27-06-2012, 05:34 PM
Wireless Sensor Networks for Habitat Monitoring
[attachment=25838]
ABSTRACT
We provide an in-depth study of applying wireless sensor
networks to real-world habitat monitoring. A set of system
design requirements are developed that cover the hardware
design of the nodes, the design of the sensor network, and
the capabilities for remote data access and management. A
system architecture is proposed to address these requirements
for habitat monitoring in general, and an instance of
the architecture for monitoring seabird nesting environment
and behavior is presented.
INTRODUCTION
Habitat and environmental monitoring represent a class
of sensor network applications with enormous potential benefits
for scientific communities and society as a whole. Instrumenting
natural spaces with numerous networked microsensors
can enable long-term data collection at scales and
resolutions that are difficult, if not impossible, to obtain otherwise.
The intimate connection with its immediate physical
environment allows each sensor to provide localized measurements
and detailed information that is hard to obtain
through traditional instrumentation.
HABITAT MONITORING
Researchers in the Life Sciences are becoming increasingly
concerned about the potential impacts of human presence in
monitoring plants and animals in field conditions. At best it
is possible that chronic human disturbance may distort results
by changing behavioral patterns or distributions, while
at worst anthropogenic disturbance can seriously reduce or
even destroy sensitive populations by increasing stress, reducing
breeding success, increasing predation, or causing a
shift to unsuitable habitats. While the effects of disturbance
are usually immediately obvious in animals, plant populations
are sensitive to trampling by even well-intended researchers,
introduction of exotic elements through frequent
visitation, and changes in local drainage patterns through
path formation.
SYSTEM ARCHITECTURE
We now describe the system architecture, functionality
of individual components and how they operate together.
We explain how they address the requirements set forth in
Section 2.
We developed a tiered architecture. The lowest level consists
of the sensor nodes that perform general purpose computing
and networking in addition to application-specific
sensing. The sensor nodes may be deployed in dense patches
that are widely separated. The sensor nodes transmit their
data through the sensor network to the sensor network gateway.
The gateway is responsible for transmitting sensor
data from the sensor patch through a local transit network
to the remote base station that provides WAN connectivity
and data logging. The base station connects to database
replicas across the internet. Finally, the data is displayed
to scientists through a user interface. Mobile devices, which
we refer to as the gizmo, may interact with any of the networks
– whether it is used in the field or across the world
connected to a database replica. The full architecture is
depicted in Figure 1.
CURRENT RESULTS
Thirty-two motes are deployed on Great Duck Island, of
which nine are in underground burrows. The sensor network
has been deployed for four weeks as of the writing of this
paper. We have calculated that the motes have sufficient
power to operate for the next six months, even though biologists
will stop visiting the island in early September. This
new data will provide insights into the climate and burrow
activity through the fall and winter, something previously
not possible due to poor off-season weather conditions for
island travel.
CONCLUSION
Habitat and environmental monitoring represent an important
class of sensor network applications. We are collaborating
with biologists at the College of the Atlantic to
define the core application requirements. Because end users
are ultimately interested in the sensor data, the sensor network
system must deliver the data of interest in a confidenceinspiring
manner. The low-level energy constraints of the
sensor nodes combined with the data delivery requirements
leave a clearly defined energy budget for all other services.
Tight energy bounds and the need for predictable operation
guide the development of application architecture and
services.
[attachment=25838]
ABSTRACT
We provide an in-depth study of applying wireless sensor
networks to real-world habitat monitoring. A set of system
design requirements are developed that cover the hardware
design of the nodes, the design of the sensor network, and
the capabilities for remote data access and management. A
system architecture is proposed to address these requirements
for habitat monitoring in general, and an instance of
the architecture for monitoring seabird nesting environment
and behavior is presented.
INTRODUCTION
Habitat and environmental monitoring represent a class
of sensor network applications with enormous potential benefits
for scientific communities and society as a whole. Instrumenting
natural spaces with numerous networked microsensors
can enable long-term data collection at scales and
resolutions that are difficult, if not impossible, to obtain otherwise.
The intimate connection with its immediate physical
environment allows each sensor to provide localized measurements
and detailed information that is hard to obtain
through traditional instrumentation.
HABITAT MONITORING
Researchers in the Life Sciences are becoming increasingly
concerned about the potential impacts of human presence in
monitoring plants and animals in field conditions. At best it
is possible that chronic human disturbance may distort results
by changing behavioral patterns or distributions, while
at worst anthropogenic disturbance can seriously reduce or
even destroy sensitive populations by increasing stress, reducing
breeding success, increasing predation, or causing a
shift to unsuitable habitats. While the effects of disturbance
are usually immediately obvious in animals, plant populations
are sensitive to trampling by even well-intended researchers,
introduction of exotic elements through frequent
visitation, and changes in local drainage patterns through
path formation.
SYSTEM ARCHITECTURE
We now describe the system architecture, functionality
of individual components and how they operate together.
We explain how they address the requirements set forth in
Section 2.
We developed a tiered architecture. The lowest level consists
of the sensor nodes that perform general purpose computing
and networking in addition to application-specific
sensing. The sensor nodes may be deployed in dense patches
that are widely separated. The sensor nodes transmit their
data through the sensor network to the sensor network gateway.
The gateway is responsible for transmitting sensor
data from the sensor patch through a local transit network
to the remote base station that provides WAN connectivity
and data logging. The base station connects to database
replicas across the internet. Finally, the data is displayed
to scientists through a user interface. Mobile devices, which
we refer to as the gizmo, may interact with any of the networks
– whether it is used in the field or across the world
connected to a database replica. The full architecture is
depicted in Figure 1.
CURRENT RESULTS
Thirty-two motes are deployed on Great Duck Island, of
which nine are in underground burrows. The sensor network
has been deployed for four weeks as of the writing of this
paper. We have calculated that the motes have sufficient
power to operate for the next six months, even though biologists
will stop visiting the island in early September. This
new data will provide insights into the climate and burrow
activity through the fall and winter, something previously
not possible due to poor off-season weather conditions for
island travel.
CONCLUSION
Habitat and environmental monitoring represent an important
class of sensor network applications. We are collaborating
with biologists at the College of the Atlantic to
define the core application requirements. Because end users
are ultimately interested in the sensor data, the sensor network
system must deliver the data of interest in a confidenceinspiring
manner. The low-level energy constraints of the
sensor nodes combined with the data delivery requirements
leave a clearly defined energy budget for all other services.
Tight energy bounds and the need for predictable operation
guide the development of application architecture and
services.