TY - JOUR
T1 - Development and field installation of smart sensor nodes for quantification of missing water in soil
AU - Afridi, Waqas A. K.
AU - Vitoria, Ignacio
AU - Jayasundera, Krishanthi
AU - Mukhopadhyay, S. C.
AU - Liu, Zhi
PY - 2023/11/1
Y1 - 2023/11/1
N2 - The article presents an experimental study conducted to mitigate the rising water data uncertainty in the current water monitoring network of NSW, Australia. For this, IoT-enabled multidepth-embedded microcontroller-based smart sensor nodes have been developed comprising of low-cost low-power off-the-shelf sensors and essential electronic components. In the course of development, the developed system has been tested for functional improvements in a controlled environment before open-field installations. The deployed system is used as a real-time monitoring tool for data visualization on an IoT analytics platform. As a foundation, the study implemented a regression model and correlation analysis on the field dataset to understand interdependencies of study variables, such as soil-moisture (SM), soil-temperature (ST), rain-precipitation (P), and environmental-temperature (T). The results obtained demonstrate a strong covariance and reliance of SM and ST on the P volume and the environmental temperature, respectively. It is expected that the real-time acquisition of soil water data through the smart sensor node offers a unique opportunity to further implement the predictive models of potential water recharge via soil profiles as well as to schedule suitable irrigation patterns for agricultural lands.[Graphic presents]
AB - The article presents an experimental study conducted to mitigate the rising water data uncertainty in the current water monitoring network of NSW, Australia. For this, IoT-enabled multidepth-embedded microcontroller-based smart sensor nodes have been developed comprising of low-cost low-power off-the-shelf sensors and essential electronic components. In the course of development, the developed system has been tested for functional improvements in a controlled environment before open-field installations. The deployed system is used as a real-time monitoring tool for data visualization on an IoT analytics platform. As a foundation, the study implemented a regression model and correlation analysis on the field dataset to understand interdependencies of study variables, such as soil-moisture (SM), soil-temperature (ST), rain-precipitation (P), and environmental-temperature (T). The results obtained demonstrate a strong covariance and reliance of SM and ST on the P volume and the environmental temperature, respectively. It is expected that the real-time acquisition of soil water data through the smart sensor node offers a unique opportunity to further implement the predictive models of potential water recharge via soil profiles as well as to schedule suitable irrigation patterns for agricultural lands.[Graphic presents]
UR - http://www.scopus.com/inward/record.url?scp=85173417983&partnerID=8YFLogxK
U2 - 10.1109/JSEN.2023.3317418
DO - 10.1109/JSEN.2023.3317418
M3 - Article
AN - SCOPUS:85173417983
SN - 1530-437X
VL - 23
SP - 26495
EP - 26502
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
IS - 21
ER -