Systematic Review on Internet of Things in Smart Livestock Management Systems

Sebastian Terence, Jude Immaculate (), Anishin Raj and Jeba Nadarajan
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Sebastian Terence: Department of Artificial Intelligence and Machine Learning, Karunya Institute of Technology and Sciences, Coimbatore 641114, India
Jude Immaculate: Department of Mathematics, Karunya Institute of Technology and Sciences, Coimbatore 641114, India
Anishin Raj: Department of Computer Science and Engineering, Muthoot Institute of Technology and Science, Varikoli 682308, India
Jeba Nadarajan: Department of Computer Science and Engineering, Kumaraguru College of Technology, Coimbatore 641049, India

Sustainability, 2024, vol. 16, issue 10, 1-37

Abstract: The advent of the Internet of Things (IoT) has sparked the creation of numerous improved and new applications across numerous industries. Data collection from remote locations and remote object control are made possible by Internet of Things technology. The IoT has numerous applications in fields such as education, healthcare, agriculture, smart cities, and smart homes. Numerous studies have recently employed IoT technology to automate livestock farm operations. We looked at IoT-based livestock farm management systems in this study. To select the publications for this investigation, we conducted a systematic literature review (SLR) that complied with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. The selected articles were divided into different categories according to their applications. Sensors, actuators, the main controller (gateway), communication protocols, storage, energy consumption, the use of renewable energy sources, scalability, security, and prediction techniques applied to the data collected for future prediction were all examined in this study as IoT technologies used to monitor animals. In this study, we found that only 22% of the articles addressed security concerns, 24% discussed scalability, 16% discussed renewable energy, 18% attempted energy consumption, and 33% employed prediction techniques based on the collected data. The challenges and future directions of intelligent livestock farming are emphasized.

Keywords: animal monitoring; Internet of Things; cattle monitoring; smart livestock management (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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