Human performance and cognition

The Institute for Intelligent Systems and Research Innovation focuses on rapid modelling methodologies to make complex models faster, at less cost, and with incomplete information. We are proud of our extensive track record in the research and development of simulation and decision support technologies.

Analyse to maximise

Process modelling and analysis can get down to the basics of a flow and identify troubling variants that are calling for a solution. We look at logistics, materials handling facilities and processes, statistical analysis, economic modelling and economic impact studies, among others.

Conventional analysis methods are static. They typically involve complex mathematics and require the end user to be able to manipulate, understand and interpret mathematical data using spreadsheets. In contrast, 3-D modelling and discrete event simulation enable the end user to see a virtual working model of an entire system.

Simulation models capture the variations in the individual processes, rather than just considering the average operating performance, resulting in higher levels of realism and more relevant outcomes. This is a great tool for assisting non-professionals to understand, and make decisions on, very complex problems. Virtual reality modelling provides the ability to demonstrate changes graphically, and effectively communicates concepts and implications.

Making an impact on airport security

Airports are susceptible to terrorist threats in several ways. Considering the payload of a typical flight, these threats can be broken down into threats from checked baggage, carry-on baggage, passengers and air cargo.

We have worked with both industry and government to assess the threat to airports and address the impacts to the sector from increased security requirements. Data collection during live trials has enabled the development of a set of model platforms that can quickly assess the impact to security process of increased security requirement, new policies and even new technology.

Featured researcher

Dr Samer Hanoun is a Senior Research Fellow in simulation and scheduling. His research interests are focused on job shop scheduling techniques, approximation algorithms and meta-heuristic methods for single objective and multi-objective optimisation.

Recently, Dr Hanoun has been engaged in the identification and assessment of technical solutions for enhancing job shop scheduling in the joinery manufacturing domain. By defining models and heuristics, the production planner can make the most of automated tools for manufacturing optimisation and, in turn, can help to take the grind out of the hard work.

Through this research we have been able to develop Pareto optimisation methodologies and tools for a set of real and conflicting manufacturing objectives such as material waste and tardiness, which can be utilised to provide production managers with a set of production schedules to select from subject to the manufacturing preferences at hand.

Dr Samer Hamoun


Research projects

Exploring how mosquito brains are affected by the zika virus

Our research aims to understand how the Zika virus attacks the brain so that potential steps towards vaccination can be made. Unlike other research groups, IISRI traced the infection back to its source in mosquitoes, the main carriers of the disease. The research involved placing mosquito brain cells on a chip and tracking their activity. It was discovered that mosquitoes infected with the Zika virus were naturally resistant to its most debilitating effects, making them more effective at spreading the virus.

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Intellegent swim sensor changes coaching capabilities

In partnership with the Australian Institute for Sport, IISRI has developed a new technology, expanding the potential of remote coaching. The technology allows swimmers to train in their local pools without missing out on the benefits of specialist coaching. The sensor engages smart monitoring, providing more accurate and analytical results. Also, unlike other existing sports sensors, the placement of this sensor doesn’t compromise performance. The device has been used mostly with the Australian Olympic team and has achieved 100 per cent accuracy.

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Advanced dynamic simulation and analysis of firearm training through haptics and motion capture

IISRI researchers are using advanced haptic and motion capture technologies to evaluate firearm discharge training tasks. This enables accurate training analysis, supports decision-making and delivers immersive shooting simulation. This research focuses on detailed analysis and realistic modelling of firearm discharge procedures, as well as force modelling and temporal-based calculation and rendering for specific firearms.

Wavelets and multi-wavelet bases for stereo correspondence estimation

Stereo correspondence estimation in one of the most active research areas in the field of computer vision. IISRI researchers have developed an algorithm that uses multi-resolution analysis enforced with wavelets/multi-wavelets transform modulus maxima to establish correspondences between stereo pairs of images.

Measuring depth accuracy in RGBD cameras

RGBD sensors project an infrared pattern and calculate depth from the reflected light using an infrared sensitive camera. In this research, the depth-sensing capabilities of two RGBD sensors are compared under various conditions.

Real-time ergonomic assessment for assembly operations using RGBD cameras

Ergonomic assessments increase productivity and performance by helping to prevent and reduce workplace injuries. The aim of this research is to use RGBD cameras for real-time ergonomic assessment in assembly operations. The accuracy and high sampling rates of RGBD sensors create an opportunity to monitor and alert operators if their current posture is risky.

Human motion analysis from video sequences

This research proposed a general framework for the analysis of human motion in videos, based on the bag-of-words representation and the probabilistic Latent Semantic Analysis (pLSA) model. This consists of detecting human subjects in videos, extracting pyramid Histogram of oriented Gradient descriptors, constructing a visual codebook by k-means clustering, and supervised learning of the pLSA model for recognition.

Event-related potential analysis to identify functional differences in the brain

The event-related potential (ERP) technique is a derivative of Electroencephalography (EEG), which measures brain activity during the cognitive processing of a sensory, motor or cognitive task. Our research investigates the use of extended multivariate autoregressive  (eMVAR) models for information flow analysis of ERP data. We are developing a range of adaptive estimation techniques, with the goal of improved extraction of the underlying information flow using the ERP data. These techniques are also used in a variety of applied research, including cognitive load assessment, development of brain-machine interfaces and rehabilitation-related studies.

Human identification from ecg signals

There is a lot of interest in using characteristics such as a person’s face, fingerprints or gait as a form of biomedical identification. Recent research reveals that individuals can be identified from Electrocardiogram (ECG) signals as people have different physiological and geometrical hearts, resulting in unique ECG signals. In our research, we are extracting compact and discriminative features from ECG signals. Unlike previous methods, the proposed method is able to capture both local and global structural information and does not need to segment individual heartbeats or detect fiducial points.

Neural microelectrodes on microfluidics

This research looks at interfacing nerve cells on an integrated microfluidics platform with electronics and software systems. The focus is on developing an integrated platform of these promising technologies into a modular platform. This involves interfacing nerve cells in immobilised microstructures inside microfluidics with embedded systems, and investigation of dynamics of bi-directional communication between neuron and silicon.