Dineva Kristina, Atanasova Tatiana
Department of Modelling and Optimization, Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria.
Animals (Basel). 2021 Sep 15;11(9):2697. doi: 10.3390/ani11092697.
In the ecological future of the planet, intelligent agriculture relies on CPS and IoT to free up human resources and increase production efficiency. Due to the growing number of connected IoT devices, the maximum scalability capacity, and available computing power of the existing architectural frameworks will be reached. This necessitates finding a solution that meets the continuously growing demands in smart farming. Cloud-based IoT solutions are achieving increasingly high popularity. The aim of this study was to design a scalable cloud-based architecture for a smart livestock monitoring system following Agile methodology and featuring environmental monitoring, health, growth, behaviour, reproduction, emotional state, and stress levels of animals. The AWS services used, and their specific tasks related to the proposed architecture are explained in detail. A stress test was performed to prove the data ingesting and processing capability of the proposed architecture. Experimental results proved that the proposed architecture using AWS automated scaling mechanisms and IoT devices are fully capable of processing the growing amount of data, which in turn allow for meeting the required needs of the constantly expanding number of CPS systems.
在地球的生态未来中，智能农业依靠信息物理系统（CPS）和物联网（IoT）来解放人力资源并提高生产效率。由于连接的物联网设备数量不断增加，现有架构框架的最大可扩展性容量和可用计算能力将达到极限。这就需要找到一种能够满足智能农业中持续增长需求的解决方案。基于云的物联网解决方案越来越受欢迎。本研究的目的是遵循敏捷方法设计一种用于智能畜牧监测系统的可扩展的基于云的架构，该架构具有环境监测、动物健康、生长、行为、繁殖、情绪状态和压力水平等功能。详细解释了所使用的亚马逊云服务（AWS）及其与所提出架构相关的具体任务。进行了压力测试以证明所提出架构的数据摄取和处理能力。实验结果证明，所提出的使用AWS自动扩展机制和物联网设备的架构完全有能力处理不断增长的数据量，这反过来又能够满足不断扩展的信息物理系统数量的需求。
