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Measuring Cities with Software-Defined Sensors 被引量:2
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作者 Charlie Catlett Pete Beckman +4 位作者 Nicola Ferrier Howard Nusbaum michael e.papka Marc G.Berman Rajesh Sankaran 《Journal of Social Computing》 2020年第1期14-27,共14页
The Chicago Array of Things(AoT)project,funded by the US National Science Foundation,created an experimental,urban-scale measurement capability to support diverse scientific studies.Initially conceived as a traditiona... The Chicago Array of Things(AoT)project,funded by the US National Science Foundation,created an experimental,urban-scale measurement capability to support diverse scientific studies.Initially conceived as a traditional sensor network,collaborations with many science communities guided the project to design a system that is remotely programmable to implement Artificial Intelligence(AI)within the devices—at the“edge”of the network—as a means for measuring urban factors that heretofore had only been possible with human observers,such as human behavior including social interaction.The concept of“software-defined sensors”emerged from these design discussions,opening new possibilities,such as stronger privacy protections and autonomous,adaptive measurements triggered by events or conditions.We provide examples of current and planned social and behavioral science investigations uniquely enabled by software-defined sensors as part of the SAGE project,an expanded follow-on effort that includes AoT. 展开更多
关键词 SENSORS edge computing computer vision urban science
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