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Open AccessArticle

Opening up the Black Box of Sensor Processing Algorithms through New Visualizations

Department of Integrated Systems Engineering, The Ohio State University, Columbus, OH 45420, USA
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Academic Editors: Kamran Sedig and Paul Parsons
Informatics 2016, 3(3), 16; https://doi.org/10.3390/informatics3030016
Received: 7 May 2016 / Revised: 5 September 2016 / Accepted: 18 September 2016 / Published: 21 September 2016
(This article belongs to the Special Issue Human–Information Interaction)
Vehicles and platforms with multiple sensors connect people in multiple roles with different responsibilities to scenes of interest. For many of these human–sensor systems there are a variety of algorithms that transform, select, and filter the sensor data prior to human intervention. Emergency response, precision agriculture, and intelligence, surveillance and reconnaissance (ISR) are examples of these human–computation–sensor systems. The authors examined a case of the latter to understand how people in various roles utilize the algorithms output to identify meaningful properties in data streams given uncertainty. The investigations revealed: (a) that increasingly complex interactions occur across agents in the human–computation–sensor system; and (b) analysts struggling to interpret the output of “black box” algorithms given uncertainty and change in the scenes of interest. The paper presents a new interactive visualization concept designed to “open up the black box” of sensor processing algorithms to support human analysts as they look for meaning in feeds from sensors. View Full-Text
Keywords: autonomy; automation; data analytics; visual analytics; human–computer interaction; visualization; sensor networks; statistical graphics; visual design autonomy; automation; data analytics; visual analytics; human–computer interaction; visualization; sensor networks; statistical graphics; visual design
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MDPI and ACS Style

Morison, A.M.; Woods, D.D. Opening up the Black Box of Sensor Processing Algorithms through New Visualizations. Informatics 2016, 3, 16.

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