Advancements in Cow Health Monitoring: A Systematic Literature Review of IoT Applications
Journal Title: Information Dynamics and Applications - Year 2023, Vol 2, Issue 4
Abstract
The landscape of livestock farming is undergoing a significant transformation, primarily influenced by the integration of the Internet of Things (IoT) technology. This systematic literature review (SLR) critically examines the role of IoT in enhancing cow health monitoring, a burgeoning field of research drawing considerable attention in recent years. Spanning articles published from 2017 to 2023 in eminent academic forums, this study meticulously selected and analyzed thirty publications. These were chosen through a structured process, evaluating each for its relevance based on title and abstract. The review encapsulates a thorough investigation of the applications, sensors, and devices underpinning IoT-based cow health monitoring systems. It is observed that the current research landscape is dynamically evolving, marked by emerging trends and noticeable gaps in technology and application. This synthesis of existing literature offers an insightful overview of the potential and limitations inherent in current IoT solutions, highlighting their efficacy in real-world scenarios. Furthermore, this review delineates the challenges faced and posits future research directions to address unresolved issues in cow health monitoring. The primary objective of this systematic analysis is to consolidate research findings, thereby advancing the understanding of IoT's impact in this field. It also aims to foster a comprehensive dialogue on the technological advancements and their implications for future research endeavors in livestock farming.
Authors and Affiliations
Muhammad Hassaan
Keywords
Related Articles
- EP ID EP732666
- DOI https://doi.org/10.56578/ida020404
- Views 36
- Downloads 0
A Deep Convolutional Neural Network Framework for Enhancing Brain Tumor Diagnosis on MRI Scans
Brain tumors are a critical public health concern, often resulting in limited life expectancy for patients. Accurate diagnosis of brain tumors is crucial to develop effective treatment strategies and improve patients' qu...
Enhanced Channel Estimation in Multiple-Input Multiple-Output Systems: A Dual Quadratic Decomposition Algorithm Approach for Interference Cancellation
In Multiple-Input Multiple-Output (MIMO) systems, a considerable number of antennas are deployed at each base station, utilizing Time-shifted pilot contamination strategies. It was observed that Time-shifted pilot contam...
A Scalable Framework to Analyze Data from Heterogeneous Sources at Different Levels of Granularity
There is an enormous amount of data present in many different formats, including databases (MsSql, MySQL, etc.), data repositories (.txt, html, pdf, etc.), and MongoDB (NoSQL, etc.). The processing, storing, and manageme...
A Data-Driven Innovation Model of Big Data Digital Learning and Its Empirical Study
Digital learning is the use of telecommunication technology to deliver information for education and training. As the increased acceleration of the propagation speed of the web, a lot of data collected by automated or se...
MR Image Feature Analysis for Alzheimer’s Disease Detection Using Machine Learning Approaches
Alzheimer’s disease (AD), a progressive neurological disorder, predominantly impacts cognitive functions, manifesting as memory loss and deteriorating thinking abilities. Recognized as the primary form of dementia, this...