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• W3198486335 abstract "Wireless underground sensor networks (WUSNs) constitute one of the promising application areas of the recently developed wireless sensor networking (WSN) techniques. WUSN is a specialized kind of WSN that mainly focuses on the use of sensors at the subsurface region of the soil. For a long time, this region has been used to bury sensors, usually targeting irrigation and environment monitoring applications, although without wireless communication capability; WUSNs promise to fill this gap and provide the infrastructure for novel applications. The underground wireless channel was only available recently. Communication through the underground medium has been a challenging research area. The applications require the deployment of sensors below the ground surface. Hence, the sensor becomes part of the sensed environment and might deliver more precise sensing. WUSNs, which have components, i.e., the sensors, are buried underground and communicate through soil. The majority of the applications for WUSNs are used for intelligent agriculture and environmental monitoring of the soil. In this proposed system, moisture content of the soil in land is measured using the sensors and is sent to the centralized server through IoT for monitoring. Our focusing area in this project is that the measured moisture value in the soil is transmitted via the existing soil. An advanced channel model is presented that was developed to characterize the underground wireless channel considering the characteristics of the propagation of EM waves in soil and their relation with the frequency of these waves, the soil composition, and the soil moisture. It helps the farmers to monitor their land without stepping into fields and it also uses automatic irrigation system. When the water moisture is lower than the actual content in the soil, then the automatic irrigation system is used to water the crops even when the farmer has missed to water the crops. This type of irrigation helps to maintain the moisture of the soil for a long period. Contributor Name Affiliation Details Dr. G. Jaspher W. Kathrine Karunya Institute of Technology and Sciences, Coimbatore, Corresponding author: kathrine@karunya.edu Dr. Priscilla Rajadurai St. Joseph’s Institute of Technology, Chennai, prisci.christa@gmail.com" @default.
• W3198486335 created "2021-09-13" @default.
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• W3198486335 date "2021-09-07" @default.
• W3198486335 modified "2023-09-25" @default.
• W3198486335 title "An Intelligent Deep Learning-Based Wireless Underground Sensor System for IoT-Based Agricultural Application" @default.
• W3198486335 doi "https://doi.org/10.1201/9781003119838-13" @default.
• W3198486335 hasPublicationYear "2021" @default.
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