Affiliations: [a] Department of Informatics, University of Piraeus, Piraeus, Greece | [b] Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Panepistimiopolis, Ilissia, Athens, Greece
Correspondence:
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Corresponding author: Konstantina Chrysafiadi, Department of Informatics, University of Piraeus, Piraeus, Greece. E-mail: [email protected].
Abstract: Many humans deal with problems that concern episodic memory decline. These problems can cause annoying, and sometimes, dangerous incidents, like failing to recall the name of a friend or forgetting to take a medicine or turn off the cooker. Concerning the above, this paper presents a fuzzy rule-based mechanism that generates emergency alerts when a dangerous situation is caused by an inconsistency in the human’s actions in the home environment. In such a way, the system protects persons with episodic memory decline problems or lapses of attention from dangerous situations that may be caused by their memory disorder and allows them to complete an everyday activity. For the paper’s needs the application of the presented mechanism is limited to the usage of a cooker. The system takes as input the time, the size and the content of the pot that is used to the cooker, calculates the degree of emergency and describes it using fuzzy sets and, finally, applies rules over the fuzzy sets to generate alert messages that notify the monitored person about the next action that s/he has to do in order to complete a particular activity. For the evaluation of the system, we have developed a simulation program that asks users to complete some activities during a specific time period. The system embeds the presented fuzzy rule-based mechanism and monitors the user’s actions and generated alerts, which concern the usage of the stove burner. The simulation software was used by 15 users. Their reactions and opinions about the system’s alerts and the assistance it offers, are positive.
Keywords: Episodic memory decline problems, smart home assistance, fuzzy logic
