Department of Electrical and Electronic Engineering, United International University, United City, Badda, Dhaka 1212, Bangladesh.
Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK S7N 5A9, Canada.
Sensors (Basel). 2021 Sep 9;21(18):6040. doi: 10.3390/s21186040.
Water, one of the most valuable resources, is underutilized in irrigated rice production. The yield of rice, a staple food across the world, is highly dependent on having proper irrigation systems. Alternate wetting and drying (AWD) is an effective irrigation method mainly used for irrigated rice production. However, unattended, manual, small-scale, and discrete implementations cannot achieve the maximum benefit of AWD. Automation of large-scale (over 1000 acres) implementation of AWD can be carried out using wide-area wireless sensor network (WSN). An automated AWD system requires three different WSNs: one for water level and environmental monitoring, one for monitoring of the irrigation system, and another for controlling the irrigation system. Integration of these three different WSNs requires proper dimensioning of the AWD edge elements (sensor and actuator nodes) to reduce the deployment cost and make it scalable. Besides field-level monitoring, the integration of external control parameters, such as real-time weather forecasts, plant physiological data, and input from farmers, can further enhance the performance of the automated AWD system. Internet of Things (IoT) can be used to interface the WSNs with external data sources. This research focuses on the dimensioning of the AWD system for the multilayer WSN integration and the required algorithms for the closed loop control of the irrigation system using IoT. Implementation of the AWD for 25,000 acres is shown as a possible use case. Plastic pipes are proposed as the means to transport and control proper distribution of water in the field, which significantly helps to reduce conveyance loss. This system utilizes 250 pumps, grouped into 10 clusters, to ensure equal water distribution amongst the users (field owners) in the wide area. The proposed automation algorithm handles the complexity of maintaining proper water pressure throughout the pipe network, scheduling the pump, and controlling the water outlets. Mathematical models are presented for proper dimensioning of the AWD. A low-power and long-range sensor node is developed due to the lack of cellular data coverage in rural areas, and its functionality is tested using an IoT platform for small-scale field trials.
水是最有价值的资源之一，但在灌溉水稻生产中未得到充分利用。作为全球主要粮食作物，水稻的产量高度依赖于合理的灌溉系统。间歇灌溉（AWD）是一种有效的灌溉方法，主要用于灌溉水稻生产。然而，无人值守、手动、小规模和离散的实施方式无法实现 AWD 的最大效益。可以使用广域无线传感器网络（WSN）实现大规模（超过 1000 英亩）AWD 的自动化。自动化 AWD 系统需要三个不同的 WSN：一个用于水位和环境监测，一个用于灌溉系统监测，另一个用于控制灌溉系统。这三个不同的 WSN 的集成需要适当的 AWD 边缘元素（传感器和执行器节点）尺寸设计，以降低部署成本并使其具有可扩展性。除了现场级监测外，还可以集成外部控制参数，例如实时天气预报、植物生理数据以及农民的输入，从而进一步提高自动化 AWD 系统的性能。物联网（IoT）可用于将 WSN 与外部数据源进行接口。本研究重点介绍了用于多层 WSN 集成的 AWD 系统的尺寸设计，以及使用 IoT 对灌溉系统进行闭环控制所需的算法。展示了在 25000 英亩土地上实施 AWD 的可能性。提出使用塑料管作为在田间输送和控制适当配水的手段，这显著有助于减少输送损失。该系统使用 250 个泵，分为 10 个集群，以确保在广大区域内为用户（田地所有者）提供均等的水量分配。所提出的自动化算法处理了在整个管网中保持适当水压、调度泵和控制出水口的复杂性。为了进行适当的 AWD 尺寸设计，提出了数学模型。由于农村地区缺乏蜂窝数据覆盖，因此开发了低功耗和长距离传感器节点，并使用物联网平台对其进行了小规模现场试验的功能测试。
