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

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

As sensing technology develops, it plays an important role in context-aware systems. Using context information improves the user experience of ubiquitous computing. One use of sensed information is to detect a meeting in progress in an office or a conference room. In our system, sensors gather context information from an office environment and act as a presence user agent to update a presence server with context changes. These context changes can be utilized by context-aware services. The presence messaging uses the SIP for Instant Messaging and Presence Leveraging Extensions (SIMPLE) protocol and the presence information is described in eXtensible Makeup Language (XML) format. In this thesis we present a context-sensing component that recognizes meetings in a typical office environment. A context-aware system is able to use this occupancy information to infer that the room is empty, an individual is alone in the room, or a meeting is taking place in the meeting room. Context-aware services might utilize this environmental information to automatically forward a user's incoming calls to their voice mail server. This and other example applications were developed to show the usefulness of this context information. / Så som sensor tekniken utvecklas, spelar de en viktig roll i kontextmedvetna system. Genom att använda kontextuell information förbättras användarupplevelsen av 'ubiquitous computing'. Ett användningsområde för sensorinsamlad information är att upptäcka ett möte som pågår i ett kontor eller konferenslokal. I vårt system samlar sensorer information från en kontorsmiljö och uppdaterar en närvaroserver med kontextuella förändringar. Dessa förändringar kan sedan utnyttjas av kontextmedvetna tjänster. För att förmedla den närvarostatusen använder närvaroservern SIP och ’Presence Leveraging Extensions’ (SIMPLE) protokoll. Närvaro information levereras i 'eXtensible Makeup Language' (XML) format. I denna avhandling presenterar vi en kontextsensorkomponent som känner av möten i en typisk kontorsmiljö. Ett kontextmedvetet system kan använda denna komponent för att dra slutsatsen att lokalen är tom, en person är ensam i lokalen, eller ett möte äger rum i lokalen. Kontextmedvetna tjänster kan utnyttja denna information för att automatiskt vidarebefordra en användares inkommande samtal till deras röstbrevlåda. Detta och andra exempel, har utvecklats för att visa nyttan av denna kontextuella information.

Vision systems have become ubiquitous. They are used for traffic monitoring, elderly care, video conferencing, virtual reality, surveillance, smart rooms, home automation, sport games analysis, industrial safety, medical care etc. In most vision systems, the data coming from the visual sensor(s) is processed before transmission in order to save communication bandwidth or achieve higher frame rates. The type of data processing needs to be chosen carefully depending on the targeted application, and taking into account the available memory, computational power, energy resources and bandwidth constraints. In this dissertation, we investigate how a vision system should be built under practical constraints. First, this system should be intelligent, such that the right data is extracted from the video source. Second, when processing video data this intelligent vision system should know its own practical limitations, and should try to achieve the best possible output result that lies within its capabilities. We study and improve a wide range of vision systems for a variety of applications, which go together with different types of constraints. First, we present a modulo-PCM-based coding algorithm for applications that demand very low complexity coding and need to preserve some of the advantageous properties of PCM coding (direct processing, random access, rate scalability). Our modulo-PCM coding scheme combines three well-known, simple, source coding strategies: PCM, binning, and interpolative coding. The encoder first analyzes the signal statistics in a very simple way. Then, based on these signal statistics, the encoder simply discards a number of bits of each image sample. The modulo-PCM decoder recovers the removed bits of each sample by using its received bits and side information which is generated by interpolating previous decoded signals. Our algorithm is especially appropriate for image coding. / Morbee, M. (2011). Optimized information processing in resource-constrained vision systems. From low-complexity coding to smart sensor networks [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/12126