Enhancing UAS Sensor Operators' Performance in Constrained Network Environments

Benjamin Purman, Daryn Dever, Bridget Furlong, Matthew Nulle


Presented at the Vertical Flight Society 79th Annual Forum & Technology Display
Crew Stations and Human Factors Technical Session - Paper 1173
10 pages

https://doi.org/10.4050/F-0079-2023-18613

 

Abstract:
Unmanned aerial systems (UASs) are currently utilized to for a wide range of intelligence, surveillance, and reconnaissance (ISR) tasks. However, current operations require transmitting video data from the UAS platform to sensor operators at the ground control station (GCS) in realtime. This approach limits operations to environments where a high-bandwidth, low-latency data connection is available between the UAS platform and the GCS. Our paper examines the effectiveness of Forward Observer, an architecture which mitigates these networking limitations for UAS sensor operators. Forward Observer is designed around the notion of 'bursty' data products. Bursty data products are compressed image files that summarize events in UAS video stream data. To generate these products, Forward Observer incorporates on-board analytics (e.g., object detection, semantic labeling) to identify content of interest, and it incorporates recommendation algorithms to prioritize content to send to the operator. To examine Forward Observer's effectiveness, experienced sensor operators engaged in an ISR task under three conditions: (1) immediate access to bursty data products; (2) limited bandwidth for bursty data product transmission; and (3) Forward Observer capabilities in a limited bandwidth. Results across all research questions found that, with Forward Observer, participants had greater time task efficiency, the amount of data needed for their task was significantly less, and confidence generally increased after approximately six minutes in the ISR task. Implications of these results show that Forward Observer's bursty data products and on-board analytics and prioritization capabilities positively contribute to sensor operators' ISR task efficiency and success.

 

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