Akhlaghinia, MJ, 2010. Occupancy monitoring and prediction in ambient intelligent environment. PhD, Nottingham Trent University.
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Abstract
Occupancy monitoring and prediction as an influential factor in the extraction of occupants' behavioural patterns for the realisation of ambient intelligent environments is addressed in this research. The proposed occupancy monitoring technique uses occupancy detection sensors with unobtrusive features to monitor occupancy in the environment. Initially the occupancy detection is conducted for a purely single-occupant environment. Then, it is extended to the multipleoccupant environment and associated problems are investigated. Along with the occupancy monitoring, it is aimed to supply prediction techniques with a suitable occupancy signal as the input which can enhance efforts in developing ambient intelligent environments. By predicting the occupancy pattern of monitored occupants, safety, security, the convenience of occupants, and energy saving can be improved. Elderly care and supporting people with health problems like dementia and Alzheimer disease are amongst the applications of such an environment. In the research, environments are considered in different scenarios based on the complexity of the problem including single-occupant and multiple-occupant scenarios. Using simple sensory devices instead of visual equipment without any impact on privacy and her/his normal daily activity, an occupant is monitored in a living or working environment in the single-occupant scenario. ZigBee wireless communication technology is used to collect signals from sensory devices such as motion detection sensors and door contact sensors. All these technologies together including sensors, wireless communication, and tagging are integrated as a wireless sensory agent.
Item Type: | Thesis |
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Creators: | Akhlaghinia, M.J. |
Date: | 2010 |
Divisions: | Schools > School of Science and Technology |
Record created by: | EPrints Services |
Date Added: | 09 Oct 2015 09:35 |
Last Modified: | 09 Oct 2015 09:35 |
URI: | https://irep.ntu.ac.uk/id/eprint/281 |
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