Poster Abstract : A sensor network for compression and streaming of GPS trajectory data

We present the design and deployment results for PosNet - a large-scale, long-duration sensor network that gathers summary position and status information from mobile nodes. The mobile nodes have a fixed-sized memory buffer to which position data is added at a constant rate, and from which data is downloaded at a non-constant rate. We have developed a novel algorithm that performs online summarization of position data within the buffer, where the algorithm naturally accommodates data input and output rate mismatch, and also provides a delay-tolerant approach to data transport. The algorithm has been extensively tested in a large-scale long-duration cattle monitoring and control application.

Demo Abstract: A Java compatible virtual machine for wireless sensor nodes

The Java programming language has potentially significant advantages for wireless sensor nodes but there is currently no feature-rich, open source virtual machine available. In this paper we present Darjeeling, a system comprising offline tools and a memory efficient run-time. The offline post-compiler tool analyzes, links and consolidates Java class files into loadable modules. The runtime implements a modified Java VM that supports multithreading and is designed specifically to operate in constrained execution environments such as wireless sensor network nodes and supports inheritance, threads, garbage collection, and loadable modules. We have demonstrated Java running on AVR128 and MSP430 microcontrollers at speeds of up to 70,000 JVM instructions per second.

Poster abstract : Energy-efficient rate adaptive MAC Protocol (RA-MAC) for long-lived sensor networks

This paper introduces an energy-efficient Rate Adaptive MAC (RA-MAC) protocol for long-lived Wireless Sensor Networks (WSN). Previous research shows that the dynamic and lossy nature of wireless communication is one of the major challenges to reliable data delivery in a WSN. RA-MAC achieves high link reliability in such situations by dynamically trading off radio bit rate for signal processing gain. This extra gain reduces the packet loss rate which results in lower energy expenditure by reducing the number of retransmissions. RA-MAC selects the optimal data rate based on channel conditions with the aim of minimizing energy consumption. We have implemented RA-MAC in TinyOS on an off-the-shelf sensor platform (TinyNode), and evaluated its performance by comparing RA-MAC with state-ofthe- art WSN MAC protocol (SCP-MAC) by experiments.

Wireless adhoc sensor and actuator networks on the farm

Agriculture accounts for a significant portion of the GDP in most developed countries. However, managing farms, particularly largescale extensive farming systems, is hindered by lack of data and increasing shortage of labour. We have deployed a large heterogeneous sensor network on a working farm to explore sensor network applications that can address some of the issues identified above. Our network is solar powered and has been running for over 6 months. The current deployment consists of over 40 moisture sensors that provide soil moisture profiles at varying depths, weight sensors to compute the amount of food and water consumed by animals, electronic tag readers, up to 40 sensors that can be used to track animal movement (consisting of GPS, compass and accelerometers), and 20 sensor/actuators that can be used to apply different stimuli (audio, vibration and mild electric shock) to the animal. The static part of the network is designed for 24/7 operation and is linked to the Internet via a dedicated high-gain radio link, also solar powered. The initial goals of the deployment are to provide a testbed for sensor network research in programmability and data handling while also being a vital tool for scientists to study animal behavior. Our longer term aim is to create a management system that completely transforms the way farms are managed.

Poster : Understanding interactions between autonomous animal control and temperament when cattle are subjected to virtual fencing applications

Virtual fencing has the potential to control grazing livestock. Understanding and refi ning the cues that can alter behaviour is an integral part of autonomous animal control. A series of tests have been completed to explore the relationship between temperament and control. Prior to exposure to virtual fencing control the animals were scored for temperament using fl ight speed and a sociability index using contact logging devices. The behavioural response of 30, Belmont Red steers were observed for behavioural changes when presented with cues prior to receiving an electrical stimulation. A control and four treatments designed to interrupt the animal’s movement down an alley were tested. The treatments consisted of sound plus electrical stimulation, vibration plus electrical stimulation, a visual cue plus electrical stimulation and electrical stimulation by itself. The treatments were randomly applied to each animal over fi ve consecutive trials. A control treatment in which no cues were applied was used to establish a basal behavioural pattern. A trial was considered completed after each animal had been retained behind the cue barrier for at least 60 sec. All cues and electrical stimulation were manually applied from a laptop located on a portable 3.5 m tower located immediately outside the alley. The electric stimulation consisted of 1.0 Kv of electricity. Electric stimulation, sound and vibration along with the Global Position System (GPS) hardware to autonomously record the animal’s path within the alley were recorded every second.

Data collection, storage and retrieval with an underwater sensor network

In this paper we present a novel platform for underwater sensor networks to be used for long-term monitoring of coral reefs and �sheries. The sensor network consists of static and mobile underwater sensor nodes. The nodes communicate point-to-point using a novel high-speed optical communication system integrated into the TinyOS stack, and they broadcast using an acoustic protocol integrated in the TinyOS stack. The nodes have a variety of sensing capabilities, including cameras, water temperature, and pressure. The mobile nodes can locate and hover above the static nodes for data muling, and they can perform network maintenance functions such as deployment, relocation, and recovery. In this paper we describe the hardware and software architecture of this underwater sensor network. We then describe the optical and acoustic networking protocols and present experimental networking and data collected in a pool, in rivers, and in the ocean. Finally, we describe our experiments with mobility for data muling in this network.

Low-Cost vision-based AUV guidance system for reef navigation

Ensuring the long term viability of reef environments requires essential monitoring of many aspects of these ecosystems. However, the sheer size of these unstructured environments (for example Australia’s Great Barrier Reef pose a number of challenges for current monitoring platforms which are typically remote operated and required significant resources and infrastructure. Therefore, a primary objective of the CSIRO robotic reef monitoring project is to develop and deploy a large number of AUV teams to perform broadscale reef surveying. In order to achieve this, the platforms must be cheap, even possibly disposable. This paper presents the results of a preliminary investigation into the performance of a low-cost sensor suite and associated processing techniques for vision and inertial-based navigation within a highly unstructured reef environment.

Vibration isolation for autonomous helicopter flight

The mechanisms of helicopter flight create a unique, high-vibration environment which can play havoc with the accurate operation of on-board sensors. Vibration isolation of electronic sensors from structural borne oscillations is paramount to their reliable and accurate use. Effective isolation is achieved by realising a trade-off between the properties of the suspended instrument package, and the isolation mechanism. This is made more difficult as the weight and size of the sensors and computing hardware decreases with advances in technology. This paper presents a history of the design, challenges, constraints and construction of an integrated isolated vision and sensor platform and landing gear for the CSIRO autonomous X-Cell helicopter. The results of isolation performance and in-flight tests of the platform in autonomous flight are presented.

Robust pose estimation for a car-like vehicle

In this paper, we outline the sensing system used for the visual pose control of our experimental car-like vehicle, the autonomous tractor. The sensing system consists of a magnetic compass, an omnidirectional camera and a low-resolution odometry system. In this work, information from these sensors is fused using complementary filters. Complementary filters provide a means of fusing information from sensors with different characteristics in order to produce a more reliable estimate of the desired variable. Here, the range and bearing of landmarks observed by the vision system are fused with odometry information and a vehicle model, providing a more reliable estimate of these states. We also present a method of combining a compass sensor with odometry and a vehicle model to improve the heading estimate.

Visual servoing of a car-like vehicle - an application of omnidirectional vision

In this paper, we develop the switching controller presented by Lee et al. for the pose control of a car-like vehicle, to allow the use of an omnidirectional vision sensor. To this end we incorporate an extension to a hypothesis on the navigation behaviour of the desert ant, cataglyphis bicolor, which leads to a correspondence free landmark based vision technique. The method we present allows positioning to a learnt location based on feature bearing angle and range discrepancies between the robot's current view of the environment, and that at a learnt location. We present simulations and experimental results, the latter obtained using our outdoor mobile platform.

Low-cost flight control system for a small autonomous helicopter

In this paper we describe a low-cost flight control system for a small (60 class) helicopter which is part of a larger project to develop an autonomous flying vehicle. Our approach differs from that of others in not using an expensive inertial/GPS sensing system. The primary sensors for vehicle stabilization are a low-cost inertial sensor and a pair of CMOS cameras. We describe the architecture of our flight control system, the inertial and visual sensing subsystems and present some flight control results.

Development of patient-specific computer simulation tools for endoscopic scoliosis surgery

Endoscopic approaches for anterior correction of idiopathic scoliosis are a relatively new surgical technique. This paper describes the development of patient-specific finite element modelling techniques to investigate the biomechanics of single rod anterior scoliosis correction. Spinal geometry is obtained from pre-operative CT scans and material properties for osteo-ligamentous spinal tissues are based on existing literature. The techniques being developed will allow pre-surgical prediction of stresses, forces and deformations in spinal tissues, rods and screws under post-operative physiological loads.

Robust image hashing using higher order spectral features

Robust image hashing seeks to transform a given input image into a shorter hashed version using a key-dependent non-invertible transform. These image hashes can be used for watermarking, image integrity authentication or image indexing for fast retrieval. This paper introduces a new method of generating image hashes based on extracting Higher Order Spectral features from the Radon projection of an input image. The feature extraction process is non-invertible, non-linear and different hashes can be produced from the same image through the use of random permutations of the input. We show that the transform is robust to typical image transformations such as JPEG compression, noise, scaling, rotation, smoothing and cropping. We evaluate our system using a verification-style framework based on calculating false match, false non-match likelihoods using the publicly available Uncompressed Colour Image database (UCID) of 1320 images. We also compare our results to Swaminathan’s Fourier-Mellin based hashing method with at least 1% EER improvement under noise, scaling and sharpening.

Bias in the nonlinear filter generator output sequence

Nonlinear filter generators are common components used in the keystream generators for stream ciphers and more recently for authentication mechanisms. They consist of a Linear Feedback Shift Register (LFSR) and a nonlinear Boolean function to mask the linearity of the LFSR output. Properties of the output of a nonlinear filter are not well studied. Anderson noted that the m-tuple output of a nonlinear filter with consecutive taps to the filter function is unevenly distributed. Current designs use taps which are not consecutive. We examine m-tuple outputs from nonlinear filter generators constructed using various LFSRs and Boolean functions for both consecutive and uneven (full positive difference sets where possible) tap positions. The investigation reveals that in both cases, the m-tuple output is not uniform. However, consecutive tap positions result in a more biased distribution than uneven tap positions, with some m-tuples not occurring at all. These biased distributions indicate a potential flaw that could be exploited for cryptanalysis.

An innovative modelling approach to assess stormwater pollutant loads from the Port of Brisbane, Australia

Port land uses are subjected to unique anthropogenic activities compared to typical urban land uses. This uniqueness results in distinctive stormwater quality characteristics. Such distinction in stormwater quality has made conventional approaches used for pollutant load estimations inaccurate. This is also the case for the Port of Brisbane (PoB). The study discussed in the paper was conducted to estimate the pollutant contributions from Port specific land uses at PoB. For estimation, software modules embedded in Mike URBAN were used. An innovative approach was adopted in modelling where the conventional model calibration step was not needed to be performed to generate suitable site specific parameters. Instead, equations and site specific parameters that replicate pollutant build-up and wash-off were generated from an extensive field investigation. Models were simulated incorporating site specific parameters from six different Port specific land uses and rainfall events from three representative years. Outcomes of the modelling exercise were used to identify the distinct pollutant contributions from different Port land uses.