Engineering
Liuxin Chen
- Lecturer
- liuxin.chen@jcu.edu.au
Mohamadreza Chalak Qazani
- Lecturer, Mechanical Engineering
- mohamadreza.chalakqazani@jcu.edu.au
Lewis Gooch
- Lecturer
- lewis.gooch@jcu.edu.au
Judy Yang
- Postdoctoral Research Fellow, Applied AI for Forestry Weed Detection and Mapping
- judy.yang@jcu.edu.au
Bouchra Senadji
- Head, Engineering
- bouchra.senadji@jcu.edu.au
Alzayat Saleh
- AIMS@JCU Postdoctoral Research Fellow, Marine Science Technology
- alzayat.saleh@jcu.edu.au
Anne Steinemann
- Adjunct Professor
- anne.steinemann@jcu.edu.au
Nico Adams
- Professor, Electronic Systems & IoT Engineering
- nico.adams@jcu.edu.au
Elsa Antunes
- Associate Professor, Mechanical Engineering
- elsa.antunes1@jcu.edu.au
Eric Wang
- Senior Lecturer, Electronic Systems and IoT Engineering
- eric.wang@jcu.edu.au
GBRF Burdekin Irrigation Project. (Old ID 27063)
Eric Wang
15 Jan 2020 - 01 Jun 2024
Increasing Industry Productivity and Profitability Through Transformational, Whole of Systems Sugarcane Approaches that Deliver Water Quality Benefits.
Joint Huawei-JCU Internet of Things Laboratory (Old ID 23113)
Wei Xiang
19 Dec 2016 - 31 Dec 2021
To enable the collaboration on opportunities that include: a) establishing a joint Huawei-JCU Internet of Things (loT) Laboratory: b) use the joint loT Lab to promote strong academic-industry collaboration; leveraging on Australia's first loT Engineering degree program run by JCU etc.
Light Field Video Compression and Streaming (Old ID 23155)
Wei Xiang
01 Mar 2017 - 01 Mar 2019
Recent advances in light field (LF) photography open a new horizon for digital video streaming, where the single-shot LF capture and glasses-free 3D display capabilities are perfect for a wide range of 3D interactive applications. This proposal aims to propose an interactive 3D VR streaming system based upon the state-of-the-art LF video compression and transmission technology. The proposed new framework and novel algorithms will be able to efficiently compress the enormous amounts of LF-based VR video data, ensure the quality of the views of interest, and achieve low-latency and error-resilient 3D video transmission.
Council improving the water quality of the Great Barrier Reef through the use of smart sensors and the IoT for urban water management (Old ID 23533)
Wei Xiang
01 Feb 2018 - 30 Jun 2019
The primary aim of this grant application is to bring smart city technology into urban water management to improve urban water quality discharging to the Great Barrier Reef by: 1). Developing IOT technology to manage large data sets obtained from existing smart meters and water quality monitoring probes to make effective management decisions; and 2) Supporting the development of new cost effective, real time water quality monitoring technology. This grant application is for purchase of commercially available water quality monitoring probes suitable for a tropical urban stormwater environment, for supporting the development of new real time monitoring technology for nutrients; for the development of data analysis tools using IOT technology for both smart meter water consumption data, sewer pump station overflow data and stormwater water quality data so that the data is available in real time and can be used for effective decision making.
Climate Smart Sugarcane Irrigation Partnerships (CSSIP) (Old ID 24754)
Bronson Philippa
22 Aug 2018 - 30 Jun 2023
CSSIP will minimise nutrient runoff, improve soil health and increase wetlands water quality by facilitating the adoption of world-class irrigation practices in sugarcane farming systems. Currently, best practice irrigation is assisted by an Irrigation Decision Support Tool (IDST) that provides evidence-based advice. However, IDSTs have not reached their full potential. Firstly, they do not integrate short to medium term weather forecasts (e.g. weekly to multi-weekly forecasts). Secondly, IDSTs do not operate at a spatial scale relevant to farmers. CSSIP will incorporate the Bureau or Meteorology’s new high-resolution climate model into the Irrigation Decision Support Tool. Thirdly, IDSTs require substantial time in manual data entry, which can be alleviated using real-time monitoring via Internet of Things technologies. This will increase irrigation efficiency, reducing excessive runoff into river systems and onto the Reef, and, will help farmers save water and energy costs.
AI-Powered Precision Farming: Mapping, Detection, Planning, and Spot Spraying (Old ID 31107)
Mohammad Jahanbakht
01 Sep 2023 - 29 Nov 2024
High-tech solutions in agriculture offer many benefits for improved crop and land management. However, current methods rely heavily on human experts for monitoring and planning. To address this, we propose a state-of-the-art AI-based spraying strategy software that: • takes aerial images of the farm/land vegetation (using drones, planes, satellites, etc.) and detects field requirements, • generates a pre-spray map on GIS systems, considering the existing terrain topographies, • optimally plans the detailed spraying strategy and suggests one or a combination of proper spraying methods such as blanket, vehicular spot, or aerial spraying, and • whenever possible, effectively commands and controls appropriate devices to spray, such as drones, vehicles, people, etc. It might also receive feedback and correspondingly optimize the process/plan. This AI-Powered system helps farmers and producers precisely spray, saving costs and the environment.
Thermal stratification, overturning and mixing in riverine environments (Old ID 21650)
Wenxian Lin
16 Jan 2015 - 15 Jan 2018
Thermal stratification is common in Australia's rivers due to our hot, drought-prone climate and high human demands relative to available supply, which has led to a significant reduction in flows relative to natural levels. Thermal stratification inhibits mixing, creating stagnant conditions characterised by low oxygen levels and increased concentrations of contaminants, leading to algal blooms, fish kills and systemic damage to ecosystems. The aim of this project is to develop predictive models for the effects of physical processes such as night-time cooling, wind, turbulence and currents n riverine thermal stratification. This will enable a more accurate determination of the flow rates required to maintain the health of our river systems.
AutoFish: Automatic Fish Phenotyping Tool for Sustainable Aquaculture and Smart Fisheries (Old ID 28947)
Mostafa Rahimi Azghadi
01 Mar 2023 - 30 Jun 2023
This project aims to advance an initial implementation of a new automatic fish phenotyping tool, named AutoFish, that will enhance aquaculture farming and post-harvest processing practices by accelerating the collection of data and automatically analysing and leveraging it using the latest advances in computer vision and machine learning technologies. We have already developed a ground-breaking solution for the aquaculture industry, and produced a Proof Of Concept (POC) device, which has been successfully tested. This POC is ready to get tailored, integrated and/or retrofitted into an available fish and aquaculture farm for grading, phenotypic collection and/or processing lines, due to its modular stand-alone nature. The AutoFish concept has been proven with Barramundi as a test species. However, it can be used to collect images of, and trained to predict features of other fish and/or aquaculture species. AutoFish can also be trained to detect and predict any customertailored features and traits of the fish/product, and/or be used to assess the health of fish/product, if th health issues are visually recognisable by an RGB camera and the background phenotypic data present for training. Hence this technology would be scalable and can be implemented for other aquaculture products worldwide. The main aim of this project is to unlock the potential of our initial AutoFish POC by applying it to, or altering it for, a partner Barramundi (or Prawn) farm, to solve a real end-users’ problem. This problem can be about any monitoring aspect, as long as cameras can capture it. We have narrowed down the scope of this project to Barramundi (and/or Prawn) due to our wider industry network in these two species.
Plasma assisted fabrication of nanofirous membranes for energy applications (Old ID 22343)
Mohan Jacob
01 Oct 2015 - 30 Sep 2016
Development of highly stable proton conductive polymer electrolyte membranes will enable advances in energy conversion systems. This project focuses on developing innovative membranes for fuel cells and vanadium redox battery based on cheap electrospun nanofibrous modified with plasma. Nanofiberousmats containing proton conducting functionalities will be prepared by electrospinning of desired polymers followed by immobilising of ionic groups. Composite membranes with webbed morphologies will be obtained using plasma assisted crosslinking of nanofiberousmats followed by introducing additional polyelectrolyte layers. The adopted fabrication technique will be a versatile strategy for producing low cost and mechanically stable PEMs for numerous electrochemical applications.
RRAP CAD-01: Coral propagation and deployment (Old ID 27237)
Elsa Antunes
01 Oct 2020 - 30 Jun 2025
Deployment device shape and material can considerably affect the growth rates and survival of recruits, but the optimal physical properties of deployment devices to maximise the survival and growth of a diversity of corals are not yet clear. For example, crevice size is an important physical factor that influences the survivorship of coral recruits and juveniles. Spatial structure of settlement surfaces can provide refugia from algae and release from grazing. The first part of the project consists of selecting potential device materials, porosities and textures that will be assessed for fouling and recruit survival. These will be first tested in the SeaSim and the most promising candidates in the field in across a range of environments and environmental gradients. The second part of the project consists of optimization and scaling up of the fabrication technology to produce millions of devices.
The validity of using inertial measurement units to monitor the torso and pelvis sagittal plane motion of elite rowers
- 2022
- Taylor & Francis
- Researchers:Sara BriceBronson Philippa
Digital twins and their significance in engineering asset management
- 2022
- Institute of Electrical and Electronics Engineers
- Researchers:Mostafa Rahimi Azghadi
Soil Mechanics and Foundation Engineering
- 2021
- McGraw-Hill
- Researchers:Siva Sivakugan
Start Date:
26 Mar 2026
Start Date:
23 Oct 2025
Start Date:
22 Oct 2025
Start Date:
25 Nov 2025
Start Date:
03 Sep 2025
Reseracher:
Stephanie Baker
(Senior Lecturer, Electronic Systems and Internet of Things Engineering)
Start Date:
01 Jan 2019
Start Date:
01 Jan 2022
Start Date:
01 Jan 2019