ISSNIP is linked to Coral Reef Environmental Observatory Network (CREON) a global consortium of reef scientists. This has resulted in access to significant resources funded by overseas research agencies in Europe and USA. This is a massive multidisciplinary environmental project with active participation from national and international institutions (AIMS, QPCF, JCU, UQ, UoM).  In order to achieve its objectives, the applicant has been pursuing collaborative projects through several grants (completed and on-going). This has resulted in several useful algorithms, small scale testbed implementations, technology demonstrations and large scale infrastructure in the form of NCRIS-IMOS ( all for the greater objective of monitoring the reef. ISSNIP is a co-investor and institutional participant in IMOS-GBROOS (Integrated Marine Observing System - Great Barrier reef Ocean Observing System).

The Great Barrier Reef (GBR)

     The Great Barrier Reef (GBR) consists of 3200 coral reefs extended over 280,000km2 [3] (see Figure 1). Understanding the patterns of thermal stress and other environmental parameters is essential for monitoring the health of the coral reefs (eg., refer [10] for environmental change and impacts on GBR). The health of the coral reefs can be affected by cold water intrusions, hot water intrusions, coral calcification, ocean acidification, coral-algae phase shifts and the spread of coral diseases due to temperature increases. For example, a temperature rise of about 2-3 degrees Celsius over the normal maximum summer temperature can kill corals [12]. In order to monitor the health of the coral reefs, sea temperatures need to be measured in fine spatial resolutions at various depths. Traditional methods of using satellite images can only reveal water surface temperature distributions at coarse spatial resolutions such as 1km2. This resolution does not provide sufficient detail to investigate the cause of coral bleaching or coral growth events in the GBR, such as 2002 coral bleaching event [3, 11]. Measurements at small spatial scales and at various depths are required in order to enable an in-depth analysis of the implications and causes of these bleaching events.

gbr-reefs-site wsn-mgtisland   

Figure 1: Great Barrier Reef [3].                        Figure 2: Sensor nodes used in Nelly Bay, Magnetic Island [9]. 

Another important factor in the analysis of the reef is the abundance of a sea water organism called plankton, which plays an important role in the GBR food chain [1]. Understanding plankton production recently became popular due to its ability to recycle CO2 and therefore its potential role in global climate change. The productivity of plankton in the GBR is influenced by the nutrient rich cold water intrusions that originate in the Coral Sea and upwell on the reef. Monitoring high frequency sea temperature changes due to daily tides and upwelling in near real-time enables the study of how the changing sea temperature affects the abundance of plankton [1]. Further more, nutrient concentrations like nitrate, phosphate and silicate are strongly correlated with water temperatures [2].

Sensor networking the GBR

The coral reef monitoring system using wireless sensor networks in the Davis Reef, North Queensland involves the placement of a number of environmental sensors that measure temperature, salinity, light and oxygen [3]. Current infrastructure installed in this reef site includes a sensor gateway, which provides the aggregation point for sensor data, a hybrid power supply utilising solar cells and a battery, a high speed microwave link, which operates using a 'humidity duct' at a data rate of 10Mbps, and cameras [4, 7, 8]. The Davis Reef weather station data is now made available on Microsoft SensorMap. More details can be obtained from here

The first experimental wireless sensor network was implemented in Nelly Bay, Magnetic Island during 2007 [9] (refer to Figure 2). The sensor network consisted of two sensor arrays that comprise four moorings, each having seven temperature sensors vertically positioned below the ocean surface 2m apart [5]. An accelerometer sensor is also being deployed at each node to measure the wave tidal frequency.

Great Barrier Reef Ocean Observing System (GBROOS)

GBROOS project consists of five components as follows:

  • An up-grade to the Townsville Remote Sensing Receiving Station, located at AIMS
  • The installation of under-way sampling systems on a number of Ships of Oppertunity
  • The installtion of a Townsville and Darwin Reference Mooring as part of the Australian National Mooring Network facility under IMOS
  • The installation of a Mooring Array along the GBR to measure and monitor the movement of oceanic water onto the GBR
  • The installation of sensor networks at seven reef sites along the GBR

One of the components of the GBROOS project is the installation of sensor networks at seven reef sites along the GBR as given below.

Currently, a sensor network is being implemented in Heron Island, Qeensland as part of the Great Barrier Reef Ocean Observing System (GBROOS) project [14]. This sensor network is a two tiered, hierarchical topological network with heterogeneous sensor nodes in each level as shown in Figure 3. The nodes in the first tier are called poles and the nodes in the second tier are called buoys. There are 5 buoys and 6 poles used in the deployment. Buoys and poles are deployed in the lagoon area of the GBR approximately 2 km apart. The buoys communicate with the poles via single hop. The poles communicate to the base station via multiple hop. The base station is located in the Heron Island, which transmits the collected data to the mainland 75 km away.

 HeronIslandSN   HI-gbr-hs

Figure 3: Sensor network deployment in Heron Island, Qeensland. Hierarchical (or layered or tiered) topology of the network.


Figure 4: Heron Island deployment: Poles, buoys, base station and electronics inside the boxes.  


Each pole and buoy collects temperature at a depth from the sea surface. The temperature is samples every 10 minutes and saved in memory before transmitted to the base station periodically. Electronics at each buoy and pole consist of memory, temperature sensor interface, antenna for wireless communication between poles, buoys and base station, solar panels and a battery. Figure 4 shows the poles, buoys, base station and a box of electronic devices in one of the buoys. A third tier of sensor consisting of small sensor nodes is planned for future deployment. These sensor nodes will communuicate their data to the buoys. Figure 5 shows the hierarchical organisation with the third tier of sensor nodes. 


Figure 5: Planned deployment of the third tier of sensor nodes.



[1] Olga Bondarenko, Stuart Kininmonth and Michael Kingsford, "Underwater Sensor Networks, Oceanography and Plankton Assemblages", in the Proc. of International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2007), pp 657-662, (Melbourne, Australia), 2007.

[2] M.J. Furnas and A.W. Mitchell, Nutrient inputs into the central Great Barrier Reef (Australia) from subsurface intrusions of Coral Sea waters: a two-dimensional displacement model. In Continental Shelf Research, 1996. 16(9): pp. 1127-1148.

[3] Stuart Kininmonth, Scott Bainbridgea, Ian Atkinsonc, Eric Gilla, Laure Barrald and Romain Vidaude (2004), "Sensor Networking the Great Barrier Reef", Spatial Sciences Qld Journal, Spring 2004, pp34-38.

[4] Cameron Huddlestone-Holmes, Gilles Gigan, Graham Woods, Adam Ruxton, Ian Atkinson, and Stuart Kininmonth, Infrastructure for a Sensor Network on Davies Reef, Great Barrier Reef, in the Proc. of International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2007) , pp 657-662, (Melbourne, Australia), 2007.

[5] Olga Bondarenko, Stuart Kininmonth and Michael Kingsford, Coral Reef Sensor Network Deployment for Collecting Real Time 3-D Temperature Data with Correlation to Plankton Assemblages, in the Proc. of International Conference on Sensor Technologies and Applications (SENSORCOMM 2007), pp 204-209, (Valencia, Spain), 2007

[6] A Perrig, J Stankovic, and D Wagner, Security in wireless sensor networks, in Wireless Personal Communications, vol 37, no 3-4, 2006.









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