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Use of Local Intelligence to Reduce Energy Consumption of Wireless Sensor Nodes in Elderly Health Monitoring Systems
School of Information Technology and Systems Management, Salzburg University of Applied Sciences, Puch/Salzburg, Austria.ORCID iD: 0000-0002-1122-6908
Department of Applied Computing, Federal University of Santa Maria, Santa Maria, Brazil.ORCID iD: 0000-0003-4655-8889
School of Information Technology and Systems Management, Salzburg University of Applied Sciences, Puch/Salzburg, Austria.
School of Information Technology and Systems Management, Salzburg University of Applied Sciences, Puch/Salzburg, Austria.
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2014 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 14, no 3, 4932-4947 p.Article in journal (Refereed) Published
Abstract [en]

The percentage of elderly people in European countries is increasing. Such conjuncture affects socio-economic structures and creates demands for resourceful solutions, such as Ambient Assisted Living (AAL), which is a possible methodology to foster health care for elderly people. In this context, sensor-based devices play a leading role in surveying, e.g., health conditions of elderly people, to alert care personnel in case of an incident. However, the adoption of such devices strongly depends on the comfort of wearing the devices. In most cases, the bottleneck is the battery lifetime, which impacts the effectiveness of the system. In this paper we propose an approach to reduce the energy consumption of sensors’ by use of local sensors’ intelligence. By increasing the intelligence of the sensor node, a substantial decrease in the necessary communication payload can be achieved. The results show a significant potential to preserve energy and decrease the actual size of the sensor device units. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

Place, publisher, year, edition, pages
Basel: Multidisciplinary Digital Publishing Institute , 2014. Vol. 14, no 3, 4932-4947 p.
Keyword [en]
sensors, wireless, energy, AAL, health care
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:hh:diva-24846DOI: 10.3390/s140304932ISI: 000336783300059PubMedID: 24618777Scopus ID: 2-s2.0-84896480640OAI: oai:DiVA.org:hh-24846DiVA: diva2:704835
Funder
Knowledge Foundation
Available from: 2014-03-13 Created: 2014-03-13 Last updated: 2017-12-05Bibliographically approved

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