An Evaluation of Sensor Technologies Suitable for Domestic Livestock Business Production and Health Management

Clicks: 1
ID: 313096
2024
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #683 of 705 articles by views in Journal of Computing & Biomedical Informatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 705 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The globe is actively pursuing the digitalization of social, economic, and political activities. With the advancement of technology in several fields, including agriculture, livestock production is also an area that necessitates the utilization of developing technologies. However, knowledge and competence are quite limited, especially in underdeveloped nations. Therefore, it is crucial to address this knowledge deficit by gathering information and disseminating it to a wide audience to facilitate continued study in the field. With the emergence of sensors designed for various domains, it is crucial to explore the potential utilization of these technologies in evaluating the status of rangelands and enhancing animal output. Technologies play a crucial role in implementing precision farming practices for livestock, specifically in monitoring individual animal behavior, grazing conditions, health status, and fodder consumption. Assessing both the grazing behavior of cattle and the characteristics of the rangeland is crucial for managing grazing stock. Rangeland resources play a crucial role in global cattle production. The abundance, species composition, and chemical composition of forages and pasture undergo changes due to environmental and management factors, resulting in dynamic fluctuations. Assessment and monitoring of rangeland resources are necessary for improved management and utilization. Traditional evaluations that include human or mechanical tallying, recognition, and analysis of chemical makeup are arduous and time-consuming. Sensors can be used to monitor the state of grazing areas and understand the grazing behavior of animals in field circumstances. This information can help improve the management of grazing stock. In order to enhance or substitute traditional methods, it is crucial to comprehend the existing technology, such as sensors or biosensors. The purpose of this review study is to enhance knowledge about the existing technologies and their significance in relation to rangeland resources, specifically in tropical rangelands. Typically, in tropical regions, GPS systems are frequently employed to evaluate the condition of rangelands, but they do not take into account the grazing stock. The analysis further clarifies that sensor technologies play a crucial role in swiftly and effortlessly detecting cattle health problems and movements at the field level. Nevertheless, similar to other technological advancements, sensors (specifically biosensors) has certain limitations, such as the precision of measurements and the occurrence of repeating data allegations. However, the assessment clarifies that the implementation of sensor technologies in animal production can effectively reduce the amount of time and energy required.
Reference Key
imported_1777058999_69ebc4b7adf3d Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Khadija Altaf
Journal Journal of Computing & Biomedical Informatics
Year 2024
DOI
DOI not found
URL
https://jcbi.org/index.php/Main/article/view/491
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.