Presenter Information

Kim StuartFollow

Degree Name

Master of Computer Science and Systems (MCSS)

Department

Institute of Technology

Streaming Media

Location

UW Tacoma - William W. Philip Hall, Milgard Assembly Room

Event Website

http://guides.lib.uw.edu/tactalks

Start Date

18-5-2017 6:05 PM

End Date

18-5-2017 6:10 PM

Abstract

As buildings and devices becoming increasingly “smarter,” the need for more data requires more sensors in order to provide more precise and insightful interpretations of daily applications. As a result, servers are required to become stronger and more advanced in order to compute and process the abundance of data arriving at high frequencies and to meet real-time requirements and expectations. The naive approach would be to buy new, or to upgrade, existing servers. This can potentially become costly and inconvenient for end users. In addition, placement of new equipment is constrained by building blueprints that must meet safety compliance, and in order to be efficient, the equipment must be placed in the vicinity of the sensors. However, the need for additional or upgraded servers can be prevented if you can effectively direct the incoming data and reroute it into proper queues before computation.

My research compares the computation of incoming data across multiple software topology designs. The system will work under various workload intensities depending on the way data is routed. However, the trade-off of changing the way the data is routed could potentially mean a loss of accuracy. While keeping accuracy of computations a high priority, one component of my research will be implementing a system that can compute occupancy predictions on environmental sensor data that is compared across multiple software topology designs, to determine under which conditions we can reduce server workload intensity while still preserving accuracy.

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May 18th, 6:05 PM May 18th, 6:10 PM

An Analysis of Real Time Streaming of Sensor Fusion in Smart Buildings

UW Tacoma - William W. Philip Hall, Milgard Assembly Room

As buildings and devices becoming increasingly “smarter,” the need for more data requires more sensors in order to provide more precise and insightful interpretations of daily applications. As a result, servers are required to become stronger and more advanced in order to compute and process the abundance of data arriving at high frequencies and to meet real-time requirements and expectations. The naive approach would be to buy new, or to upgrade, existing servers. This can potentially become costly and inconvenient for end users. In addition, placement of new equipment is constrained by building blueprints that must meet safety compliance, and in order to be efficient, the equipment must be placed in the vicinity of the sensors. However, the need for additional or upgraded servers can be prevented if you can effectively direct the incoming data and reroute it into proper queues before computation.

My research compares the computation of incoming data across multiple software topology designs. The system will work under various workload intensities depending on the way data is routed. However, the trade-off of changing the way the data is routed could potentially mean a loss of accuracy. While keeping accuracy of computations a high priority, one component of my research will be implementing a system that can compute occupancy predictions on environmental sensor data that is compared across multiple software topology designs, to determine under which conditions we can reduce server workload intensity while still preserving accuracy.

https://digitalcommons.tacoma.uw.edu/tactalks/2017/spring/4