Abstract
The problem of localization of nodes of a wireless sensor network placed in different physical media (anchor nodes above ground and sensor nodes underground) is addressed in this article. We use time of arrival of signals transmitted between neighboring sensor nodes and between satellite nodes and sensor nodes as the ranging measurement. The localization problem is formulated as a parameter estimation of the joint distribution of the time of arrival values. The probability distribution of the time of arrival of a signal is derived based on rigorous statistical analysis and its parameters are expressed in terms of the location coordinates of the sensor nodes. Maximum likelihood estimates of the nodes’ location coordinates as parameters of the joint distribution of the various time of arrival variables in the network are computed. Sensitivity analysis to study the variation in the estimates with respect to error in measured soil complex permittivity and magnetic permeability is presented to validate the model and methodology.
Highlights
Miniaturization of wireless enabled compute devices, sensors, and further advances in the field of automation and control have led to their adoption in agriculture
The underground transmission range is approximately 34 m in dry soil at a transmission power level of 30 dBm, yielding to an average of 3 neighbors per sensor node, whereas the air-to-soil transmission range is approximately 1000 m, as computed using the average received signal strength expressions given in Equations (23), (24) and (36)
We presented our study of sensor node localization for a wireless sensor network with anchor nodes placed above ground and sensor nodes deployed below ground surface
Summary
Miniaturization of wireless enabled compute devices, sensors, and further advances in the field of automation and control have led to their adoption in agriculture. Information and control technologies allow for the application of agricultural inputs such as irrigation, fertilizers, pesticides, etc., as per the precise needs which minimize the impact on the environment while maximizing the crop yield. Various factors determine the fertilizer uptake in a farm-field such as variability in plant population, nitrogen mineralization from organic matter, water stress, soil properties, pests, etc.—which vary in space and with time. While under-application affects crop yield, over-application of fertilizers can lead to issues such as aquatic hypoxia and contamination of ground and surface water resources. Production of nitrogen-based fertilizers affects the environment due to its high energy cost. Our group has been pursuing agriculture sensor design for soil [1,2,3,4,5,6,7,8,9,10,11,12,13] and plant health [14,15,16,17,18,19,20,21,22], modeling for soil moisture/nutrients and plant growth dynamics [23,24], and decision-making for irrigation and fertilization for over a decade [23,25]
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