A Framework for Real-time Cattle Monitoring using Multimedia Networks
Rotimi-Williams Bello1, Abdullah Zawawi Hj Talib2, Ahmad Sufril Azlan Bin Mohamed3
1Rotimi-Williams Bello, School of Computer Sciences, Universiti Sains Malaysia, 11800, Pulau, Pinang, Malaysia.
2A. Z. H. Talib, School of Computer Sciences, Universiti Sains Malaysia, 11800, Pulau, Pinang, Malaysia.
3A. S. A. Mohamed, School of Computer Sciences, Universiti Sains Malaysia, 11800, Pulau, Pinang, Malaysia.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 974-979 | Volume-8 Issue-5, January 2020. | Retrieval Number: E5742018520/2020©BEIESP | DOI: 10.35940/ijrte.E5742.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Monitoring cattle behaviour has been a perpetual challenge in animal husbandry and animal breeding. Various methods have been used in the past to monitor the behaviour of cattle and their grazing patterns. We proposed a framework for real time cattle monitoring using multimedia networks. The study observes the grazing patterns of cattle and their behaviours in the grazing field. In order to accomplish the above observation, global positioning system monitoring collar for cattle is utilized; this technology monitors the activities of individual cattle during grazing through a networked system. The materials used in carrying out the work include cattle, waterproof global positioning system tracking collars (TR20) for cattle, and supporting application software by Sigfox’s global Internet of Things network. The paddock size was 121 by 174 m. Forage was predominantly agricultural plants. Cattle weighing up to 580 kg were used. The collared cattle were used to initiate all data collections. Latitude and longitude information of location was cumulatively stored in memory that is on-boarded and big enough for the fixing of position. Each fix record is comprised of corresponding estimation of height, date and time of global positioning system, precision value dilution, status of fix, temperature, including horizontal and vertical activity sensor counts in intervals that are fixed. Units of collar were well compacted, robust, and of about 1 kg in weight. Location fixes for over a day period were showed through testing to be accurate, at roughly 95% for eight minutes of time after correction of the difference. There was no bias of direction on the part of errors that have consistency with other studies’ finding.
Keywords: Cattle, Collar, Behaviour, Network, GPS
Scope of the Article: Behaviour of Structures.