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In modern office environments, lighting systems, heating/cooling system and personal computers are the main energy consumers. Our aim is to minimise use of energy resources in the office environments while still taking account of user preferences and comfort. To achieve the goal, a data collection system is designed and built. This required a wireless sensor network to monitor a wide range of ambient conditions and user activities, and a software agent to monitor user's personal computer activities. Collected data from different users are gathered into a central database and converted into a meaningful format for description of the worker's Activity of Daily Working (ADW) and office environment conditions. An activity recognition model using an event-driven model is proposed to recognise a worker's activities during times when the office is occupied or unoccupied. The experimental results demonstrate the model recognises a worker's activities and can classify them into six categories (home, lunch, short break, out of office duties, not using computer and using computer) with accuracy of more than 90%.
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