Wireless Underground Channel Modeling

A comprehensive treatment of wireless underground channel modeling is presented in this chapter. The impacts of the soil on bandwidth and path loss are analyzed. A mechanism for the UG channel sounding and multipath characteristics analysis is discussed. Moreover, novel time-domain impulse response model for WUC is reviewed with the explanation of model parameters and statistics. Furthermore, different types of the through-the-soil wireless communications are surveyed. Finally, the chapter concludes with discussion of the UG wireless statistical model and path loss model for through-the-soil wireless communications in decision agriculture. The model presented in this chapter is also validated with empirical data

Current Advances in Internet of Underground Things

The latest developments in Internet of Underground Things are covered in this chapter. First, the IOUT Architecture is discussed followed by the explanation of the challenges being faced in this paradigm. Moreover, a comprehensive coverage of the different IOUT components is presented that includes communications, sensing, and system integration with the cloud. An in-depth coverage of the applications of the IOUT in various disciplines is also surveyed. These applications include areas such as decision agriculture, pipeline monitoring, border control, and oil wells

Decision Agriculture

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and crop growth are also analyzed

Electromagnetic Characteristics of the Soil

The electromagnetic characteristics of the soil are discussed in this chapter. The characteristics of porous bedrock, soil medium, and impacts of rain attenuations are also presented. The models of dielectric soil properties are studied with a rigorous focus on the constitutive parameters of subsurface soil medium. Moreover, the permittivity and wavenumber in soil are explained. In addition, the frequency-dependent dielectric properties such as dispersion in soil, absorption characteristic, and penetration depth versus frequency are reviewed. Furthermore, the effective permittivity of soil–water mixture for through-the soil-propagation mechanism is analyzed thoroughly

Underground Phased Arrays and Beamforming Applications

This chapter presents a framework for adaptive beamforming in underground communication. The wireless propagation is thoroughly analyzed to develop a model using the soil moisture as an input parameter to provide feedback mechanism while enhancing the system performance. The working of array element in the soil is analyzed. Moreover, the effect of soil texture and soil moisture on the resonant frequency and return loss is studied in detail. The wave refraction from the soil–air interface highly degrades the performance of the system. Furthermore, to beam steering is done to achieve high gain for lateral component improving the UG communication. The angle enhancing the lateral wave depends upon dielectric properties and usually ranges from 0∘ to 16∘. These dielectric properties change with the change in soil moisture and soil texture. It is shown from the experiments that optimal UG lateral angle is high at lower soil moisture readings and decreases with decrease in soil moisture. A planar structure of antenna array and different techniques for optimization are proposed for enhanced soil moisture adaptive beamforming. UG channel impulse response is studied from the beamforming aspect to identify the components of EM waves propagating through the soil. An optimum steering method for beamforming is presented which adapts to the changing values of soil moisture. Finally, the limitations of UG beamforming are presented along with the motivation to use it

Signals in the Soil: An Introduction to Wireless Underground Communications

In this chapter, wireless underground (UG) communications are introduced. A detailed overview of WUC is given. A comprehensive review of research challenges in WUC is presented. The evolution of underground wireless is also discussed. Moreover, different component of UG communications is wireless. The WUC system architecture is explained with a detailed discussion of the anatomy of an underground mote. The examples of UG wireless communication systems are explored. Furthermore, the differences of UG wireless and over-the-air wireless are debated. Different types of wireless underground channel (e.g., In-Soil, Soil-to-Air, and Air-to-Soil) are reported as well

Spatio-temporal characteristics of point and field sources in wireless sensor networks

Wireless Sensor Networks (WSN) are comprised of densely deployed sensor nodes collaboratively observing and communicating extracted information about a physical phenomenon. Dense deployment of sensor nodes makes the sensor observations highly correlated in the space domain. In addition, consecutive samples obtained by a sensor node are also temporally correlated for the applications involving the observation of the variation of a physical phenomenon. Based on the physical characteristics and dispersion pattern over the area, the phenomenon to be observed can be modeled as point source or field source. Clearly, understanding the spatio-temporal correlation characteristics of the point and field sources brings potential advantages to be exploited in the design of efficient communication protocols. In this paper, a theoretical analysis of spatio-temporal correlation in WSN is carried out. The objective of this analysis is to capture the spatio-temporal characteristics of point and field sources in WSN. First, the model for point and field sources are developed and their spatio-temporal characteristics are analytically derived along with the distortion functions. Based on the theoretical analysis, numerical simulations are performed. This analytical work provides tools for finding the feasible operating region in terms of spatial and temporal resolution for a specific distortion constraint considering spatio-temporal correlation, signal properties, and network variables in WSN. © 2006 IEEE

On the cross-layer interactions between congestion and contention in wireless sensor and actor networks

Wireless Sensor and Actor Networks (WSAN) are composed of large number of sensor nodes collaboratively observing a physical phenomenon and relatively smaller number of actor nodes, which act upon the sensed phenomenon. Due to the limited capacity of shared wireless medium and memory restrictions of the sensor nodes, channel contention and network congestion can be experienced during the operation of the network. In fact, the multi-hop nature of WSAN entangles the level of local contention and the experienced network congestion. Therefore, the unique characteristics of WSAN necessitate a comprehensive analysis of the network congestion and contention under various network conditions. In this paper, we comprehensively investigate the interactions between contention resolution and congestion control mechanisms as well as the physical layer effects in WSAN. An extensive set of simulations are performed in order to quantify the impacts of several network parameters on the overall network performance. The results of our analysis reveal that the interdependency between network parameters call for adaptive cross-layer mechanisms for efficient data delivery in WSAN. © 2007 Elsevier B.V. All rights reserved

Spatio-temporal correlation: Theory and applications for wireless sensor networks

Wireless Sensor Networks (WSN) are characterized by the dense deployment of sensor nodes that continuously observe physical phenomenon. Due to high density in the network topology, sensor observations are highly correlated in the space domain. Furthermore, the nature of the physical phenomenon constitutes the temporal correlation between each consecutive observation of a sensor node. These spatial and temporal correlations along with the collaborative nature of the WSN bring significant potential advantages for the development of efficient communication protocols well-suited for the WSN paradigm. In this paper, several key elements are investigated to capture and exploit the correlation in the WSN for the realization of advanced efficient communication protocols. A theoretical framework is developed to model the spatial and temporal correlations in WSN. The objective of this framework is to enable the development of efficient communication protocols which exploit these advantageous intrinsic features of the WSN paradigm. Based on this framework, possible approaches are discussed to exploit spatial and temporal correlation for efficient medium access and reliable event transport in WSN, respectively. © 2004 Elsevier B.V. All rights reserved