Wireless Underground Sensor Networks Research Articles

Optimized Network lifetime and path loss of Underwater Wireless Sensor Network (UWSN) Using Multi-objective multi-verse optimization algorithm

In ocean scanning applications, such as ocean tracking, pollution sensor, ocean resource control, underwater system maintenance, etc, the underground wireless sensor networks (UWSNs) are commonly used. Due to the problems of underwater communication, underwater Wireless Sensor Networks (UWSN) have become a common research subject. One of the key purposes of an underwater network is to evaluate the improved path through the sensor nodes to the onshore station for the assignment of monitoring data. The transmission cycle requires energy from every node and energy is limited in UWSNs. The most demanding task in the underwater wireless sensor network, therefore, is energy efficiency. This paper focuses primarily on coping with the energy usage and network life.This paper proposes a Multi-Objective Multi-verse Optimization Algorithm (MOMVO) to optimize network life, path loss and minimize power consumption in UWNNs. In this paper, a comparative analysis of hierarchical routing protocols such as the stable election protocol (SEP), the Zonal-Stable Election Protocol (Z-SEP) and the LEACH-based Multi-Objective Multi-verse Optimization (MOMVO) is presented in a variety of performance metrics such as live nodes per round, base station packets (BS) per round, and dead nodes per round.

Study on the propagation characteristic of electromagnetic wave based on WUSN

Wireless underground sensor network (WUSN) is widely used in agriculture, frontier defense, and other fields with great research value. This paper takes the propagation characteristics of the electromagnetic waves that propagate in WUSN as research target, and systematically tests the effect of influence factors on the communication quality of electromagnetic waves. The influence factors are chosen on the basis of the propagation theory of electromagnetic waves. Specifically, the influence factors include the burial depth of sensor sub-node, the horizontal distance between nodes, the communication frequency, and the thickness of snow. Moreover, the experiments are carried out in normal and snow-covered soil. The propagation characteristic of electromagnetic waves is measured by received signal strength (RSS) and symbol error rate (SER). Finally, the selection of communication frequency in different application scenarios is concluded. The conclusions have a great significance for guiding the arrangement of WUSN nodes in different scenarios.

Data Collection in MI-Assisted Wireless Powered Underground Sensor Networks: Directions, Recent Advances, and Challenges

Wireless underground sensor networks (WUSNs) facilitate remote monitoring and control of various underground environments, which are suffering from a significant reliability problem. To address this problem and relieve the ongoing networking challenges, we propose a new concept, called the magnetic induction (MI)-assisted wireless powered underground sensor network (MI-WPUSN), which integrates the advantages of MI communication techniques with those of wireless power transfer mechanisms. MI-WPUSN offers a unique platform consisting of seven envisioned devices and four distinct communication modes to provide significant reliability potential, which is constrained by its complex and challenging data collection. To unlock the potential of MI-WPUSN, we provide a systematic research roadmap for MI-WPUSN data collection, spreading from sensor deployment to multiple channel access control and to frequency-selective routing establishment. Specifically, we first summarize the state-of-the-art research advances on sensor deployment, based on which we propose a bidirectional projection-based deployment topology that achieves high network reliability and discuss the sensor numerical determination problem resorting to weighted Voronoi diagrams. We then introduce the principles for multiple channel access control and review the existing research. Finally, after introducing kernel regression methods that can easily handle the frequency-selective property of MI-WPUSN, we develop a modified Q-learning-based routing protocol. In particular, we list and analyze the underlying challenges and related future issues in each direction.

Novel MIMO-UWB-Based AG-UG-AG Routing With Microbit Sensors for WUSN

In this letter, empirical with analytical methodology to decode-and-forward packets over aboveground-to-underground-to-aboveground systems in the wireless underground sensor network environment is corroborated. Multiple-input-multiple-output ultrawideband (MIMO-UWB) radio frequency links were empirically characterized and exploited using microbit moisture-measuring white light-emitting diodes in different volumetric water content and orientation depths. Relay-routing and selection using the novel maximum available channel capacity technique was accomplished. The simulation performance demonstrates relay-routing and selection impacts on channel conditions, overall outage probability, transmission power, and energy consumption, without depreciated aggregate system throughput.

FracBot Technology for Mapping Hydraulic Fractures

Summary Miniaturized transponder systems are under development for monitoring unconventional reservoirs, mapping hydraulic fractures, and determining other wellbore parameters. These gadgets are an extension of radio-frequency identification (RFID) and are known as fracture robot (FracBot) nodes to recognize wireless underground sensor networks (WUSNs) for characterization and mapping of hydraulic breakages in unconventional reservoirs. 3D constellation maps of proppant-bed placement are generated by autonomous localization algorithms as FracBots are injected during hydraulic-fracturing operations. To investigate this model, a FracBot platform was established to explore this concept, and three basic functions have been explained. First, we have developed an innovative cross-layer communication model for magnetic-induction (MI) networks in altering underground environments, coupled with selections of coding, modulation, and power control and a geographic forwarding structure. Second, we have developed an innovative MI-based localization framework to capture the locations of the randomly deployed FracBot nodes by exploiting the exceptional properties of the MI field. Third, we have proposed an energy model for a linear FracBot network scheme that provides reasonable data rates while preserving collected energy limitations. Finally, to examine the functionalities of FracBot nodes in air, sand, and stone media, a physical MI-based WUSN test bed was implemented. Experiments indicated that the constructed FracBots can form a communication link and transfer data over amplitude-shift keying (ASK) modulation with 1.6 kbit/sec as a data rate and a minimum receiver sensitivity of −70 dBm. The performance of near-field-communication (NFC) antennas was affected by sand and stone media, which ultimately affect MI signal propagation and decrease the energy transfer. In sand or stone media, augmented mismatch between transmitter and receiver antennas was detected, leading to the decision that an advanced matching circuit design or an adaptive-frequency feature should be integrated into the FracBot design. This permits an optimal energy transmission and consistent communication link through sand and stone media.

Energy‐Spectral Efficiency Optimization in Wireless Underground Sensor Networks Using Salp Swarm Algorithm

Achieving high data rate transmission is critically constrained by green communication metrics in Wireless Sensor Networks (WSNs). A unified metric ensuring a successful compromise between the energy efficiency (EE) and the spectral efficiency (SE) is, then, an interesting design criterion in such systems. In this paper, we focus on EE‐SE tradeoff optimization in Wireless Underground Sensor Networks (WUSNs) where signals penetrate through a challenging lossy soil medium and nodes’ power supply is critical. Underground sensor nodes gather and send sensory information to underground relay nodes which amplify‐and‐retransmit received signals to an aboveground sink node. We propose to optimize source and relay powers used for each packet transmission using an efficient recent metaheuristic optimization algorithm called Salp Swarm Algorithm (SSA). Thus, the optimal source and relay transmission powers, which maximize the EE‐SE tradeoff under the maximum allowed transmission powers and the initial battery capacity constraints, are obtained. Further, we study the case where the underground medium properties are dynamic and change from a transmission to another. For this situation, we propose to allocate different maximum node powers according to the soil medium conditions. Simulation results prove that our proposed optimization achieves a significant EE‐SE tradeoff and prolongs the network’s lifetime compared to the fixed allocation node power scheme. Additional gain is obtained in case of dynamic medium conditions.

Retracted] Simulation Test of Wireless Underground Sensor Network in Stadiums

The underground sensor network is a kind of sensor network with sensor nodes buried in the soil. It is used in football fields, golf courses, and other stadiums and can effectively assist the stadium managers to maintain the turf condition. As the turf maintenance in the stadium is still in the manual state, the turf maintenance is time‐consuming and laborious. In order to improve this situation and adapt to future development needs, this paper proposes a wireless underground sensor network, designs the network architecture, and uses NS2 network simulation. The performance of the network was simulated and tested by the platform. This article first proposes a distance estimation method for sound and vibration signals based on the generalized correlation of the time difference of arrival based on the characteristics of the real signal when the event occurs. Then, for the range estimation obtained by applying this method, applying the idea of sparse signal reconstruction, a positioning algorithm based on the time difference of arrival based on the velocity function is proposed. Finally, using the above‐mentioned positioning algorithm, this paper obtains an overall fusion positioning strategy with the help of the idea of data fusion while taking into account the characteristics of the vibration source on the steel beam based on the positioning results of individual sound and vibration signals. The point of innovation lies in the development of positioning and tracking‐oriented platforms, including the development of wireless sensor network gateways and the development of sensor nodes. A network gateway based on network communication was developed to realize the connection with the Internet extranet. The results show that the wireless underground sensor network has strong usability in stadiums, and the network performance can meet the application requirements.

Signal Propagation Models in Soil Medium for the Study of Wireless Underground Sensor Networks: A Review of Current Trends

Radio signal propagation modeling plays an important role in the design of wireless communication systems. Various models have been developed, over the past few decades, to predict signal propagation and behavior for wireless communication systems in different operating environments. Recently, there has been an interest in the deployment of wireless sensors in soil. To fully exploit the capabilities of sensor networks deployed in soil requires an understanding of the propagation characteristics within this environment. This paper reviews the cutting‐edge developments of signal propagation in the subterranean environment. The most important modeling techniques for modeling include electromagnetic waves, propagation loss, magnetic induction, and acoustic wave. These are discussed vis‐a‐vis modeling complexity and key parameters of the environment including electric and magnetic properties of soil. An equation to model propagation in the soil is derived from the free space model. Results are presented to show propagation losses and at different frequencies and volumetric water content. The channel capacity and the operating frequency are also analyzed against soil moisture at different soil types and antenna sizes.

Experimental Link Quality Analysis for LoRa-Based Wireless Underground Sensor Networks

A variety of industrial applications are deployed in underground environments, such as soil condition assessment and pipeline monitoring (PM). Wireless underground sensor networks (WUSNs) are capable of continuously monitoring pipelines and promptly alerting any anomaly of entities. However, underground soils significantly influence the traditional WUSNs connectivity success. Long range (LoRa), being a leading low-power wide-area networks (LPWANs) technology, provides a new solution for underground industrial monitoring with its advantages in long-range capability and ultralow power consumption. Nevertheless, the LoRa-based link quality characteristics have not yet been quantitatively evaluated for WUSNs. In this article, the channel models of both the underground-to-aboveground (UG2AG) and aboveground-to-underground (AG2UG) communications are investigated. We experimentally analyze the impact of the propagation direction, burial depth and LoRa physical layer parameters on the in-situ LoRa propagation performance. The received signal strength indictor (RSSI), signal-to-noise ratio (SNR), and packet deliver ratio (PDR) are characterized for both communication channels in LoRa-based WUSNs. The semiempirical path-loss models are successfully verified by our field results, and we demonstrate that the communication range can be greater than 50 m at the burial depth of 0.4 m by adjusting the LoRa transmission/receiving settings. The combination of RSSI and SNR can be a better indicator of PDR than relying on either of them alone. Finally, the frame error rate (FER) is calculated to estimate the link performance with EM interferences. These results successfully demonstrate the advantages of LoRa for PM applications, which serve the first step toward the efficient protocol development of LoRa-based WUSNs.

Link Quality Analysis of Wireless Sensor Networks for Underground Infrastructure Monitoring: A Non-Backfilled Scenario

Wireless underground sensor networks (WUSNs) have been preliminarily applied in underground infrastructure monitoring (UIM) to alert entities about any anomaly in a timely manner. Some key repeaters are deployed along a typical borehole to ensure reliable connectivity with the aboveground gateways. However, the link quality characteristics of the bi-directional communications between the underground repeaters and aboveground devices have not been experimentally analyzed for UIM-WUSNs. To this end, a semi-empirical evaluation of underground-to-aboveground (UG2AG) and aboveground-to-underground (AG2UG) communications are presented in non-backfilled scenarios. In this paper, the effects of burial depth, internode distance, propagation direction, and backfilled condition on link quality are quantitatively investigated by real-life experiments. First, the non-backfilled UG2AG and AG2UG channel model is proposed and verified by the measured data. Then, the symmetry between the UG2AG and AG2UG links is demonstrated in the non-backfilled communication. Finally, the backfilled UG2AG/AG2UG communications show asymmetry behavior, which is largely due to the channel sensitivity to the soil properties. These findings can provide guidelines for the design and development of new communication protocols in UIM-WUSNs.

Reinforcement learning–enabled efficient data gathering in underground wireless sensor networks

Wireless underground sensor networks (WUSNs) consist of sensors that are buried in and communicate through soil medium, while the channel quality of WUSNs is greatly impacted by the underground environment, such as soil moisture and composition. Due to the precipitation and harsh weather, the underground environments change frequently, which make wireless communication in WUSNs much complicated than that in terrestrial over-the-air wireless sensor networks. To achieve reliable and energy-efficient data gathering in dynamic WUSNs, this article proposes an optimal transmission policy, where path loss of sensory data transmission, energy constraint, and network load balancing are the factors to be considered. Specifically, we capture the effect of underground environments on wireless communications, and evaluate path probability, energy consumption, and load balancing factor with respect to reliability and efficiency of transmission paths. The transmission topology can be reduced to a multi-objective and multi-constrained optimization problem and solved through an improved maximum flow minimum cost algorithm. By using reinforcement learning, we derive an adaptive transmission policy for underground sensors to efficiently use their energy and avoid transmitting sensory data in unreliable paths under a dynamic environment. Through simulations and comparison upon publicly available real data, our technique achieves more reliable wireless communication with significant reduction of packet loss, and enables more energy-efficient data gathering than other techniques, especially when soil moisture varies frequently.

Exploiting relay nodes for maximizing wireless underground sensor network lifetime

A major challenge in wireless underground sensor networks is the signal attenuation originated from multi-environment transmission between underground sensor nodes and the above-ground base station. To overcome this issue, an efficient approach is deploying a set of relay nodes aboveground, thereby reducing transmission loss by shortening transmitting distance. However, this introduces several new challenges, including load balancing and transmission loss minimization. This paper tackles the problem of deploying relay nodes to reduce transmission loss under a load balancing constraint by proposing two approximation algorithms. The first algorithm is inspired by Beam Search, combined with a new selection scheme based on Boltzmann distribution. The second algorithm aims to further improve the solutions obtained by the former by reducing the transmission loss. We observe that we can find an optimal assignment between sensor nodes and a set of the chosen relay in polynomial time by reformulating the part of the problem as a bipartite matching problem with minimum cost. Experimental results indicate that the proposed methods perform better than the other existing ones in most of our test instances while reducing the execution time.

Deployment of Underground Wireless Sensor Network Based on Magnetic Core Antennas and Multiple Surface Acoustic Wave Sensor Modules

For the first time, a 3less (batteryless, chipless, wireless) underground sensor system was developed for real time monitoring of variations in temperature, humidity, and hydrogen gas concentrations around underground utility burials. The completed sensor system consists of several magnetic core antennas, surface acoustic wave (SAW) sensors, and a measurement system. Each SAW sensor was activated by pure magnetic energy, and showed high sensor performances in sensitivity and linearity. A long readout distance was observed between the upper and underground antennas, and wireless magnetic communication was analyzed in terms of the interdistances, the angles between antennas, and the underground constituent mediums. A circulator was employed to discern magnetic signals emitting and receiving in between the upper and underground systems. A COMSOL simulation and coupling of mode (COM) modeling were also conducted to determine optimal design parameters for the sensor modules, and to predict the experimental results in advance.

Long range wide area network for agricultural wireless underground sensor networks

Wireless underground sensor networks (WUSNs) enable large-scale agricultural monitoring for improving farming efficiency and reducing pollution. A WUSN system based on the long range wide area network (LoRaWAN) standard is proposed. A novel LoRaWAN-based simulator is developed to model wireless signal attenuation and path loss in an underground environment by incorporating the Peplinski and modified Friis models. The simulator incorporates the full network stack of the LoRa physical and MAC layers. Simulation results show LoRaWAN-based WUSNs (with a node burial depth of 50 cm) can maintain network connectivity with a range of over several kilometres. The simulation results also show the regional duty cycle restriction significantly reduces network scalability due to acknowledgements from end-devices. For agricultural applications where such frequent acknowledgements are not required, the results show a LoRaWAN WUSN is scalable. A field experiment to evaluate the accuracy of the theoretical path loss model was conducted and results were found to agree with the simulations.

An Intelligent Guiding System for Trekkers using WUSN

To design and develop an automated surveillance system to detect and intimate the presence of animals, monitoring the health parameters of the trekkers and to detect fire in the dense forest. Using sensors and wireless technology that communicate to the base station using wireless communication. In this project the image processing technique is explored for the detection of animals so that any change in pattern then the trekkers and base station are alerted. For the communication process, a wireless underground sensor network is employed which has a lot of interlinked nodes. This is because internet usage is not effective in the dense and reserved forest area. Node to node communication is performed for efficient information sharing with the base station and the communication process for trekkers is carried on with wireless sensor networks thus provides warning information to the trekkers. Animal detection based applications have a very important role in many real-life situations and also detection of forest fire in dense forest is hard and fast-spreading. Therefore there must be automation and faster means of communication.

An Intelligent Guiding System for Trekkers using WUSN

To design and develop an automated surveillance system to detect and intimate the presence of animals, monitoring the health parameters of the trekkers and to detect fire in the dense forest. Using sensors and wireless technology that communicate to the base station using wireless communication. In this project the image processing technique is explored for the detection of animals so that any change in pattern then the trekkers and base station are alerted. For the communication process, a wireless underground sensor network is employed which has a lot of interlinked nodes. This is because internet usage is not effective in the dense and reserved forest area. Node to node communication is performed for efficient information sharing with the base station and the communication process for trekkers is carried on with wireless sensor networks thus provides warning information to the trekkers. Animal detection based applications have a very important role in many real-life situations and also detection of forest fire in dense forest is hard and fast-spreading. Therefore there must be automation and faster means of communication

A Statistical Impulse Response Model Based on Empirical Characterization of Wireless Underground Channels

Wireless underground sensor networks (WUSNs) are becoming ubiquitous in many areas. The design of robust systems requires an extensive understanding of the underground (UG) channel characteristics. In this article, the UG channel impulse response is modeled and validated via extensive experiments in indoor and field testbed settings. Three distinct types of soils are selected with sand contents ranging from 13% to 86%, and clay contents ranging from 3% to 32%. The impacts of changes in soil texture and soil moisture are investigated with more than 1, 200 measurements in a novel UG testbed at the University of Nebraska-Lincoln that allows flexibility in soil moisture control. Moreover, the time-domain characteristics of the channel, such as the RMS delay spread, coherence bandwidth, and multipath power gain, are analyzed. The power delay profile analysis validates the three main components of the UG channel: direct, reflected, and lateral waves. Furthermore, it is shown that the RMS delay spread follows a log-normal distribution. The coherence bandwidth ranges between 650 kHz and 1.15 MHz for soil paths of up to 1 m and decreases to 418 kHz for distances above 10 m. Soil moisture is shown to affect the RMS delay spread non-linearly, which provides opportunities for soil moisture-based dynamic adaptation techniques. A statistical channel model for the wireless underground channel has been developed based on the measurements and analysis. The statistical model shows good agreement with the measurement data. The model and analysis pave the way for tailored solutions for data harvesting, UG sub-carrier communication, and UG beamforming.

Wireless Underground Sensor Networks Path Loss Model for Precision Agriculture (WUSN-PLM)

Despite a large number of applications in the field of health care, military, ecology or agriculture, the Wireless Underground Sensor Network (WUSN) faces the problem of wireless Underground Communication (WUC) which largely attenuate the signal on the ground. For the case of precision agriculture, the motes are buried and they have to check the good growth of plants by verifying data like the water content. However, due to soil composition, the wave signal is attenuated as it travels across the ground. Thus, before a real deployment of WUSN, the prediction of the path loss due to signal attenuation underground is an important asset for the good network functioning. In this paper, we proposed a WUSN path loss for precision agriculture called WUSN-PLM. To achieve it, the proposed model is based on an accurate prediction of the Complex Dielectric Constant (CDC). WUSN-PLM allows evaluating the path loss according to the different types of communication (Underground-to-Underground, Underground to Aboveground and Aboveground to Underground). On each communication type, WUSN-PLM takes into account reflective and refractive wave attenuation according to the sensor node burial depth. To evaluate WUSN-PLM, intensive measurements on real sensor nodes with two different pairs of transceivers have been conducted on the botanic garden of the University Cheikh Anta Diop in Senegal. The results show that the proposed model outperforms the existing path loss models in different communication types. The results show that our proposed approach can be used on real cheap sensor with 87.13% precision and 85% balanced accuracy.

Theoretical and Experimental Studies on the Signal Propagation in Soil for Wireless Underground Sensor Networks.

Wireless Underground Sensor Networks (WUSNs), an important part of Internet of things (IoT), have many promising applications in various scenarios. Signal transmission in natural soil undergoes path loss due to absorption, radiation, reflection and scattering. The variability and dynamic of soil conditions and complexity of signal attenuation behavior make the accurate estimation of signal path loss challenging. Two existing propagation models for predicting path loss are reviewed and compared. Friis model does not consider the reflection loss and is only applicable in the far field region. The Fresnel model, only applicable in the near field region, has not considered the radiating loss and wavelength change loss. A new two stage model is proposed based on the field characteristics of antenna and considers four sources of path loss. The two stage model has a different coefficient m in the near field and far field regions. The far field distance of small size antenna is determined by three criteria: 2 D2/λ, 5 D, 1.6 λ in the proposed model. The proposed two stage model has a better agreement with the field experiment data compared to Friis and Fresnel models. The coefficient m is dependent on the soil types for the proposed model in near field region. It is observed from experiment data that the m value is in the range of 0~0.20 for sandy soils and 0.433~0.837 for clayey silt.

A Rescue-Assistance Navigation Method by Using the Underground Location of WSN after Disasters.

A challenging rescue task for the underground disaster is to guide survivors in getting away from the dangerous area quickly. To address the issue, an escape guidance path developing method is proposed based on anisotropic underground wireless sensor networks under the condition of sparse anchor nodes. Firstly, a hybrid channel model was constructed to reflect the relationship between distance and receiving signal strength, which incorporates the underground complex communication characteristics, including the analytical ray wave guide model, the Shadowing effect, the tunnel size, and the penetration effect of obstacles. Secondly, a trustable anchor node selection algorithm with node movement detection is proposed, which solves the problem of high-precision node location in anisotropic networks with sparse anchor nodes after the disaster. Consequently, according to the node location and the obstacles, the optimal guidance path is developed by using the modified minimum spanning tree algorithm. Finally, the simulations in the 3D scene are conducted to verify the performance of the proposed method on the localization accuracy, guidance path effectiveness, and scalability.