Al Moshi Md Adnan, Hardie Marcus, Choudhury Tanveer, Kamruzzaman Joarder
Centre for Smart Analytics (CSA), Federation University Australia, Churchill, VIC 3842, Australia.
Cooperative Research Centre for High Performance Soils (Soil CRC), Callaghan, NSW 2308, Australia.
Sensors (Basel). 2024 May 14;24(10):3113. doi: 10.3390/s24103113.
The rapid advancement toward smart cities has accelerated the adoption of various Internet of Things (IoT) devices for underground applications, including agriculture, which aims to enhance sustainability by reducing the use of vital resources such as water and maximizing production. On-farm IoT devices with above-ground wireless nodes are vulnerable to damage and data loss due to heavy machinery movement, animal grazing, and pests. To mitigate these risks, wireless Underground Sensor Networks (WUSNs) are proposed, where devices are buried underground. However, implementing WUSNs faces challenges due to soil heterogeneity and the need for low-power, small-size, and long-range communication technology. While existing radio frequency (RF)-based solutions are impeded by substantial signal attenuation and low coverage, acoustic wave-based WUSNs have the potential to overcome these impediments. This paper is the first attempt to review acoustic propagation models to discern a suitable model for the advancement of acoustic WUSNs tailored to the agricultural context. Our findings indicate the Kelvin-Voigt model as a suitable framework for estimating signal attenuation, which has been verified through alignment with documented outcomes from experimental studies conducted in agricultural settings. By leveraging data from various soil types, this research underscores the feasibility of acoustic signal-based WUSNs.
向智慧城市的快速发展加速了各种物联网(IoT)设备在地下应用中的采用,包括农业领域,其旨在通过减少水等重要资源的使用并实现产量最大化来提高可持续性。带有地上无线节点的农场物联网设备容易因重型机械移动、动物啃食和害虫而受损及数据丢失。为降低这些风险,人们提出了无线地下传感器网络(WUSN),即设备埋于地下的网络。然而,由于土壤的非均质性以及对低功耗、小尺寸和远距离通信技术的需求,实施WUSN面临挑战。虽然现有的基于射频(RF)的解决方案受到信号大幅衰减和覆盖范围小的阻碍,但基于声波的WUSN有潜力克服这些障碍。本文首次尝试回顾声学传播模型,以辨别适合农业环境的声学WUSN发展的合适模型。我们的研究结果表明,开尔文 - 沃伊特模型是估计信号衰减的合适框架,这已通过与在农业环境中进行的实验研究记录结果进行比对得到验证。通过利用来自各种土壤类型的数据,本研究强调了基于声学信号的WUSN的可行性。