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WildSensing: A Hybrid Framework of Mobile and Sensor Nodes for Wildlife Monitoring
Kindly Sponsored by the UK's Engineering and Physical Sciences Research Council, INTEL and Wavetrend.
Grant: EPSRC EP/E012914/1 Project dates: January 2007 - July 2010
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Technological advances in Micro-Electro-Mechanical Systems (MEMS) are envisaged to allow the dense deployment of nodes with sensing, communication and processing capabilities in large areas for monitoring purposes. In this project we offer an alternative to plain multi hop data forwarding through the sensor network. Our approach suggests the forwarding of sensor data and its storage in selected nodes (storage nodes) from where the data will be collected later on by roaming mobile nodes. This new operational setting will leverage recent advances in mobile technology to relieve the sensor network from heavy multi-hop communication tasks. It will exploit the vast availability of a variety of different mobile devices (e.g., phones, pdas and domain specific wireless- equipped devices such as health monitors) and the potential for user or unmanned vehicle mobility. Mobile devices are equipped with one or more wireless network interfaces (Bluetooth, 802.11, 802.15.4, etc), which makes them able to connect and interact with storage nodes in radio range, in an ad hoc manner.

An application that would particularly benefit from continous monitoring using sensor nodes is wildlife monitoring. One of the primary benefits of this new technology will be to offer biologists the means to monitor animals more effectively. The animals too will benefit through the refinements to welfare that these small and efficient RFID devices provide. This entire technology will permit a whole suite of new and more detailed questions about animal movements and spatial behaviour to be answered.

Current approaches to wildlife monitoring and conservation often still rely on labour intensive techniques for making observations of animal behaviour or for tracking animal movements with established (but outmoded) VHF telemetry equipment. The typical mode of monitoring is to send staff to every single sensor node in the field, to collect sensor readings. The raw data is collected by staff, brought together in a lab, and processed in a centralized manner. The heavy reliance on field-staff for animal monitoring currently incurs considerable employment costs and overheads for ancillary equipment.

The use of personnel working alone at night in forests also has significant health and safety implications, and the scrutiny of the Health and Safety Executive is likely to jeopardise many of these protocols in the future.

Technical Aims

  • Define high-level language primitives for programming the integrated platform of sensor and mobile nodes.
  • Develop distributed algorithms for intelligent cooperation among mobile devices and sensor nodes, allowing the system to minimize the total monitoring effort, which has two components: the distance traversed by mobile hosts to collect data from a few sensor nodes acting as storage nodes, and the energy spent by sensor nodes to wirelessly relay data hop-by-hop to the storage nodes.
  • Design distributed algorithms for energy-efficient data dissemination in the sensor network.
  • Deploy a prototype monitoring system at Oxford University's research reserve, Wytham Woods, in order to monitor the social behaviour of badgers and the microclimatic conditions around their setts.


After the initial testing in the autumn of 2008, the project had its first large-scale deployment in Wyhtam Woods, Oxford. We deployed 28 RFID-Sensor nodes ('detection nodes') around the forest, near places where we expect animals to come by. Such places are known setts as well as latrines, and have been identified by domain-experts. 30 badgers have been tagged with RFID collars, and as a result, we have been collecting badger sightings since February, 2009. Despite our efforts, the lifetime of the detection nodes is limited to a few weeks, which requires us to change the batteries rather often. Another constraint we have is the limited memory of the nodes storing the sightings - it gets filled up in weeks (depending on the activity of the place). Our current efforts are to reduce the energy usage considerably, and extend the memory of the sensors. Reducig the energy consumption of the detection nodes involves improving the software running on the sensors, introducing dutycycling on the readers and perhaps improve the hardware design of the board. We are looking at ways to connect an external flash memory (such as an SD card) to extend the memory from the current 1 MB to several hundrends.

Along with the badger detection deployment, we are deploying static wireless sensor network to collect environmental information as well as aid the delivery of the data from the detection nodes to the end users. For details on the static sensor network, contact our collaborators in the ComLab, Oxford.


Past members

  • Dr. Vladimir Dyo
  • Dr. Anders Lindgren
  • Dr. Kharsim Yousef
  • Project Collaborators


    Kindly Sponsored by the UK's Engineering and Physical Sciences Research Council, INTEL and Wavetrend.
    Grant: EPSRC EP/E012914/1, Project dates: January 2007 - July 2010.
    © 2008 University of Cambridge