IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends
The world population currently stands at about 7 billion amidst an expected increase in 2030 from 9.4 billion to around 10 billion in 2050. This burgeoning population has continued to influence the upward demand for animal food. Moreover, the management of finite resources such as land, the need to...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Big Data and Cognitive Computing |
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| Online Access: | https://www.mdpi.com/2504-2289/5/1/10 |
| _version_ | 1797395120019996672 |
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| author | Bernard Ijesunor Akhigbe Kamran Munir Olugbenga Akinade Lukman Akanbi Lukumon O. Oyedele |
| author_facet | Bernard Ijesunor Akhigbe Kamran Munir Olugbenga Akinade Lukman Akanbi Lukumon O. Oyedele |
| author_sort | Bernard Ijesunor Akhigbe |
| collection | DOAJ |
| description | The world population currently stands at about 7 billion amidst an expected increase in 2030 from 9.4 billion to around 10 billion in 2050. This burgeoning population has continued to influence the upward demand for animal food. Moreover, the management of finite resources such as land, the need to reduce livestock contribution to greenhouse gases, and the need to manage inherent complex, highly contextual, and repetitive day-to-day livestock management (LsM) routines are some examples of challenges to overcome in livestock production. The Internet of Things (IoT)’s usefulness in other vertical industries (OVI) shows that its role will be significant in LsM. This work uses the systematic review methodology of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to guide a review of existing literature on IoT in OVI. The goal is to identify the IoT’s ecosystem, architecture, and its technicalities—present status, opportunities, and expected future trends—regarding its role in LsM. Among identified IoT roles in LsM, the authors found that data will be its main contributor. The traditional approach of reactive data processing will give way to the proactive approach of augmented analytics to provide insights about animal processes. This will undoubtedly free LsM from the drudgery of repetitive tasks with opportunities for improved productivity. |
| first_indexed | 2024-03-09T00:29:51Z |
| format | Article |
| id | doaj.art-c24bd5e53fb0425e8b406d320b3c618e |
| institution | Directory Open Access Journal |
| issn | 2504-2289 |
| language | English |
| last_indexed | 2024-03-09T00:29:51Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Big Data and Cognitive Computing |
| spelling | doaj.art-c24bd5e53fb0425e8b406d320b3c618e2023-12-11T18:37:11ZengMDPI AGBig Data and Cognitive Computing2504-22892021-02-01511010.3390/bdcc5010010IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future TrendsBernard Ijesunor Akhigbe0Kamran Munir1Olugbenga Akinade2Lukman Akanbi3Lukumon O. Oyedele4Department of Computer Science & Engineering, Obafemi Awolowo University, Ile-Ife 220282, NigeriaDepartment of Computer Science and Creative Technology, University of the West of England, Bristol BS16 1QY, UKBig Data Enterprise and Artificial Intelligence Laboratory, University of the West of England, Bristol BS16 1QY, UKDepartment of Computer Science & Engineering, Obafemi Awolowo University, Ile-Ife 220282, NigeriaBig Data Enterprise and Artificial Intelligence Laboratory, University of the West of England, Bristol BS16 1QY, UKThe world population currently stands at about 7 billion amidst an expected increase in 2030 from 9.4 billion to around 10 billion in 2050. This burgeoning population has continued to influence the upward demand for animal food. Moreover, the management of finite resources such as land, the need to reduce livestock contribution to greenhouse gases, and the need to manage inherent complex, highly contextual, and repetitive day-to-day livestock management (LsM) routines are some examples of challenges to overcome in livestock production. The Internet of Things (IoT)’s usefulness in other vertical industries (OVI) shows that its role will be significant in LsM. This work uses the systematic review methodology of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to guide a review of existing literature on IoT in OVI. The goal is to identify the IoT’s ecosystem, architecture, and its technicalities—present status, opportunities, and expected future trends—regarding its role in LsM. Among identified IoT roles in LsM, the authors found that data will be its main contributor. The traditional approach of reactive data processing will give way to the proactive approach of augmented analytics to provide insights about animal processes. This will undoubtedly free LsM from the drudgery of repetitive tasks with opportunities for improved productivity.https://www.mdpi.com/2504-2289/5/1/10IoT technologiesIoT ecosystem and architectureartificial intelligencebig datacloud computing5G nexus |
| spellingShingle | Bernard Ijesunor Akhigbe Kamran Munir Olugbenga Akinade Lukman Akanbi Lukumon O. Oyedele IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends Big Data and Cognitive Computing IoT technologies IoT ecosystem and architecture artificial intelligence big data cloud computing 5G nexus |
| title | IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends |
| title_full | IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends |
| title_fullStr | IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends |
| title_full_unstemmed | IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends |
| title_short | IoT Technologies for Livestock Management: A Review of Present Status, Opportunities, and Future Trends |
| title_sort | iot technologies for livestock management a review of present status opportunities and future trends |
| topic | IoT technologies IoT ecosystem and architecture artificial intelligence big data cloud computing 5G nexus |
| url | https://www.mdpi.com/2504-2289/5/1/10 |
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