Title:
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Sensor distribution optimisation in smart environments
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The worldwide human population is set to inflate by over 2 billion within the
coming decades, with the ratios of old and older old forecast to enlarge rapidly in both
developed and developing countries. Chronic and progressive disease and disability are
positively correlated with advanced ageing. Global financial instability, fiscal deficits,
high unemployment and an enormous predicted energy shortage represent the global
backdrop to the task of providing safe and secure accommodation and/or medical
supervision to elderly cohorts, both now and in the future.
Smart homes are living spaces facilitated with technology that allow individuals to
remain in their own homes for longer, rather than be institutionalised. Sensors are the
fundamental physical layer with any smart home as the data they generate is used to
inform decision support systems, which is turn facilitate appropriate actuator actions.
The appropriateness of actuator actions is thus crucial in providing safety and security
to a smart home inhabitant. The positioning, amount(s) and field of view(s) of sensors is
therefore a fundamental characteristic of a smart home. Contemporary smart home
sensor distribution is aligned to either a) a total coverage approach, or b) a human
assessment approach. These methods for sensor arrangement are not data driven
strategies, are unempirical, and frequently irrational.
The overall aim of this thesis was to develop and test a novel sensor distribution
paradigm for the optimisation of resources. Four chronological studies were conducted.
Studies 1 and 2 investigated the problem of how to acquire inhabitant spatial frequency
data from a smart home environment, which was robust to the range of ambient
conditions prevalent in an indoor scene, unobtrusive, efficient and which provided
privacy to the inhabitant and their home. Studies 3 and 4 investigated what methods
could be applied to these spatial frequency data to determine the most optimal sensor
distribution per inhabitant, unique to each inhabitant’s movement behaviour and
environmental physicalities. These investigations propose novel application of existing
methods. In addition, the presented sensor distribution optimisation paradigm is
proposed as a novel concept in the implementation and dissemination of smart home
technology.
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