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A Wireless Sensor Node Architecture for Exploring Distributed Sensor Network Applications

Abstract—This document describes a new versatile generalpurpose
wireless sensor node architecture designed around the
OKI ARM ML67Q500x microprocessor and the IEEE 802.15.4
compliant CC2420 radio from Chipcon. This platform designed
for experimentation, educational projects and preliminary deployment
in industrial environments. The XYZ node architecture
is described in the context of a 3-D testbed recently installed at
ENALAB to facilitate wireless sensor experiments at scale. In the
next few months, this testbed will host approximately 100 wireless
devices, and it will form a flexible environment for instrumenting
and testing complex sensor network scenarios prior to their
deployment. The primary set of applications to be implemented
on the testbed includes, node localization in 3-D space, sensor
calibration and a set of controlled mobility applications such as
boundary estimation.
I. INTRODUCTION
The proliferation of wireless sensor networks and the recent
efforts for the standardization of sensor communication under
the umbrella of the IEEE 802.15.4 and Zigbee standards
are beginning to facilitate a rapidly expansion application
space. In addition to the numerous industrial control and home
automation applications, this technology carries the potential
to significantly impact the course of information technologies
in industrial and scientific applications. According to a recent
National Research Council report [1], “could well dwarf
previous milestones in information technology”.
Our research focus in this domain is the investigation of
problems where multipoint sensor measurements are fused to
make complex decision on the detection and characterization
of distributed phenomena. The main application currently
being investigated under this umbrella is the detection of
boundaries with distributed wireless sensors. Such detection
of delineation between regions in large physical spaces is a
highly desirable capability across many domains. Scientists,
regulating authorities and public safety officials are interested
in studying the propagation of gases and fluids in physical
environments. Example applications include the tracking and
monitoring of poisonous gases, oil and chemical spills in
terrestrial and marine environments, algae blooms and fire
spreading. While the study of such distributed phenomena can
sometimes be studied using the remote sensing capabilities
of satellites or radars, the observation of these phenomena
becomes more challenging in obstructed environments such as
urban settings, dense forests and indoor environments. Remote
sensing is also practically infeasible with some types of
chemical sensing where sensors are required to have physical
contact with the chemicals being sensed. Despite the fact that
boundary estimation has been studied in other domains, its
application over large areas imposes a new set of challenges
that remain to be addressed. An overview of the challenges
associated with boundary estimation given in [2] suggests that
this problem in also inherently coupled with several other
challenging problems such as that of node localization, sensor
calibration, time synchronization and clustering.
The aggregate of these problems calls for the consideration
of both data fusion algorithms for the interpretation of sensor
information, and highly integrated platforms that offer reliable
functionality at low cost and minimal power consumption.
Our design of the XYZ node based on commercial off-theshelf
components strives to attain a middle-ground between a
small form factor, low power device and the current needs for
experimental evaluation of sensor network systems. Despite
the availability of a few wireless sensor nodes in the community
we have decided to develop our own to facilitate specific
experiments that we cannot conduct with existing nodes. These
reasons include the need to have sensor peripherals directly
connected to the microcontroller, small form factor for wearable
applications, 32-bit computation resources for running
optimization and sensor fusion algorithms, low cost and long
term ultra low power sleep modes. Our implementation is
based around the OKI ARM ML67Q500x microcontroller, that
provides ample computational resources for data fusion and
the IEEE 802.15.4 and Zigbee compliant CC 2420 radio from
Chipcon. With this platform we are in the process of building
a state-of-the-art 3D testbed that will allow us to develop
and experiment with scalable sensor network applications. An
overview of this testbed is described in the next section.



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