Laing, Mac (2018) Remote Livestock Monitoring Utilising Internet of Things Technology. [USQ Project]
Abstract
Australia is among the world's largest producers of commercial livestock servicing both domestic and export markets, with the industry worth more than 20.6 billion dollars. Livestock are spread geographically throughout the entire continent, with an estimated total of 78 000 farms in Australia. There is a growing trend for farmers to manage multiple properties while not residing on or near these farmlands, resulting in vast land usage, causing additional challenges for the farmer. Livestock theft is estimated at 72 million dollars however, this could be much higher as an Australian National Farm Crime Survey report indicated that 50 percent of rural crimes were not disclosed to police.
Taking these factors into account it is apparent that livestock represents a major asset to farming families. It is also apparent that farmers spend a lot of energy, resources, time and money traveling to and around these remote properties to inspect their livestock for security, health, feed and watering conditions.
This dissertation describes the design and development of a prototype system which uses radiofrequency identification (RFID) and Internet of Things (IoT) technology to provide farmers with the ability to remotely monitor livestock for precise, individual animal identification regardless of where the farmer resides or the geographic location of the livestock. Data collected from each animal and local farming infrastructure is collated and used to display livestock inventory, whereabouts, security and watering conditions through real-time and historical reporting tools.
The major achievement of this research has been the successful implementation of a prototype livestock monitoring system. The developed system successfully achieved all defined objectives and requirements during system acceptance testing. It is anticipated that the application will provide an increase in farming operational business efficiencies and a reduction in operating costs.
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| Item Type: | USQ Project |
|---|---|
| Item Status: | Live Archive |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021) |
| Supervisors: | Hills, Catherine; Banhazi, Thomas |
| Qualification: | Bachelor of Engineering (Honours) (Electrical and Electronic) |
| Date Deposited: | 06 Sep 2022 01:27 |
| Last Modified: | 29 Jun 2023 01:49 |
| Uncontrolled Keywords: | livestock; monitoring; radiofrequency identification (RFID); Internet of Things (IoT) |
| URI: | https://sear.unisq.edu.au/id/eprint/40781 |
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