Sensor networks in workplaces: correlating comfort and productivity

van der Valk, Steven, Myers, Trina, Atkinson, Ian, and Mohring, Karl (2015) Sensor networks in workplaces: correlating comfort and productivity. In: Proceedings of 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP). pp. 1-6. From: IEEE ISSNIP 2015: 2015 IEEE Tenth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, 7-9 April 2015, Singapore.

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Current designs of modern office workplaces focus on health and safety standards but minimally address worker comfort and satisfaction. However, physical and mental wellness indicators directly affect the output of the worker according to existing studies that illustrate the strong relationship between workplace conditions and productivity. Personal and environmental sensed data can inform smarter workplace design and operations to potentially increase productivity and benefit all stakeholders in the modern workplace. This paper introduces a project that will measure environmental variables and personal physical and mental parameters of employees in different office environments to determine correlations with productivity. In-vivo measurements are obtained via a combination of environmental sensor modules and personal monitoring devices that record the interplay between variables affecting comfort and productivity in a workplace. The office spaces included in the study vary in age, heating/cooling management systems and the internal environmental efficiency of the buildings' design. This paper presents the pilot study that obtained bio-metric data from body area network sensors for each participant and environmental data on the state for workplace including thermal, humidity and light measurements. The participants were given self-reflective micro-surveys on productivity during the time of data collection. The preliminary results indicate that despite climate controlled conditions (i.e., a sealed air conditioned building), natural variance and sub-optimal conditions directly affected reported productivity.

Item ID: 39199
Item Type: Conference Item (Research - E1)
ISBN: 978-1-4799-8054-3
Keywords: Internet of Things; sensor networks; personal monitoring device; productivity monitoring
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Date Deposited: 16 Jun 2015 01:08
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0805 Distributed Computing > 080503 Networking and Communications @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970110 Expanding Knowledge in Technology @ 100%
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