TY - JOUR
T1 - An AWS-Enabled IoT Architecture for Real-Time Livestock Health Monitoring and Predictive Analytics
AU - George Wilson
AU - Chloe Bennett
AU - Ethan Wright
AU - Jack Turner
JF - Journal of Intelligent Agriculture and Food Systems
Y1 - 2024
VL - 3
IS - 1
SP - 94
N2 - Presently, the agricultural domain faces major hurdles in efficiently monitoring livestock health. Established observation practices tend to be labor-heavy, slow, and ill-suited to the evolving requirements of contemporary farming. The rapid proliferation of IoT devices in this field has brought scalability issues and increased processing demands to the forefront, creating an urgent need for streamlined, scalable architectures. This work proposes a cloud-centric framework to elevate the standard of livestock wellness tracking. Engineered to monitor key physiological metrics such as motility, thermal state, and cardiac rhythm, the setup leverages AWS for resilient data orchestration, alongside Python for analytical computation and live-stream analytics. The framework embraces Narrow Band IoT (NB-IoT) mechanisms, fine-tuned for minimal bandwidth usage and extended transmission range, which are ideal for isolated agricultural terrains. Its scalable design enables seamless administration of a dynamic number of IoT devices, a vital feature for accommodating changes in livestock density and operational scale. Early-stage testing conducted to gauge system capability has confirmed its resilience and practical value, reflecting a cohesive integration of AWS IoT Cloud capabilities with field-level IoT devices. Beyond this, the inquiry examines the deployment of predictive algorithmic models to support anticipatory healthcare strategies in animal populations. By forecasting impending health anomalies before visible symptoms, the mechanism stands to advance animal well-being and farm output substantially. The confluence of cloud computing power and IoT infrastructure not only meets the intensifying digital demands of modern agriculture but also pioneers a new paradigm for sustainable ecological farming methods. The revelations from this investigation may carry far-reaching weight for the trajectory of animal stock oversight, potentially catalyzing broad-based acceptance of digitally driven wellness surveillance frameworks across the farming sector. Such a shift would aid in streamlining husbandry-based health management worldwide, thereby enhancing yields and long-term viability in the agrarian economy.
UR - https://airpublications.com/b160990742
ER -