Wireless Sensor Network System Research Articles

Adaptive Random Spatial based Channel Estimation (ARSCE) for Millimeter Wave MIMO System

Millimeter-wave and mMIMO communications are the most essential success systems for next-generation wireless sensor networks to have enormous amounts of accessible throughput and spectrum. Through installing huge antenna arrays at the base station and performing coherent transceiver processing, mMIMO is a potential technology for enhancing the bandwidth efficiency of wireless sensor networks. The use of mmWave frequencies for mMIMO systems solves the problem of high path-loss through offering greater antenna gains. In this work, we provide a design with a random spatial sample structure that incorporates a totally random step before the analogue is received. It contains a totally random step before the analogue received signals are sent into the digital component of the HBF receiver. Adaptive random spatial based channel estimation (ARSCE) is proposed for channel session measurement collection, and an analogue combiner with valves has been used to estimate the signals at each receiving antenna. The proposed optimization problem formulation attempts to discover the orientations and gains of wideband channel routes. In addition, our proposed model has compared to various state-of-art techniques while considering error minimization.

An enhanced Grey Wolf Optimizer based Particle Swarm Optimizer for intrusion detection system in wireless sensor networks

An enhanced Grey Wolf Optimizer based Particle Swarm Optimizer for intrusion detection system in wireless sensor networks

An adaptive anti-jamming system in HyperLedger-based wireless sensor networks

An adaptive anti-jamming system in HyperLedger-based wireless sensor networks

Performance Analysis on Wireless Sensor Network Based on Zigbee Wireless Communication Protocol

This journal discusses the performance analysis of a Wireless Sensor Network (WSN) system based on the Zigbee Wireless Communication protocol. Zigbee in this system is used for sensor communications that do not require high data transmission speeds, such as sensor applications, such as temperature, humidity, light, pressure, and other sensors. The analysis carried out is to examine the QoS of a network system based on the topology used in the Zigbee protocol-based WSN system. The results of the study show that the use of topology is very influential on the availability, stable speed, and accuracy of the data transmitted between these sensors.

Sensor Mathematical Model Data Fusion Biobjective Optimization

Sensors are an important tool to quantify the changes and an important part of the information acquisition system; the performance and accuracy of sensors are more strictly desired. In this paper, a highly sensitive fiber optic sensor for measuring temperature and refractive index is prepared by using femtosecond laser micromachining technology and fiber fusion technology. The multimode fiber is first spliced together with single-mode fiber in a positive pair, and then, the multimode fiber is perforated using a femtosecond laser. The incorporation of data model sensors has led to a rapid increase in the development and application of sensors as well. Based on the design concept and technical approach of the wireless sensor network system, a general development plan of the indoor environmental monitoring system is proposed, including the system architecture and functional definition, wireless communication protocols, and design methods of node applications. The sensor has obvious advantages over traditional electrical sensors; the sensor is resistant to electromagnetic interference, electrical insulation, corrosion resistance, low loss, small size, high accuracy, and other advantages. The upper computer program of the indoor environment monitoring system was developed in a Visual Studio development environment using C# language to implement the monitoring, display, and alarm functions of the indoor environment monitoring system network. The sensor-data model interfusion with each other for mutual integration performs the demonstration of the application.

Enhanced Route Optimization for Wireless Networks Using Meta-Heuristic Engineering

Wireless Sensor Networks (WSN) are commonly used to observe and monitor precise environments. WSNs consist of a large number of inexpensive sensor nodes that have been separated and distributed in different environments. The base station received the amount of data collected by the numerous sensors. The current developments designate that the attentFgion in applications of WSNs has been increased and extended to a very large scale. The Trust-Based Adaptive Acknowledgement (TRAACK) Intrusion-Detection System for Wireless Sensor Networks (WSN) is described based on the number of active positive deliveries and The Kalman filter used in Modified Particle Swarm Optimization (MPSO) has been proposed to predict knot confidence. Simulations were run for non-malicious networks (0% malicious) and different percentages of malicious nodes were discussed. The findings suggest that the proposed method TRAACK Modified Particle Swarm Optimization (MPSO) packet delivery rate outperforms TRAACKPSO by 3.3% with 0% malicious nodes. Similarly, the packet delivery rate of TRAACKMPSO is 30% malicious, 3.5% better than TRAACKPSO in WSN.

Energy Efficient Hop-by-Hop Retransmission and Congestion Mitigation of an Optimum Routing and Clustering Protocol for WSNs

In the past few decades, wireless sensor networks, which take a growing number of applications in the surroundings further than the human reach, have risen in popularity. Various routing pseudo codes have been suggested for network optimization, emphasizing energy efficiency, network longevity, and clustering processes. To the existing load balancing energy-efficient sleep awake, aware smart sensor network routing protocol, the modified load-balancing efficient-energy sleep active alert smart routing system for wireless sensor networks is presented in this paper, which takes network homogeneity into account. The modified protocol is the optimum clustering and routing protocol in wireless sensor networks (OCRSN), which simulates an enhanced network coupled node pair model. Our suggested modified approach studies and enhances factors such as network stability, network lifetime, and cluster monitor mechanism choice. The significance of typically combining sensor endpoints is applied to maximize energy efficiency. The proposed protocol significantly improved network parameters in simulations, showing that it could be a valuable option for WSNs. In wireless sensor networks, in addition to memory considerations and dependable transportation, this paper presents a hop-by-hop re-transmission strategy and congestion mitigation, which is the major contribution of this paper. It is a very consistent method based on a pipe flow model. After performing additional optimized overhead to improve the network lifespan of wireless sensors networks, the current algorithm can be paralleled to the less energy adaptive clustering hierarchy protocol. The optimal clustering in multipath and multihop technique intends to minimize the energy consumption highlighted for a circular area enclosed by a sink by replacing one-hop communication with efficient multihop communication. The optimum quantity of clusters is determined, and the energy consumption is reduced by splitting the network into clusters of nearly equal size. The obtained simulation results will demonstrate the increase in the network lifetime compared to previous clustering strategies such as Low Energy Adaptive Clustering Hierarchy.

Detection and Avoidance of Clone Attack in IoT Based Smart Health Application

The deployment of wireless sensors in the hostile environment makes them susceptible to malicious attacks. One of the most harmful attacks is the clone attack in which a malicious node illegitimately claims the identity of a genuine node in the network and eventually tries to capture the entire network. This attack is also termed as node replication attack. The mobile nature of wireless sensor network (WSN) in smart health environment increases the vulnerability of node replication attack. Since the data involved in smart health system are highly sensitive data, preserving the system from the attack by malicious nodes is a crucial task. In this research, we proposed a new scheme called Routing Protocol for Energy Efficient Networks (RPEEN) for the detection of clone attack in IoT-based smart health application. The main advantage of this scheme is the increase in the energy efficiency as the energy efficiency is the most important constraint in WSN systems. The performance of the proposed scheme is highlighted using parameters like time delay, residual energy, throughput, energy efficiency and error rate. Further, to portray the efficacy of the proposed algorithm, this algorithm is compared with the existing Hybrid Multi-Level Clustering (HMLC) algorithm. It has been found that the proposed RPEEN scheme achieves a time delay of 0.63 and 0.6 ms with 0 dead nodes and by avoiding clone attack respectively. Furthermore, the proposed scheme attains the highest residual energy of 49.5 J for the 2500 rounds. In addition, the proposed algorithm attains the highest throughput of 99.2% for the 50 nodes.

Energy Efficient Node Deployment Technique for Heterogeneous Wireless Sensor Network based Object Detection

Lifetime of the network and the quality of operation are the two important issues in a wireless sensor network system meant for object detection and tracking application. At the same time, there should be a tradeoff between network cost and the quality of operation as high cost of the network limits its real-time usability. Heterogeneous wireless sensor networks promises the prolonged network lifetime as well as enhances network reliability as they contain a mixture of nodes with different characteristics. Further prolongation of network lifetime can be achieved by managing the available node energy in a proper way, i.e, by minimizing number of communication, minimizing node density, minimizing overhead information generated during operation etc. Proper node deployment scheme not only helps to enhance the lifetime of the network but also helps in reducing deployment cost while maintaining the quality of operation in terms of object detection accuracy. This paper focuses on the energy efficient node deployment in heterogeneous wireless sensor network system with the features of maximum network coverage, optimum node density and optimum network cost. This paper proposes a novel energy efficient node deployment algorithm that determines the number of static and mobile nodes required for deployment and then relocates the mobile nodes to cover up the coverage hole using 8-neighbourhood and Particle Swarm Optimization (PSO) algorithm. The performance of the proposed algorithm is compared with corresponding model of Harmony Search Algorithm (HSA) and PSO based node deployment and it is seen that the proposed model outperforms better in comparison to them.

Data Reliability and Sensors Lifetime in Bridge Health Monitoring using LoRaWAN-Zigbee

The Wireless Sensor Network (WSN) is regarded as the fastest expanding technological trend in recent years due its application in a variety of sectors. In the monitoring region, several sensor nodes with various sensing capabilities are installed to gather appropriate data and communicate it to the gateway. The proposed system of the heterogeneous WSN employing LoRaWAN-Zigbee based hybrid communication is explored in this research study. To communicate in a network, two Long–Range Wide Area Network (LoRaWAN) sensor clusters and two Zigbee sensor clusters are employed, together with two Zigbee and LoRaWAN converters. The suggested Golden eagle shepherd optimization (GESO) method then forms Zigbee as well as LoRaWAN networking clusters. Furthermore, depending on energy usage and data packet size, the fitness of each sensor node is assessed using the Dynamic Intelligent Reasoning Based Neural (DIRN) approach. MATLAB software is used to implement and execute this study. When the Zigbee network’s transmission distance is 650 m and the LoRaWAN network’s transmission range is 3.5 km, the system can function with a packet loss rate of less than 0.04 percent. This study shows significant gains in the performance of the system when compared to traditional approaches based on digital findings obtained on software solutions.

Modeling of Leopard optimization based Node Localization Technique for Wireless Communication Networks

Wireless communication inculcates transfer of information not having any physical connection among two or more points. The significant operation of a sensor network becomes collecting and forwarding data to destiny. It is highly crucial to have an awareness regarding the place of collected data. This data is acquired by leveraging localization method in wireless sensor networks (WSNs). Localization is a way of determining the sensor nodes (SNs) location. Localization of SNs turns out to be an exciting research area, and several studies were performed till now. It is very favourable to model scalable, effectual, and low-cost localization systems for WSNs. This study develops a Leopard optimization based Node Localization Technique for Wireless Communication (LONLT-WC). The goal of the LONLT-WC model is to recognize the location of the nodes involved in the network. The LONLT-WC model involves the design of snow leopard optimization (SLO) algorithm, inspired from the characteristics of snow leopards. The presented LONLT-WC approach computes the unidentified location of the nodes utilizing anchor nodes in the network with the accomplishment of least error rate. The experimental analysis of the LONLT-WC model involves a series of simulations and the results highlighted the betterment of the presented technique.

IoT networks for monitoring and detection of leakage in pipelines

Pipelines have been an important means of oil transport in recent years, especially in Saudi Arabia. Since oil pipelines have extensive length, tracking them is a critical task. Therefore, monitoring pipeline leaks has become a significant field of intelligent sensing systems. There are many challenges when monitoring long-distance pipelines, requiring energy efficiency. Wireless sensor networks (WSNs) deployed in oil pipelines provides solutions to address these challenges, but various issues must be considered, such as costs, scalability, and delay issues for monitoring systems. The recent advances in internet of things (IoTs) and the new LPWAN capabilities have promising benefits over monitoring systems. This paper investigates WSN systems in oil pipelines with IoT technologies. Also, it presents a LoRa as an LPWAN single-hop model for monitoring aboveground oil pipelines. The LoRa model is evaluated by using two scenarios and analysing the scalability and capacity of the LoRa and discussing the result.

A Sustainable WSN System with Heuristic Schemes in IIoT

Recently, the development of Industrial Internet of Things has taken the advantage of 5G network to be more powerful and more intelligent. However, the upgrading of 5G network will cause a variety of issues increase, one of them is the increased cost of coverage. In this paper, we propose a sustainable wireless sensor networks system, which avoids the problems brought by 5G network system to some extent. In this system, deploying relays and selecting routing are for the sake of communication and charging. The main aim is to minimize the total energy-cost of communication under the precondition, where each terminal with low-power should be charged by at least one relay. Furthermore, from the perspective of graph theory, we extract a combinatorial optimization problem from this system. After that, as to four different cases, there are corresponding different versions of the problem. We give the proofs of computational complexity for these problems, and two heuristic algorithms for one of them are proposed. Finally, the extensive experiments compare and demonstrate the performances of these two algorithms.

Wireless Sensor Network System for Precision Irrigation using Soil and Plant Based Near-Real Time Monitoring Sensors

Real-time monitoring for precision irrigation using wireless technologies is crucial to combat surplus irrigation and reduce the climate change effect on water use efficiency. Variations in sap-flow and volumetric water contents (VWC) were investigated on date palm trees of Al Naghal (Phoenix dactylifera L.) in water scare countries using traditional flood and modern drip irrigation systems. Daily SF rates and VWC were tracked in connection to weather conditions. The results showed that the meteorological parameters that affected SF rates were noted with order temperature (T) > net solar-radiations (Rn) > vapor-pressure-deficit (VPD) > wind-speed for two consecutive years, 2015 and 2016 (U). Daytime fluctuations in Rn and temperature resulted in the highest SF rates between 12:00 and 14:00, decreasing relative trends between 18:00 and 23:00, and high volumetric water contents. SF rates were used to determine the plant's water condition and environmental challenges. Under highly drought conditions, the variety (Al-Naghal) demonstrated its aptitude, stability, and consistency. The actual water use efficiency explored with 80.6% and 71.4% at aflaj and modern irrigation systems, respectively, was determined by soil and plant-based monitoring, yielding accurate quantities of 17.5 and 12 liters/day at aflaj and modern irrigation systems, respectively. It has exposed the actual plant transpiration, and irrigation water requirement used to inaugurate precision irrigation systems in the arid regions.

Arduino based wireless sensor network systems for agriculture

Arduino based wireless sensor network systems for agriculture

Street Level Flood Monitoring and Warning System, a conceptual model using IoT: A Case of Surat City

Most of the natural disasters are unpredictable, but the most frequent occurring catastrophic event over the globe is flood. Developing countries are severely affected by the floods because of the high frequencies of floods. The developing countries do not have good forecasting system compared to the developed country. The metro cities are also settled near the coast or river bank which are the most vulnerable places to floods. This study proposes plan for street level flood monitoring and warning system for the Surat city, India. Waterlogging happens in the low lying area of the Surat city due to heavy storm and heavy releases from the Ukai dam. The high releases from upstream Ukai dam and heavy rainfall resulted into flooding in the low lying area of the Surat city. This research proposed a wireless water level sensor network system for the street water level flood monitoring. The system is proposed to monitor the water levels of different areas of city through the wireless water level sensors as well as to capture live photos using CCTV camera. This will help authority not only to issue flood warning but also to plan flood mitigation measures and evacuation of people.

Real-time condition assessment of a painted megalithic cave using Wireless Sensor Network

The deterioration of underground heritage caves caused by visitations has attracted extensive attention over the recent decades. Most previous research focused on investigating the impact of visitors on the microclimatic conditions of the interior of large show caves, but much less relevant effort was made for small confined caves, for example, megalithic burial dolmen caves. In addition to environmental condition issues, the structural performance of underground heritage caves also deteriorates in the long-term subject to both natural hazards (e.g. creep in geo-materials and extreme weather) and manmade ones (e.g. construction activities). To this end, a real-time Wireless Sensor Network (WSN) system is deployed inside an underground megalithic dolmen to monitor its structural performance with time so as to assess its long-term structural stability. Meanwhile, the WSN system together with other field sensors and inspection monitors the interior environmental change caused by human visitation effect, aiming to reveal the mechanism behind visitor-caused rock painting deterioration in the small confined dolmen chamber. Results show that structurally, the dolmen can be regarded as generally stable despite a progressive development of structural performance during the first 1.5 months and accidental instability of the near-opening pillar A. In terms of environmental condition, the presence of visitors leads to significant changes of interior microclimatic conditions frequently inside the confined cave against consistent rock painting conservation. Particularly, the cave paintings may deteriorate critically with time as visitation induces a ‘hotbed’ environment for interactions between microorganisms and microstructures of the rock paintings due to the variations of interior microclimate. To ensure long-term structural stability and restore acceptable level of interior microclimate, tinted hydraulic lime and steel rod/brace were recommended for enhancing structural robustness and a mechanical ventilation system for improving environmental resilience of the dolmen. A generalized monitoring approach was proposed for the reference of other similar caves.

Integration of Wireless Sensor Network and IoT for Smart Environment Monitoring System

Air contamination, water waste, and radioactive contamination are significant environmental issues. Adequate supervision is needed to ensure economic sustainability through the preservation of a good society. Environmental tracking has become a Smart environment monitoring (SEM) system in recent times, with developments in the Internet of Things and the creation of advanced detectors. This situation evaluates substantial achievements and scientific studies on SEM, including air quality control, water management, radiation emissions, and agricultural practices. A Wireless sensor network and IoT integrated system for Smart environment monitoring (WSN-IoT-SEC) framework are proposed in this research. The analysis will be divided employing SEM techniques applications, and each aim will then be further studied in terms of the detectors, machine learning models, and classifiers operated. A systematic study was carried out based on the study’s evaluated results and patterns, indicating important suggestions and the SEM analysis’s influence. The researchers have discussed objectively how the advancements in mobile technologies, IoT, and wireless sensor networks allow the control of the atmosphere an intelligent monitoring device. Eventually, the concept of rigorous machine learning techniques has been proposed, denouncing techniques and developing appropriate WSN specifications.

An intrusion detection system for wireless sensor networks using deep neural network

An intrusion detection system for wireless sensor networks using deep neural network

Narrowband and wideband EMW path loss in underwater wireless sensor network

PurposeUtilization of electromagnetic wave (EMW) sensors in an underwater environment has the potential to increase the data rate compared to acoustic-based sensors because of the ability to use larger signal bandwidth. Nevertheless, EMW signals has the drawback of large signal attenuation in underwater, attributed to the high relative permittivity and conductivity of water compared to the atmosphere, hence employment of wide signal bandwidth is necessary to balance the data rate-attenuation trade-off. The purpose of this paper is to analyze the characteristics of both narrowband and wideband EMW signal propagation underwater and devise a path loss model for both cases.Design/methodology/approachPath loss measurement was conducted using a point-to-point configuration in a laboratory water tank while transmitting narrowband and wideband signals between a pair of wideband underwater antennas. The wideband underwater antennas use buffer-layer structures as the impedance matching layer to optimize the antenna performance when operating underwater. The path loss for narrowband signal was modeled using a multi-layer propagation equation in lossy medium considering losses at the medium boundaries. For the case of the wideband signal, a modified version of the model introducing power integration over bandwidth is adopted. These models were formulated through numerical simulations and verified by measurements.FindingsThe measured narrowband path loss marked an 80 dB attenuation using 800 MHz at 2 m distance. The proposed narrowband model agrees well with the measurements, with approximately 3 dB modeling error. Utilization of the proposed wideband path loss model resulted in a reduction of the gradient of the path loss curve compared to the case of the narrowband signal. The measured wideband path loss at 2 m distance underwater was approximately −65 dB, which has been shown to enable a working signal-to-noise ratio of 15 dB. This proves the potential of realizing high data rate transmission using the wideband signal.Originality/valueThe paper proposed a wideband propagation model for an underwater EMW sensor network, using power integration over bandwidth. The effectiveness of using wideband EMW signals in reducing path loss is highlighted, which is seldom discussed in the literature. This result will be of useful reference for using wideband signals in designing a high data rate transmission system in underwater wireless sensor networks, for example, in link budget, performance estimation and parameter design of suitable transmission scheme.