Development of a cloud-based IoT system for livestock health monitoring using AWS and python
The agriculture industry is currently facing significant challenges in effectively monitoring the health of livestock. Traditional methods of health monitoring are often labor-intensive, inefficient, and insufficiently responsive to the needs of modern farming. As the number of IoT devices in agricu...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375524001291 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850245085916037120 |
|---|---|
| author | Harini Shree Bhaskaran Miriam Gordon Suresh Neethirajan |
| author_facet | Harini Shree Bhaskaran Miriam Gordon Suresh Neethirajan |
| author_sort | Harini Shree Bhaskaran |
| collection | DOAJ |
| description | The agriculture industry is currently facing significant challenges in effectively monitoring the health of livestock. Traditional methods of health monitoring are often labor-intensive, inefficient, and insufficiently responsive to the needs of modern farming. As the number of IoT devices in agriculture proliferates, issues of scalability and computational load have become prominent, necessitating efficient and scalable solutions. This research introduces a cloud-based architecture aimed at enhancing livestock health monitoring. This system is designed to track critical health indicators such as movement patterns, body temperature, and heart rate, utilizing AWS for robust data handling and Python for data processing and real-time analytics. The proposed system incorporates Narrow Band IoT (Nb IoT) technology, which is optimized for low-bandwidth, long-range communication, making it suitable for rural and remote farming locations. The architecture's scalability allows for the effective management of varying numbers of IoT devices, which is essential for adapting to changing herd sizes and farm scales. Preliminary experiments conducted to assess the system's performance have demonstrated its durability and effectiveness, indicating a successful integration of AWS IoT Cloud services with the deployed IoT devices. Furthermore, the study explores the implementation of predictive analytics to facilitate proactive health management in livestock. By predicting potential health issues before they become apparent, the system can offer significant improvements in animal welfare and farm efficiency. The integration of cloud computing and IoT not only meets the growing technological needs of modern agriculture but also sets a new benchmark in the development of sustainable farming practices. The findings from this research could have broad implications for the future of livestock management, potentially leading to widespread adoption of technology-driven health monitoring systems in agriculture. This would help in optimizing the health management of livestock globally, thereby enhancing productivity and sustainability in the agricultural sector. |
| format | Article |
| id | doaj-art-5d2dcac2e63b47539444ca94bedeb82a |
| institution | OA Journals |
| issn | 2772-3755 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj-art-5d2dcac2e63b47539444ca94bedeb82a2025-08-20T01:59:34ZengElsevierSmart Agricultural Technology2772-37552024-12-01910052410.1016/j.atech.2024.100524Development of a cloud-based IoT system for livestock health monitoring using AWS and pythonHarini Shree Bhaskaran0Miriam Gordon1Suresh Neethirajan2Faculty of Computer Science, 6050 University Avenue, Dalhousie University, Halifax, CanadaFaculty of Agriculture, Agricultural Campus, PO Box 550, Dalhousie University, Truro, NS B2N 5E3, CanadaFaculty of Computer Science, 6050 University Avenue, Dalhousie University, Halifax, Canada; Faculty of Agriculture, Agricultural Campus, PO Box 550, Dalhousie University, Truro, NS B2N 5E3, Canada; Corresponding author.The agriculture industry is currently facing significant challenges in effectively monitoring the health of livestock. Traditional methods of health monitoring are often labor-intensive, inefficient, and insufficiently responsive to the needs of modern farming. As the number of IoT devices in agriculture proliferates, issues of scalability and computational load have become prominent, necessitating efficient and scalable solutions. This research introduces a cloud-based architecture aimed at enhancing livestock health monitoring. This system is designed to track critical health indicators such as movement patterns, body temperature, and heart rate, utilizing AWS for robust data handling and Python for data processing and real-time analytics. The proposed system incorporates Narrow Band IoT (Nb IoT) technology, which is optimized for low-bandwidth, long-range communication, making it suitable for rural and remote farming locations. The architecture's scalability allows for the effective management of varying numbers of IoT devices, which is essential for adapting to changing herd sizes and farm scales. Preliminary experiments conducted to assess the system's performance have demonstrated its durability and effectiveness, indicating a successful integration of AWS IoT Cloud services with the deployed IoT devices. Furthermore, the study explores the implementation of predictive analytics to facilitate proactive health management in livestock. By predicting potential health issues before they become apparent, the system can offer significant improvements in animal welfare and farm efficiency. The integration of cloud computing and IoT not only meets the growing technological needs of modern agriculture but also sets a new benchmark in the development of sustainable farming practices. The findings from this research could have broad implications for the future of livestock management, potentially leading to widespread adoption of technology-driven health monitoring systems in agriculture. This would help in optimizing the health management of livestock globally, thereby enhancing productivity and sustainability in the agricultural sector.http://www.sciencedirect.com/science/article/pii/S2772375524001291Cloud computingInternet of Things (IoT)Livestock health monitoringPredictive analyticsAmazon web services (AWS) |
| spellingShingle | Harini Shree Bhaskaran Miriam Gordon Suresh Neethirajan Development of a cloud-based IoT system for livestock health monitoring using AWS and python Smart Agricultural Technology Cloud computing Internet of Things (IoT) Livestock health monitoring Predictive analytics Amazon web services (AWS) |
| title | Development of a cloud-based IoT system for livestock health monitoring using AWS and python |
| title_full | Development of a cloud-based IoT system for livestock health monitoring using AWS and python |
| title_fullStr | Development of a cloud-based IoT system for livestock health monitoring using AWS and python |
| title_full_unstemmed | Development of a cloud-based IoT system for livestock health monitoring using AWS and python |
| title_short | Development of a cloud-based IoT system for livestock health monitoring using AWS and python |
| title_sort | development of a cloud based iot system for livestock health monitoring using aws and python |
| topic | Cloud computing Internet of Things (IoT) Livestock health monitoring Predictive analytics Amazon web services (AWS) |
| url | http://www.sciencedirect.com/science/article/pii/S2772375524001291 |
| work_keys_str_mv | AT harinishreebhaskaran developmentofacloudbasediotsystemforlivestockhealthmonitoringusingawsandpython AT miriamgordon developmentofacloudbasediotsystemforlivestockhealthmonitoringusingawsandpython AT sureshneethirajan developmentofacloudbasediotsystemforlivestockhealthmonitoringusingawsandpython |