Improved Decision Making Using Fuzzy Temporal Relationships within Intelligent Assisted Living Environments

Abstract

The overall age of the population within the United Kingdom is increasing. By 2034 it is estimated that 23% of the population will be aged 65 and over compared to 18% aged under 16. With an ageing population there is an increased requirement for formal or informal care often within established institutions. The advent of intelligent assisted living environments such as smart homes may offer a reduction in the requirement for such care whilst maintaining levels of independence and safety within individuals own homes. The use of ambient intelligent technology such as Wireless Sensor Networks can produce a number of issues, two of which we have endeavoured to address within this paper. Firstly, the nature of the hardware often used produces discrete temporal data readings which are an unreliable source of event recognition. Through the use of a derivative of Allen's temporal algebra, we have produced a method to identify events from discrete temporal information. Additionally, the construction of the sensors and topology, and the large inherent uncertainties in the areas which they are deployed can both produce inconsistent and unreliable data. This paper has formulated a method to produce a confidence level in the events that have been recorded through a comparative analysis of the variance of multiple sensor events. The method developed was further enhanced through the fuzzification of the temporal relationships to more adequately express the detail contained.