About
Teaching
  • CC2510: Digital Logic and Computing Methods (Level 2; TSV)
  • EE3010: Digital Signal Processing (Level 3; TSV)
  • EE4500: Electrical and Electronic Engineering Design (Level 4; CNS & TSV)
  • EE5510: Advanced Electrical Engineering Design (Level 5; TSV)
  • EG1012: Electric Circuits (Level 1; TSV)
Research Disciplines
Publications

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.

Journal Articles
Conference Papers
Other research outputs
Current Funding

Current and recent Research Funding to JCU is shown by funding source and project.

Skyrail Rainforest Foundation - Research Funding

Low-cost Cloud Height Monitoring

Indicative Funding
$2,500 over 1 year
Summary
The Wet Tropics World Heritage Area is one of the most important environmental regions of northern Queensland - and its ongoing health and the effect of climate change on its ecosystem is of great concern going forward. By monitoring the presence of water vapor over a large time scale it will be possible to detect cloud height patterns and trends potentially damaging changes to the ecosystem. The development of a relatively low-cost monitoring system is important to help acquire field data as many of the current technologies to monitor cloud height are expensive. Providing a low-cost alternative for acquiring these data will allow for further research to be more readily conducted in the future.
Investigators
Samuel Healion, Scott Heron, Owen Kenny, Brendan Calvert and Mark Payne (College of Science & Engineering)
Keywords
Tropical Rainforest; Water vapour content; Wireless sensor networks; Climate Change; Electronic sensor development

Australian Government Department of Agriculture, Water and the Environment - Control Tools and Technologies for Established Pest Animals and Weeds Programme

Improving the accuracy of weed killing robots with new image processing algorithms and near infra-red spectroscopy techniques

Indicative Funding
$271,772 over 2 years
Summary
Automated weed species recognition remains a major obstacle to the development and industry acceptance of robotic weed control technology. Particular problems occur in rangeland applications, including high light variability and weed-camera distance variability, which cause camera dynamic range problems, image blurring, and occlusion by other plants. This project aims to develop robust image recognition systems combined with Near Infra-Red spectroscopic methods for these complex rangeland environments with special emphasis on the broad-acre grazing pastures in North Queensland. The developed imaging systems will be suitable for all weed killing applications with particular emphasis given to foliar spot-spraying and Herbicide Ballistic Technologies.
Investigators
Ron White, Bronson Philippa, Alex Olsen and Owen Kenny in collaboration with Brett Wedding, Michael Graham, Carole Wright and Stephen Grauf (College of Science & Engineering, QLD Department of Agriculture and Fisheries and Forestry)
Keywords
Weed; Near-Infra-Red; Robotics; Image Analysis
Supervision

Advisory Accreditation: I can be on your Advisory Panel as a Secondary Advisor.

These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.

Completed

Connect with me
Share my profile
Share my profile:
jcu.me/owen.kenny

Email
Phone
Location
Advisory Accreditation
Secondary Advisor
Find me on…
Icon for Scopus Author page

Similar to me

  1. A/Prof Roberto Dillon
    JCU Singapore
  2. Dr Euijoon Ahn
    Information Technology
  3. Dr Mangalam Sankupellay
    College of Science & Engineering
  4. Dr Dmitry Konovalov
    Information Technology
  5. Dr James Whinney
    Physical Sciences