It is always difficult to determine behavior without observing one's subject in its natural environment. If noticed, the subject may change its behavior or just run away. For example, I pride myself on being able to type at least 65-85 wpm. But of course, as soon as someone walks in and watches me I make mistakes and begin typing like a 5-year old... To observe anything in its natural habitat is one of the hardest challenges to overcome when trying to monitor many species in our world today. However, there is a group of individuals at University of Florida and University of Missouri, Colombia who are using Crossbow's wireless sensor networks products to try and understand the role of free-ranging wildlife in maintaining diversity, tracking invasive species and the spread of emerging diseases by obtaining unobtrusive visual information that prove vital when studying the behaviors and interactions of wildlife species in their environment.
The biological relationship between wildlife and humans has never been more intertwined. Outbreaks of various infectious wildlife diseases threaten wildlife populations, human health, food safety and national economy. Current technologies available for wildlife studies, such as VHF ratio-telemetry and GPS tracking, significantly limit our capability in studying the behavior and interaction of the wildlife species, and the dynamics of the free-ranging wildlife remains largely unknown. Lack of scientific knowledge about the behavioral interactions and dynamics of wildlife systems, our ability to prevent, manage, and control wildlife diseases is very limited.
DeerNet is a NSF-sponsored project on wireless sensor networking for wildlife
behavior analysis and interaction modeling to better understand the biology and management of the world's ungulates. The overall goal of the research is to develop a long-lived and
unobtrusive wildlife video monitoring system capable of real-time video
streaming with remote control capability. The captured video in real
time will be transmitted over wireless sensor networks to a remote
monitoring center for real-time viewing and camera control. Because
real-time transmission requirements are particularly challenging to
wireless sensor network design, the research is addressing important
issues on energy minimization and performance optimization in video
sensing over mobile wireless sensor networks. By usin
g Crossbow's Stargate platform and MICA Mote platform along with wireless network video in a portable, low-energy solution coupled with optimized transmission protocols and routing schemes
for transferring the video images through sensor node design, access
control, and robust routing protocol this goal is becoming a reality.
In embedded video communication system design for wildlife activity monitoring, the system is expected to operate over an extended period of time, say a few weeks or even months. Therefore, energy minimization of video encoding is very critical. The design of a power-aware embedded system, e.g., DeerNet video sensor, is composed of three parts: the hardware, the underlying system architecture, and the model for distributing applications across the tiers. In general, the design is similar to many distributed systems; each tier is under autonomous control while decisions are made in a distributed manner. Client applications reside at the most powerful tier, and tasks that support those applications are distributed among the various tiers.
The DeerNet video sensor is designed in a strictly hierarchical manner, and the higher tier is more powerful than the lower tier. The two tiers can communicate each other and communication occurs via a local port where the tiers are connected to a common power source. The higher tier is based on the Stargate platform, which has an XScale PXA255 CPU (400 MHz) with 32MB flash memory and 64MB SDRAM along with a daughter board with Ethernet, USB and serial connectors. A Logitech QuickCam Pro 4000 webcam is connected through a USB connection 
for video capture. The MICA Mote then plays the lower tier rule which works with a powerful Atmega128L micro-controller. The data, measurements, and other user-defined information are stored in a 4-Mbit serial flash (Atmel AT45DB041). In the higher tier Stargate, the linux operating system manages all the tier resources including the power management and the video capture. The video capture mod-ule performances the new P-R-D optimization encoder which compresses the video sequence into a CF card. The power management can put the Stargate into sleep if it is necessary. Once the Stargate is in sleep state, it will wait for a signal to wake up from the Mote at the lower tier. The MICA Mote, at the lower tier, performs tasks such as determining the motion signal that reflects the deer motion state, recording the deer motion state, communicating with the higher tier, and sending wakeup signal to higher tier Stargate.
The DeerNet video sensor is used to track the deer’s action and some situations do not need to be recorded such as sleep, repeating the same action, and at night. On the Stargate, a timer is designed which tracks what time it is and how long it will last. Therefore, once the timer shows night coming, the Stargate is put into sleep. Another signal comes from MICA which determines motion state. The overall objective of this research project is to develop a next-generation wildlife monitoring
technology for behavior analysis, interaction modeling, disease
tracking and control. The research team is working to develop
theories and technologies in efficient wireless networking and video
sensing, to collect video information about their daily activities,
which is the essential information needed in wildlife behavior analysis
and interaction modeling.
DeerNet is an innovative interdisciplinary engineering, computer science and wildlife science project. The video monitoring has the potential to significantly advance this area of science and engineering, and has the broader application to other fields including surveillance, security, process monitoring and other industrial applications.
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