@article {s140304932,
	title = {Use of Local Intelligence to Reduce Energy Consumption of Wireless Sensor Nodes in Elderly Health Monitoring Systems},
	journal = {Sensors},
	volume = {14},
	number = {3},
	year = {2014},
	note = {n/a},
	pages = {4932{\textendash}4947},
	abstract = {<p>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{\textquoteright} by use of local sensors{\textquoteright} 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.</p>
},
	issn = {1424-8220},
	doi = {10.3390/s140304932},
	url = {http://www.mdpi.com/1424-8220/14/3/4932},
	author = {Lampoltshammer, Thomas J. and Pignaton de Freitas, Edison and Nowotny, Thomas and Plank, Stefan and da Costa, Jo{\~a}o Paulo Carvalho Lustosa and Larsson, Tony and Heistracher, Thomas}
}
