Reactive, proactive, and extensible situation-awareness in ambient assisted living
| Autor: | Iara Augustin, Alencar Machado, Vincius Maran, Leandro Krug Wives, Jos Palazzo Moreira de Oliveira |
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| Rok vydání: | 2017 |
| Předmět: |
User profile
Ambient intelligence Activities of daily living Situation awareness Computer science business.industry General Engineering Cognition 02 engineering and technology Proactivity Computer security computer.software_genre Expert system Computer Science Applications Identification (information) Risk analysis (engineering) Knowledge base Artificial Intelligence 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business computer |
| Zdroj: | Expert Systems with Applications. 76:21-35 |
| ISSN: | 0957-4174 |
| DOI: | 10.1016/j.eswa.2017.01.033 |
| Popis: | The identification and prediction of situations in smart houses.An approach developed with the principles of reactive and proactive behavior.A case study presented with sensors and appliances.The proactivity and reasoning about uncertainty supported by probabilistic ontology. Considering that the world population is aging, health-support issues are in evidence, and many dangerous situations concerning users in their living environment may arise. This paper presents an approach to allow Ambient Assisted Living (AAL) systems to identify and predict situations that may endanger users in their living environment. Elderly people generally have difficulties to perform daily activities as using some electronic device, cooking, dressing among others. This paper offers an alternative to acquire comprehension of a former person's behavioral providing this knowledge when cognitive impairments will occur. This is a significant improvement to traditional expert systems applied to AAL as the handling of the knowledge base is adapted to the failing users behavior. We consider the user profile dynamics where new and different situations not initially planned in the development of the systems may occur. This approach was developed considering the principles of reactive and proactive behavior and the extensibility capacity of the system. Systems developed following the above-described principles can react to the current situations and anticipate proactively a dangerous situation eliminating it or controlling its impact. The approach is evaluated and verified by a case study where unwanted, dangerous situations were created and subsequently detected. The case study is based on a simulated smart house fulfilled with sensors and appliances. An application was build based on the developed approach, and it was capable of choosing the most appropriate actions to solve the unwanted situations. The main contributions of the present work are the identification and prediction of situations in smart houses, an approach developed with the principles of reactive and proactive behavior validated with a case study and supported by a probabilistic ontology. |
| Databáze: | OpenAIRE |
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