Wireless Sensor Network Technology Research Articles

Recent Developments in Wireless Soil Moisture Sensing to Support Scientific Research and Agricultural Management

In recent years, wireless sensor network (WSN) technology has emerged as an important technique for wireless sensing of soil moisture from the field to the catchment scale. This review paper presents the current status of wireless sensor network (WSN) technology for distributed, near real-time sensing of soil moisture to investigate seasonal and event dynamics of soil moisture patterns. It is also discussed how WSN measurements of soil measurements contribute to the validation and downscaling of satellite data and non-invasive geophysical instruments as well as the validation of distributed hydrological models. Finally, future perspectives for WSN measurements of soil moisture are highlighted, which includes the improved integration of real-time WSN measurements with other information sources using the latest wireless communication techniques and cyberinfrastructures.

Data transmission reduction using prediction and aggregation techniques in IoT-based wireless sensor networks

Currently, broad ranges of economic sectors exploit the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) technology generating problems to be managing, processing and organizing the big data streams. Given the inherent sensor constraints (battery-dependent life, lack of memory space, limited processor power), there is a need for systems capable of reducing data transmission flux of the distributed IoT-based WSNs applications to mitigate the continuously increasing network traffic. Prediction and data aggregation techniques are promising solutions to meet this requirement. These techniques are particularly powerful solutions in forecasting processes where a huge data to be collected, transmitted and recorded. This is right even if we consider the integration of IoT-based WSNs with cloud computing technology. This paper proposes the combination of the recently developed prediction scheme EADPS (Extended Adaptive Dual Prediction Scheme) and the temporal correlation based data aggregation technique as a power tool to address the problem of communication reduction in connected IoT-based WSNs. First, we studied separately the impact of each technique before considering their combination. To achieve this goal, we consider the multi-hop ring model of the IoT-based WSNs. The results show that the aggregation technique is powerful compared to the DPS prediction scheme but loses its superiority for small WSNs size (with lesser than five rings) when the EADPS schema is applied. In addition, the data correlation has a feeble impact on reduction of transmission rates. According to the imposed tolerance thresholds, we show that the proposed scheme reduced the average transmission rates in the range 85%–96% for the entire network. The obtained results are presented and discussed.

Monitoring, Detecting and Early Warning of Forest Fires using Blockchain in Wireless Sensor Network

Forest fires cause economic and material losses and destroy the environment, causing many negative impacts on human habitats and forest ecosystems. The unpredictable threat of wildfires leads to climate change and the greenhouse effect. It is worth noting that up to 90% of forest fires occur mainly due to human activities [1], even due to tampering, vandalism, and hostile actions. Therefore, to minimize the destruction caused by forest fires as well as accurately identify the area where forest fires occur and support government agencies, forest rangers, and search and disaster relief forces, ... it is necessary to monitor, detect and warn of forest fires right from the early stage (early warning). This paper proposes to use static sensor nodes combined with mobile in wireless sensor network (WSN) to Forest fire Monitoring, Detection, and Early Warning - FMDW. At the same time, integrating Blockchain technology (BC) in WSN solves the problem of secure routing, and distributed data storage, and prevents destructive and tampering attacks. This also suggests new research directions on monitoring, detecting, warning, and protecting forests in countries using Blockchain security technology in WSN.

Available Wireless Sensor Network and Internet of Things testbed facilities: dataset

The availability of data is an important aspect of any research as it determines the likelihood of the study's commencement, completion, and success. The Internet of Things and Wireless Sensor Networks technologies have been attracting a huge amount of researchers for more than two decades, without having a consolidated or unified source, identifying and describing available Internet of Things and Wireless sensor network testbed facilities. In this paper, a dataset including 41 distinct testbed facilities is described. These testbed facilities are classified according to their key features such as Device Under Test (DUT) type, mobility, access level, facility count, connection/interaction interfaces along with other criteria. The systematic review process resulting in the gathered data set consisted of three filtering phases applied to relevant articles published between the years 2011 and 2021 as obtained from the Web of Science and SCOPUS databases.

Advanced energy efficient pegasis based routing protocol for IoT applications

The Scientific betterments in Wireless Sensor Networks (WSNs) technology have paved the way for the advancement of lower sized, reduced-cost, and highly-powered sensor nodes. The sensor nodes are consistently expected to work with limited power batteries, and their energy is the most precious asset in a WSN, proper usage of the total energy to perpetuate the Network's lifetime is the primary constraint and objective of the majority of the research works. As energy conservation and prolonging of network-lifetime have become a critical issue, a novel protocol for WSN based on an Advanced Fixed Path and Mobile Base Station energy-efficient PEGASIS based routing protocol is proposed in this research work. The proposed method focuses on the base station's specified mobility with a multiple-chain model to attain small size chains and reduce the single leader node load that directly affect the Network's energy conservation and lifetime. The experimental results based on average energy, residual energy, consumed energy, dead nodes, and alive nodes reflect the proposed method's efficiency to fulfill the above-said objectives. The proposed method is also compared with three current routing protocols, i.e., Energy Efficient Routing Algorithm with Mobile Sink Support for WSNs (EERCCSM), Cluster-Chain Mobile Agent Routing (CCMAR), and Energy-efficient Cluster-based Dynamic Routing Algorithm (ECDRA). This novelty and advancement of the base station will open new horizons for getting it placed much closer to the cluster leader to prolong Network's lifetime to a great extent in the future.

DV-Hop-based localization algorithm using optimum anchor nodes subsets for wireless sensor network

Node localization has become a crucial technology in wireless sensor network (WSN) research field. Although the widely used DV-Hop localization algorithm is simple and easy to implement, its positioning accuracy still needs to be further enhanced. To improve the DV-Hop algorithm accuracy, a DV-Hop-based scheme using optimum anchor nodes subsets (OANS DV-Hop) is put forward in this article. For OANS DV-Hop algorithm, first of all, each anchor node localizes itself by using other anchor nodes, and employs binary particle swarm optimization (BPSO) algorithm to generate an optimum subset composed of other anchor nodes except itself. Then the anchor node applies OANS to recalculate its average hop size and broadcasts the new hop size and OANS to the nearest unknown nodes. The unknown node localizes itself by using OANS instead of all anchor nodes. Finally, a fitness function is designed based on OANS, and the continuous particle swarm optimization (PSO) algorithm is applied to further increase the localization accuracy. Simulation results demonstrate that OANS DV-Hop algorithm owns higher localization accuracy compared with the primal DV-Hop and other improved DV-Hop algorithms in various network environments.

A software development for medical with a multiple decision taking functionalities

BackgroundSmart devices including sensors and smartphones have grown exponentially during the past few years due to rapid growth in wireless sensor network (WSN) technology under IoT. In addition with smart city, concepts of smart traffic systems and smart health are also being developed. It enables remote connectivity of smart devices (i.e., mobiles, sensors) and medical smart software with the internet for monitoring. The availability of smart devices plays a remarkable role in the new era of mobile health (mHealth) monitoring. mHealth software is mostly used for humans who suffer from any chronic disease and need remote monitoring. In this case, such human needs smart medical software for careful monitoring from a distance due to their continuous movement and distance from any medical support. Existing LimitationsNowadays, due to the frequent use and development of intelligent software for medical still, this domain has several limitations such as (i) not rescuing timely, (ii) no mechanism to assure that medical condition is abnormal or due to any other reason i.e. environmental effects, (iii) not a decision taking medical software for selection of multiple ontologies simultaneously, (iv) no acknowledgment process for enlisting the medical centers which can provide the medical facilities and (v) issues with assessing the environmental factors. These limitations make smart medical field less effective particularly for users who have severe situations. Proposed SolutionTherefore, this work has proposed a framework and developed medical software for humans. For the development of the software, we used the hardware including Arduino UNO board, for pulse values used a pulse sensor and for its connectivity with the mobile software used a Bluetooth module HC-05 module. Arduino and Android based software are linked via a Bluetooth module. ImplementationFor testing the software, case studies are used with different scenarios. This study has revealed more valuable results in respect of human rescue and ensuring the severe condition of the human with current activities, examining the effects of the environmental factors on the health, preventing the system from false alert generation, and timely receiving of medical facilities. ConclusionThe developed software as per the suggested framework's features has overcome the mentioned challenges from remote monitoring. It potentially outperformed with easiness and in a better way towards smart health monitoring services.

Construction of Landscape Ecological Planning Evaluation Model Based on Sensor Network

The application of wireless sensor network (WSN) technology promotes the modernization of forestry. WSN application technology in forest areas is an important research topic for the sustainable development of forestry in China and is also a research hotspot for forestry ecological monitoring at present. The application of wireless sensor networks in forest areas, first of all, solves the problem of limited energy supply and low-latency data transmission in the forest environment. Due to the large area of the forest environment and uneven tree density, dynamic changes in forest height, easy to block the signal, and other characteristics, the forest environment is prone to node energy depletion fast, the network life cycle is short, and data transmission delays large dilemma. Second, the application of wireless sensor networks is usually centered on maximum data acquisition, but the contradiction between high data acquisition rate and limited energy supply is inevitable, so it is necessary to construct a maximum data acquisition rate model with limited energy supply as a constraint to guarantee the optimal acquisition conditions for wireless sensor networks. In this paper, from the application of wireless sensor network technology in forest environment, the research on the application of wireless sensor network in forestry is carried out around the analysis of energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision-making fire danger warning process, so as to provide a solution to the overall problem of forest fire warning based on rechargeable wireless sensor network. In this paper, we analyze the dynamic replenishment of energy in rechargeable wireless sensor networks and propose an energy-based transmission control protocol that effectively improves data transmission efficiency. In the rechargeable wireless sensor network, the network E2E (end-to-end) average delay time is calculated based on the number of nodes on the data transmission link. The research idea of this paper starts from the application technology of wireless sensor network in the forest environment, and the design of the energy self-collection permanent function of sensor nodes, sensor node transmission routing strategy, data collection, fusion, and fuzzy inference decision fire danger warning process are realized vertically.

Vibration State Monitoring of Mechanical Equipment Based on Wireless Sensor Network Technology

Vibration State Monitoring of Mechanical Equipment Based on Wireless Sensor Network Technology

Internet of Things Based Korean Cross-Cultural Communication Interactive Talent Training Model under Curriculum, Ideology, and Politics

With the development of society, the exchanges between various countries have become increasingly close, and this open communication mode also affects and changes the communication culture of each country. In the context of globalization, cross-cultural communication is increasing day by day, and cross-cultural communication ability has become a necessary quality for modern talents, so it is imperative to cultivate cross-cultural communication talents. However, the development level of informatization is insufficient, especially since the development of Internet of Things technology is lagging behind, the application level is low, and there are fracture characteristics in the application of each link. Information exchange cannot be effectively realized, information is incomplete, and asymmetry is obvious, and there is no effective information exchange platform. Following the trend of internationalization, scholars are paying more and more attention to the combination of cross-cultural communication and IoT technology. The combination of the two is to realize the real-time monitoring of personnel training. The acquisition and transmission of personnel training information is the primary problem to be solved in the realization of Korean cross-cultural communication. The wireless sensor network (WSN) has the characteristics of wide distribution of nodes, strong self-organization ability of routing, and good adaptability to dynamic changes in topology structure. WSN is used to solve this problem and is a good choice. Therefore, this paper used random forest algorithm and GBDT algorithm to apply WSN technology to the process of interactive talent training and established a network information service (NIS) system for interactive talent training. The experimental results have shown that the random forest algorithm and the GBDT algorithm can further simplify the input feature quantity and both can achieve good prediction results, while the GBDT model of the two models has relatively better prediction performance. The models obtained by the two methods meet the needs of detection parameter optimization, which realizes the real-time development of interactive talent training and realizes the intelligence and high efficiency of interactive talent training.

Research Trends on Greenhouse Engineering Using a Science Mapping Approach

Horticultural protected cultivation has spread throughout the world as it has proven to be extremely effective. In recent years, the greenhouse engineering research field has become one of the main research topics within greenhouse farming. The main objectives of the current study were to identify the major research topics and their trends during the last four decades by analyzing the co-occurrence network of keywords associated with greenhouse engineering publications. A total of 3804 pertinent documents published, in 1981–2021, were analyzed and discussed. China, the United States, Spain, Italy and the Netherlands have been the most active countries with more than 36% of the relevant literature. The keyword cluster analysis suggested the presence of five principal research topics: energy management and storage; monitoring and control of greenhouse climate parameters; automation of greenhouse operations through the internet of things (IoT) and wireless sensor network (WSN) applications; greenhouse covering materials and microclimate optimization in relation to plant growth; structural and functional design for improving greenhouse stability, ventilation and microclimate. Recent research trends are focused on real-time monitoring and automatic control systems based on the IoT and WSN technologies, multi-objective optimization approaches for greenhouse climate control, efficient artificial lighting and sustainable greenhouse crop cultivation using renewable energy.

Performance Evaluation of Badminton Trajectory Error Based on Wireless Sensor Network

The successful holding of the Olympic Games has made the attention to sports continue to rise. China’s badminton has always been at the forefront of the world, and since badminton became an Olympic sport, it has been tasked with winning gold medals. Because the entry of badminton is simple, badminton has a solid mass foundation in China. Badminton has a very high fitness, confrontation, and fun, with speed as the core and stability, accuracy, ruthlessness, and liveliness as the main tactical style. In professional competitions, athlete’s prediction of badminton’s trajectory is of great significance to the performance of the game, so the prediction of badminton’s trajectory is very important. This paper aims to study the performance evaluation of badminton trajectory error analysis based on wireless sensor network. It is expected to predict the trajectory of badminton with the help of wireless sensor network technology, reduce the prediction error, and improve the game performance. Sensors in WSN communicate wirelessly, so network settings are flexible, device locations can be changed at any time, and wired or wireless connections to the Internet are possible. This paper analyzes and compares the commonly used dynamic target capture algorithms, compares the advantages and disadvantages of this wireless sensor network, combines the flight characteristics of badminton, and analyzes the error of its trajectory. Aiming at the vision system in badminton monitoring, the application research on the side detection, tracking, and trajectory prediction algorithm of flying badminton in the two-dimensional image plane video stream is completed. The experimental results of this paper show that the error of using the wireless sensor network is 2 cm and the trajectory error of not using the wireless sensor network is 8 cm. It can be seen that the trajectory extraction error using the wireless sensor network strategy is small.

An Effective Frequency Drift and Phase Offset Estimation Based on Two-Way Message Exchange for WSNs Time Synchronization

Time synchronization is one of the key technologies of wireless sensor networks. At present, most studies assume that the transmission delay is a fixed value, and there is no effective processing of historical clock data. Therefore, this paper proposes a clock frequency drift and phase offset estimation scheme which is considering variable transmission delay and historical clock data. This paper has clarified the effectiveness of the Gaussian delay model in the calculation of time synchronization error. On this basis, this paper calculated the maximum likelihood estimations of frequency drift and phase offset and the corresponding Cramer-Rao lower bound. Meanwhile, the transmission delay is optimized by comparing the chi-square distance between measured and standard data. Also, this paper conducts autonomous training on historical data to provide services for improving the accuracy of fitting estimation. Simulation results validate the performance of the proposed scheme.

Integration of Wireless Sensor Networks in Environmental Monitoring Cyber Infrastructure

Abstract: Wireless sensor networks (WSNs) have great potential to revolutionize many science and engineering domains. We present a novel environmental monitoring system with a focus on overall system architecture for seamless integration of wired and wireless sensors for long-term, remote, and near-real-time monitoring. We also present a unified framework for sensor data collection, management, visualization, dissemination, and exchange, conforming to the new Sensor Web Enablement standard. Some initial field testing results are also presented. The monitoring system is being integrated into the Texas Environmental Observatory infrastructure for long-term operation. As part of the integrated system, a new WSN-based soil moisture monitoring system is developed and deployed to support hydrologic monitoring and modeling research. This work represents a significant contribution to the empirical study of the emerging WSN technology. We address many practical issues in real-world application scenarios that are often neglected in the existing WSN research

Optimization of Intelligent Display Mode of Museum Cultural Relics Based on Intelligent Wireless Sensor Network

The traditional way of museum exhibition is physical exhibition, which is essentially restricted by the venue, time, space, and display conditions and is no longer applicable to the display form of modern museum exhibits. Therefore, with the development of a large number of modern technologies such as information technology, wireless sensor technology and image processing technology, the way of museum cultural relics display also tends to be more intelligent and intelligent. Based on this, this paper will set up corresponding gateway nodes, routing nodes, and corresponding terminal nodes for each node of the corresponding museum based on the intelligent wireless sensor network technology; transmit the audio impact information of the corresponding museum exhibits through the terminal nodes; and automatically send the node short address information of the corresponding information to the corresponding analysis end in real time for analysis and processing, and then based on the information characteristics of the corresponding exhibits, at the same time, combined with virtual fusion and human-computer interaction technology, a set of augmented reality application system for tourist mobile terminal is developed. Abandoning the disadvantages of traditional museum display methods, this paper creatively designs the corresponding museum heritage intelligent display workflow based on intelligent wireless sensor network through C/S architecture and finally realizes the enhancement effect of virtual reality on tourism terminals. In order to verify the superiority of the intelligent display mode of museum cultural relics based on intelligent wireless sensor network proposed in this paper, this paper compares it with the traditional display mode. The experimental results show that this paper has obvious advantages in the display comprehensiveness, visitor satisfaction, and display effectiveness, which further improves the effect of museum cultural relics display.

Key Technologies of Real-Time Location Service in Satellite Navigation and Positioning Network Based on Internet of Things.

In this day and age, the necessities for route and situating exactness are getting ever more elevated. The global positioning and navigation system (GPS) can give high-accuracy and long haul route and situating data. But it largely depends on the external environment and is susceptible to environmental disturbances. As a result, the number of visible stars is insufficient, and even placement fails. The research on node positioning technology is of great significance to the research of wireless sensor networks, and node positioning technology is one of the important technologies in wireless sensor networks. Therefore, this paper will introduce the relevant algorithms and technologies of positioning in detail. The purpose of this text is to research how to analyze and research based on Internet of things (IoT) satellite navigation and positioning technology. And the wireless sensor network is described. The two simulation results have showed that, with the positioning technology proposed in this paper, the average positioning error of the anchor node can be kept a small constant regardless of the conditions of different packet sending intervals, changing moving rates, or increasing the transmission power and changing distance. The average positioning error provided in this paper has been kept at about 0.80 m, and the positioning accuracy is high, which is naturally newer and better than the Ssu positioning technology.

Empirical Analysis of Extended QX-MAC for IOT-Based WSNS

The Internet of Things (IoT) connects our world in more ways than we imagine. Wireless sensor network (WSN) technology is at the core of implementing IoT architectures. Although WSN applications give us enormous opportunities, their deployment is challenging because of the energy constraint in sensor nodes. The primary design objective of WSNs is therefore to maximize energy efficiency. Enhancing network quality of service (QoS), such as latency, is another crucial factor, particularly for different delay-sensitive applications. Medium access control (MAC) protocols are of paramount importance to achieve these targets. Over the years, several duty-cycled MAC protocols were proposed. Among them, the strobed preamble approach introduced in X-MAC has gained much interest in IoT field because of its several theoretical advantages. However, X-MAC is highly efficient only under light traffic. Under heavy traffic, X-MAC incurs high per-packet overhead and extra delay. In addition, X-MAC has several design flaws that can significantly degrade network performance. In this paper, we point out some specific malfunctions in the original X-MAC design and propose alternatives to reduce their impact. We present an energy-efficient, traffic-adaptive MAC protocol called QX-MAC that addresses the foreseen shortcomings in X-MAC. QX-MAC integrates Q-learning and the more bit scheme to enable the nodes to adapt the active period and duty cycle in accordance with incoming traffic. Finally, the performance of QX-MAC is thoroughly analyzed compared with other reference protocols to validate its efficacy. Our QX-MAC simulation results demonstrate substantial improvements in overall network performance in terms of energy consumption, packet loss, delay, or throughput.

Applications of wireless sensor networks to improve occupational safety and health in underground mines

Introduction: The very complex and hazardous environment of underground mines may significantly contribute to occupational fatalities and injuries. Deploying wireless sensor network (WSN) technology has the potential to improve safety and health monitoring of miners and operators. However, the application of WSN in the industry is not fully understood and current research themes in this area are fragmented. Thus, there is a need for a comprehensive review that directly explores the contribution of WSNs to occupational safety and health (OSH) in underground mines. Method: This study aims to conduct a systematic literature review on the existing applications of WSNs for improving OSH in the underground mining industry to pinpoint innovative research themes and their main achievements, reveal gaps and shortcomings in the literature, recommend avenues for future scholarly works, and propose potential safety interventions. The major contribution of this review is to provide researchers and practitioners with a holistic understanding of the integration of WSN applications into underground mine safety and health management. Results: The review results have been categorized and discussed under three predominant categories including location monitoring and tracking, physiological and body kinematics monitoring, and environmental monitoring. Finally, seven major directions for future research and practical interventions have been identified based on the existing research gaps including: (1) further applications of WSNs for underground mining OSH management; (2) application of WSNs from research to real-world practice; (3) big data analytics and management; (4) deploying multiple WSNs-based monitoring systems; (5) integration of WSNs with other communication systems; (6) adapting WSNs to the Internet of Things (IoT) infrastructure; and (7) autonomous WSNs.

Programmable timer triggered energy harvesting wireless sensor-node using long range radio access technology

<span>Despite widespread deployment of wireless sensor networks (WSN) in remote and inapproachable locations, energy consumption/storage of WSN hindered its adoption. Similarly, the battery-powered sensor nodes are of no use once the battery is depleted. To overcome this limitation, energy harvesting is one of the key techniques. In this paper, an almost perpetual self-powered sensor node is proposed. This sensor node uses a solar panel to harvest energy while the entire energy management is accomplished by BQ25570. Similarly, a super-capacitor is used as an energy storage unit with long range radio access (LoRa) as a transceiver unit. We measured the power generated/consumed continuously for 15 days with a transmission interval of 10 minutes. The result shows that this sensor node can potentially last for more than 7 days even at a low illuminance. Considering periodic wakeup at every 10 seconds with a sleep interval of 3 sec, a timer-triggered mechanism saves approximately 595 milliwatts of energy in one day compared to a deep-sleep mechanism. Furthermore, it is found that the application of the novel idea of external timer-driven technology in sensor node reduces energy consumption and provides a much efficient power optimization mechanism compared to the deep sleep mechanism that prevailed in WSNs technology.</span>

Cuboid-based Wireless Sensor Network Localization Algorithm

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints on cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use anchor nodes, which are equipped with GPS units among unknown nodes and broadcast their current locations to help nearby unknown nodes with localization. In this paper we can proposed a novel algorithm of cuboid localization with the help of central point precision method. Simulation shows that the results are far better then existing cuboid methods and gain accuracy of up to 83% with a localization error of 1.6m and standard deviation of 2.7.