The focus of this study was to investigate an alternative and more cost effective
solution for occupancy sensing in commercial office buildings. The intended purpose of
this solution is to aid in efficient energy management. The main requirements were that
the proposed solution made use of existing infrastructure only, and provided a means to
focus on occupant location.
This research was undertaken due to current solutions making use of custom
occupancy sensors that are relatively costly and troublesome to implement. These
solutions focus mainly on monitoring environmental changes, and not the physical
locations of the occupants themselves. Furthermore, current occupancy sensing
solutions are unable to provide proximity and timing information that indicate how far an
occupant is located from a specific area, or how long the occupant resided there.
The research question was answered by conducting a proof of concept study with data
simulated in the OMNeT++ environment in conjunction with the MiXiM framework for
wireless networks. The proposed solution investigated the fidelity of existing WiFi
infrastructure for occupancy sensing, this entailed the creation of a Virtual Occupancy
Sensor (VOS) that implemented RSS-based localisation for an occupant’s WiFi
devices. Localisation was implemented with three different location estimation
techniques; these were trilateration, constrained nearest neighbour RF mapping and
unconstrained nearest neighbour RF mapping. The obtained positioning data was
interpreted by a developed intelligent agent that was able to transform this regular
position data into relevant occupancy information. This information included a distance
from office measurement and an occupancy result that can be interpreted by existing
energy management systems. The accuracy and operational behaviour of the
developed VOS were tested with various scenarios. Sensitivity analysis and extreme
condition testing were also conducted.
Results showed that the constrained nearest neighbour RF mapping approach is the
most accurate, and is best suited for occupancy determination. The created VOS
system can function correctly with various tested sensitivities and device loads.
Furthermore results indicated that the VOS is very accurate in determining room level
occupancy although the accuracy of the position coordinate estimations fluctuated
considerably. The operational behaviour of the VOS could be validated for all
investigated scenarios.
It was determined that the developed VOS can be deemed fit for its intended purpose,
and is able to give indication to occupant proximity and movement timing. The
conducted research confirmed the fidelity of WiFi infrastructure for occupancy sensing,
and that the developed VOS can be considered a viable and cost effective alternative to
current occupancy sensing solutions. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2014
| Identifer | oai:union.ndltd.org:NWUBOLOKA1/oai:dspace.nwu.ac.za:10394/15178 |
| Date | January 2014 |
| Creators | Delport, Melanie |
| Source Sets | North-West University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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