Detection, Sensors, Training, Team.

Snapshot from FOCUS depicting the flight paths of the unmanned aerial vehicles (UAVs) and sensor field of view in green.

LiDAR map of the city of Samarra, Iraq utilized in FOCUS for this experiment.

Identification of Situational Awareness (SA) level data sets - baseline. Histogram and distribution curve.

Full Reference:
Bates, C.T., Croitoru, A., Crooks, A.T. and Harclerode, E. (2019), The Impact of Message Quality on Entity Location and Identification Performance in Distributed Situational Awareness, Proceedings of the SPIE Optics + Photonics, San Diego, CA. Paper 11137-64 (pdf)

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