Department of Electronics, Universidad Técnica Federico Santa María, Valparaíso 2390123, Chile.
Escuela de Ingeniería Eléctrica, Pontificia Universidad Católica de Valparaíso, Valparaíso 2362804, Chile.
Sensors (Basel). 2022 Apr 7;22(8):2824. doi: 10.3390/s22082824.
Nowadays, conventional agriculture farms lack high-level automated management due to the limited number of installed sensor nodes and measuring devices. Recent progress of the Internet of Things (IoT) technologies will play an essential role in future smart farming by enabling automated operations with minimum human intervention. The main objective of this work is to design and implement a flexible IoT-based platform for remote monitoring of agriculture farms of different scales, enabling continuous data collection from various IoT devices (sensors, actuators, meteorological masts, and drones). Such data will be available for end-users to improve decision-making and for training and validating advanced prediction algorithms. Unlike related works that concentrate on specific applications or evaluate technical aspects of specific layers of the IoT stack, this work considers a versatile approach and technical aspects at four layers: farm perception layer, sensors and actuators layer, communication layer, and application layer. The proposed solutions have been designed, implemented, and assessed for remote monitoring of plants, soil, and environmental conditions based on LoRaWAN technology. Results collected through both simulation and experimental validation show that the platform can be used to obtain valuable analytics of real-time monitoring that enable decisions and actions such as, for example, controlling the irrigation system or generating alarms. The contribution of this article relies on proposing a flexible hardware and software platform oriented on monitoring agriculture farms of different scales, based on LoRaWAN technology. Even though previous work can be found using similar technologies, they focus on specific applications or evaluate technical aspects of specific layers of the IoT stack.
如今,由于安装的传感器节点和测量设备数量有限,传统的农业农场缺乏高级别的自动化管理。物联网 (IoT) 技术的最新进展将通过最小化人工干预实现自动化操作,在未来的智能农业中发挥重要作用。这项工作的主要目标是设计和实现一个灵活的基于物联网的平台,用于远程监控不同规模的农业农场,实现从各种物联网设备(传感器、执行器、气象桅杆和无人机)持续收集数据。这些数据将可供最终用户使用,以改善决策,并用于训练和验证高级预测算法。与专注于特定应用或评估物联网堆栈特定层的技术方面的相关工作不同,这项工作考虑了一种通用方法和四个层面的技术方面:农场感知层、传感器和执行器层、通信层和应用层。所提出的解决方案已根据 LoRaWAN 技术设计、实现和评估,用于远程监控植物、土壤和环境条件。通过模拟和实验验证收集的结果表明,该平台可用于获取实时监控的有价值的分析,从而做出决策和采取行动,例如控制灌溉系统或生成警报。本文的贡献在于提出了一个基于 LoRaWAN 技术的、面向不同规模农业农场监控的灵活硬件和软件平台。尽管之前的工作可以使用类似的技术找到,但它们侧重于特定的应用或评估物联网堆栈特定层的技术方面。