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Integration of a Wireless Sensor-actuator Network and an FPGA
for Intelligent Inhabited Environments
Javier Echanobe, Estibaliz Asua and Inés del Campo
1
Department of Electricity and Electronics, University of the Basque Country, 48940, Leioa, Spain
Keywords: Wireless Sensor Network, FPGA, Intelligent Environments, Neurofuzzy Systems.
Abstract: Wireless Sensor and Actuator Networks together with processing elements named intelligent agents are
achieving great importance in environmental control. The trend in this field points to implement small, low
power, low cost and fast systems, which is in general, hard to achieve. In this paper, an electronic system
that consists of several sensors and actuators and a FPGA endowed with Neurofuzzy based intelligent
algorithms is presented. The purpose of this work is to demonstrate the effectiveness of the FPGA to
provide intelligence to a Wireless Sensor and Actuator Networks. As example of application, a system
which acts over a floor lamp intensity and an opening of a window in an autonomous way is presented. This
autonomous action is calculated by the FPGA based on several parameters provided by the network
(temperature, humidity and luminosity). By integrating the low power WSAN and the FPGA-based
Intelligent Agent, a small, low power, low cost high-performance intelligent environment system is
achieved.
1 INTRODUCCTION
In the last decade, the research area known as
Wireless Sensor and Actuator Networks (WSAN) has
rapidly grown mainly due to several technological
advances such as the hardware miniaturization, the
maturity of the wireless technologies and protocols,
and also the sensor integration. The area is at present
quite mature for small networks and hence, the
number of application fields where WSAN can be
found is very large (Dargie, 2010): Environmental
Control (Ambient Intelligence, Home Automation,
Intelligent Environments) (Cook, 2009), Body Area
Networks (health care, telemedicine, elder care,
remote patient monitoring) (Acampora, 2014),
Machine-to-Machine Communications, Internet of
Things (IoT), surveillance, manufacturing, etc.
Together with the sensor network, a processing
counterpart to handle the amount of information
gathered by the sensors is often required. In many of
cases, these processing elements must provide, in
autonomous scenarios, a response which is sent back
to the actuators in the network. In addition, many
applications demand those elements to be small, low
power, low cost but fast enough to provide real-time
response, which is in general hard to achieve: i.e.,
intelligence demands high computational power and
therefore large size elements with high power
consumption.
In order to face those requirements, in Inhabited
Intelligent Environments (also called Ambient
Intelligence Environments), where a number of
sensors and intelligent elements have to be deployed
throughout the environment without the user being
aware of its presence, Intelligent Agents are
proposed (Jang, 1997). Intelligent Agents are
autonomous units of intelligence whose actions are
driven by a goal; they are able to take decisions
based on their internal state and information
collected from the environment. In this sense, soft
computing approaches (Doctor, 2005), mainly fuzzy
systems and neural networks are commonly used.
In this paper we propose an electronic system to
control ambient parameters in an intelligent
inhabited environment. The system is based on a
WSAN, which receives/sends data from/to the
environment and on a FPGA which addresses the
Intelligent Agent. The Intelligent Agent
implemented on the FPGA is, in turn, based on
several Neurofuzzy systems whose ability to learn
and model the dynamics of smart environments has
been demonstrated by the authors in recent works
(Del Campo, 2012).
331
Echanobe J., Asua E. and del Campo I..
Integration of a Wireless Sensor-actuator Network and an FPGA for Intelligent Inhabited Environments.
DOI: 10.5220/0004680703310336
In Proceedings of the 3rd International Conference on Sensor Networks (SENSORNETS-2014), pages 331-336
ISBN: 978-989-758-001-7
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)