Wireless Sensor Network For Monitoring Research Articles

Monitoring of Gas Distribution Pipelines Network Using Wireless Sensor Networks

The Wireless Sensor Networks (WSNs) usually consist of several wirelessly connected sensors, to accumulate the data from some geographically scattered field and communicate it to a central database. Thus WSNs become an expedient tool to monitor the widespread gas distribution network such as Sui Northern Gas Pipelines Ltd. Pakistan. In this paper, some routing protocols performance has been investigated for gas pipeline monitoring applications. Simulated comparison of various routing protocols for WSNs deployed over gas distribution pipeline networks can give a valuable insight into the workability of the system, its performance, and other critical design parameters. The estimated lifetime of the network, node deployment for encyclopedic operation, the impact of energy harvesting from the field, and placement of the sink node at an optimal location are the key issues in the design of the WSN for pipeline network monitoring. All these issues are studied through simulation of various protocols for WSNs based upon real geographic locations of the nodes, real-world power levels and power consumptions by various processes of the wireless sensor networks. The simulations results show that DDEEC based WSN, for monitoring an actual Gas Distribution Network with a substantial quantity of nodes, can run with about 99.9% alive nodes for a benchmark period of 10 years. It was also evident from the comparison of the simulation results that the routing protocol DDEEC based system performs 0.4 to 34% better than the system based on LEACH, SEP, DEEC, and its other variants.

Weighted Connected Vertex Cover Based Energy-Efficient Link Monitoring for Wireless Sensor Networks Towards Secure Internet of Things

Industry 4.0 utilizes the Internet of Things (IoT) to rise the efficiency in manufacturing and automation where wireless sensor networks (WSNs) are crucial technologies for communication layer of IoT. WSNs include hundreds of small sized sensor nodes that have the abilities of wireless transmission and environmental sensing. Wireless transmission is prone to various attacks such as data manipulation since data communication is achieved through transfer of radio packets. A countermeasure of this issue is link monitoring by deploying secure points that can physically capture and inspect radio packets. Graph theory plays a critical role to solve various problems in WSNs. Finding minimum Vertex Cover (VC) is an important NP-Hard graph theoretic problem in which the minimum set of nodes (vertices) is aimed to select in such a way that each link should be incident to at least one node from this set. VC is a significant structure for WSNs where it perfectly fits for link monitoring when nodes in VC are set as secure points (monitors). Since sensor nodes are generally battery-powered and have limited transmission range, energy-efficient multi-hop communication to the sink node is of utmost importance. In weighted connected VC (WCVC) structure, subgraph induced by monitor nodes are connected where monitors are chosen according to their weights. When weights of nodes are assigned as reciprocal of their energies, an energy-efficient virtual backbone can be formed. We propose a novel metaheuristic WCVC algorithm for link monitoring and backbone formation in WSNs modeled as undirected graphs. Our proposed algorithm integrates a genetic search with a greedy heuristic to improve WCVC solution quality and decrease the search time. To evaluate the efficiencies of greedy heuristics, we adopt three different heuristics for WCVC problem. We implement our algorithm with its counterparts and reveal that the algorithm is favorable in terms of solution quality and resource consumption.

Secure data aggregation scheme based on node self-adaptive monitoring for wireless sensor networks

Malicious nodes in wireless sensor networks will cause a great deviation in aggregation data. Such malicious nodes assigned with the aggregation task can forge and send a mass of false data. As a result, the network may consume a mass of resources and users may make wrong decisions. Concerning this problem, a secure data aggregation scheme based on node self-adaptive monitoring is proposed in this paper. According to the scheme, a master cluster head node and a vice cluster head node are selected, wherein, the vice cluster head node verifies the aggregation data produced by the master cluster head, the intra-cluster monitoring nodes monitor the behaviour of the master and vice cluster head nodes in a self-adaptive manner. Besides, the confidence interval theory is introduced to evaluate and calculate the credibility of nodes and highly credible node data are selected for data aggregation. Both theoretical analysis and experimental results show that our scheme can not only effectively recognise and shield malicious nodes, enhance accuracy of data aggregation but also prevent malicious master cluster head nodes from forging and sending a lot of false data.

Secure data aggregation scheme based on node self-adaptive monitoring for wireless sensor networks

Malicious nodes in wireless sensor networks will cause a great deviation in aggregation data. Such malicious nodes assigned with the aggregation task can forge and send a mass of false data. As a result, the network may consume a mass of resources and users may make wrong decisions. Concerning this problem, a secure data aggregation scheme based on node self-adaptive monitoring is proposed in this paper. According to the scheme, a master cluster head node and a vice cluster head node are selected, wherein, the vice cluster head node verifies the aggregation data produced by the master cluster head, the intra-cluster monitoring nodes monitor the behaviour of the master and vice cluster head nodes in a self-adaptive manner. Besides, the confidence interval theory is introduced to evaluate and calculate the credibility of nodes and highly credible node data are selected for data aggregation. Both theoretical analysis and experimental results show that our scheme can not only effectively recognise and shield malicious nodes, enhance accuracy of data aggregation but also prevent malicious master cluster head nodes from forging and sending a lot of false data.

Approach to Anomaly Detection in Self-Organized Decentralized Wireless Sensor Network for Air Pollution Monitoring

The paper reveals the essence and features of the proposed approach to detecting anomalies in a self-organizing decentralized wireless sensor network (WSN). As a basis for detecting anomalies, the used WSN is intended to monitor atmospheric air pollution near industrial facilities and human life objects. The distinctive features of such a network are the decentralized nature of its structure and services, the autonomy and mobility of the network nodes, as well as the possibility of non-deterministic physical movement of nodes in space. The spontaneous nature of the dynamic formation of the network topology as well as the assignment of roles and private monitoring functions between the available network nodes determines such networks are subject to attacks that exploit the properties of network decentralization and its self-organization. The proposed approach to detecting anomalies is based on the collection and analysis of data from sensors and is designed to increase the security of self-organizing decentralized WSN by identifying anomalies that are critical in the context of the monitoring purposes.

Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption

Wireless sensor network (WSN) can achieve real-time data collection and transmission of environment, soil, meteorology, crop physiology and other information in agriculture. The data provided by WSN could be used for decision making and management, which is very important in precision agriculture. Wheat farmland wireless sensor network has the characteristics of wide coverage area, long planting period, inconvenient energy supply, and serious impact of crop environment on wireless signal transmission. Routing protocol is an important method to achieve long-term WSN monitoring by selecting an appropriate path with low energy consumption for data transmission. According to the phenomenon of uneven environment and channel parameters caused by intensive crop growth in farmland, a non-uniform clustering routing protocol based on effective energy consumption (UCEEC) was proposed in this work. The method combined with the characteristics of multi-path fading of farmland environment signals. The idea of image segmentation was introduced. Nodes with high similarity were divided into a cluster area by the dissimilarity between nodes in order to improve the intracluster communication performance. Meanwhile, a multi-hop path selection method between cluster-heads based on the estimation of two-hop effective energy consumption is designed. The energy consumption cost factor is calculated by the effective energy consumption and the average energy consumption within the cluster to achieve the minimum and balance of the overall energy consumption of the network. Simulation results show that, compared with the existing Maximum Residual Energy Based Routing (MREBR) protocol, minimum Energy Consumption Based Routing (MEC) routing protocols, UCEEC improves the energy balance effect between nodes, prolongs the network life cycle, and realizes efficient energy utilization of wireless sensor network data collection in the complex environment of wheat field. Keywords: farmland, wireless sensor networks, multi-path fading channel, routing protocol, energy optimization DOI: 10.25165/j.ijabe.20211403.6540 Citation: Miao Y S, Zhao C J, Wu H R. Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption. Int J Agric & Biol Eng, 2021; 14(3): 163–170.

A Binary Adaptive Clone Shuffled Frog Leaping Algorithm for Three‐Dimensional Low‐Energy Target Coverage Optimization in Environmental Monitoring Wireless Sensor Networks

In recent years, more and more researchers have paid attention to the three‐dimensional target coverage of environmental monitoring wireless sensor networks (EMWSNs) under real environmental conditions. However, the target coverage method studied in the traditional two‐dimensional plane is full of loopholes when applied in the real three‐dimensional physical world. Most coverage algorithms usually only optimize for a single problem of target coverage or network energy consumption and cannot reduce network energy consumption while improving coverage. This paper proposes a novel binary adaptive clone shuffled leapfrog algorithm (BACSFLA) suitable for EMWSNs. BACSFLA has an excellent performance in the coverage of three‐dimensional nodes, which can significantly reduce the network energy consumption of ENWSNs in the coverage process, and greatly improve the coverage of nodes. Through simulation experiments, BACSFLA was compared with simulated annealing (SA) and genetic algorithm (GA) in the same conditional parameters. The coverage rate of BACSFLA in EMWSNs is 3.9% higher than that of GA and 5.4% higher than that of SA. The network energy consumption of BACSFLA is 36.0% lower than GA and 35.9% lower than SA. Moreover, BACSFLA can significantly reduce the calculation time and get better results in a shorter time.

A Chaotic Elite Niche Evolutionary Algorithm for Low‐Power Clustering in Environment Monitoring Wireless Sensor Networks

In recent years, as people’s demand for environmental quality has increased, it has become inevitable to monitor sensitive parameters such as temperature and oxygen content. Environmental monitoring wireless sensor networks (EMWSNs) have become a research hotspot because of their flexibility and high monitoring accuracy. This paper proposes a chaotic elite niche evolutionary algorithm (CENEA) for low‐power clustering in EMWSNs. To verify the performance of CENEA, simulation experiments are carried out in this paper. Through simulation experiments, CENEA was compared with shuffled frog leaping algorithm (SFLA), differential evolution algorithm (DE), and genetic algorithm (GA) in the same conditional parameters. The results show that CENEA balances node energy and improved node energy usage efficiency. CENEA’s network energy consumption is reduced by 8.3% compared to SFLA, 3.9% lower than DE, and 4.6% lower than GA. Moreover, CENEA improves the precision and minimizes the computation time.

Research on Green Habitat Design Based on Field Wireless Sensing Hazardous Substance Detection

Field wireless sensor network is the current global engineering field research hotspot for structural health monitoring wireless sensor network that is one of the important branches to real‐time monitoring of the safety status of the upper wood engineering structure to avoid the occurrence of many safety accidents caused by major structural and equipment damage and to guide the maintenance of major structures; the establishment of a wireless sensor network system is one of the current research priorities. This paper researches and designs a wireless sensor network system level scheme for structural health monitoring that is divided into two parts based on the hardware platform design and software development based on the system that focuses on the time synchronization protocol and synchronous acquisition method featuring synchronous acquisition start time scheme, time separation method, and flexible optimization model of time information. The method applies to high‐frequency acquisition to guarantee the time of sampling points in structural environmental measurement. The accuracy of the information and the reliability of the field diagnosis, for the detection of harmful substances, as well as leading to the construction of green habitat environment have a qualitative leap, for the design of green habitat environment that has enough progress.

A Review of Conventional Fault Detection Techniques in Solar PV Systems and a Proposal of Long Range (LoRa) Wireless Sensor Network for Module Level Monitoring and Fault Diagnosis in Large Solar PV Farms

This paper reviews various faults that exist in large solar Photovoltaic (PV) systems. The faults are reviewed in their various classes based on the location and structure. Conventional solutions for fault detection and various research work in PV system monitoring and fault detection are reviewed. It is obvious that PV module level monitoring exhibit advantages over array or string monitoring. Therefore, the paper proposes the use of Long Range (LoRa) Wireless Sensor Networks (WSN) for PV module level monitoring and fault diagnosis. LoRa was proposed for this application due to the advantages it has over other wireless technologies which include long range of data transfer, low cost, low power consumption and multi sensor connection capabilities.

Multiagent Architecture for Bridge Capacity Measurement System Using Wireless Sensor Network and Weight in Motion

Wireless sensor network (WSN) has played important roles in various aspects of life including in bridge structural health monitoring system. Due to environmental and operational circumstances, a bridge needs to be monitored to make sure its continuous availability and operational safety. The structural stiffness of a bridge will decrease after some period of time due to structural strength declining and cracking. The change in bending stiffness will change the structural dynamic characteristics of the bridge and its capacity. Therefore, an automatic assessment system for bridge capacity is required. This article proposes the development of data acquisition and processing method for bridge capacity determination using its dynamic response, based on agent-based in-network processing. The use of WSN in bridge capacity monitoring and diagnostic also allows for sending warning messages to the control room. Experiment in the laboratory-scale bridge is performed to test the proposed system performance and the result was well validated with the finite-element analysis (FEA) results with modal assurance criterion value 0.90 that shows the high correlation degree between the FEA and the experiment. In addition, the processing time and energy consumption are compared with previous similar work, which shows the efficiency of the proposed system.

WITHDRAWN: Developing a software reliability evaluation model for wireless sensor networks based on analysis of software fault growth

Abstract Due to potential of various application in emergency and security monitoring fields, fault tolerance monitoring in wireless sensor networks (WSNs) software reliability became one of the most fundamental concern in computer field. In WSNs Previous literature had been proposed about how to improve network reliability. However the work done on establishing evaluating models of reliability for WSNs are insufficient yet. In this article, a model for wireless sensor networks (WSNs) is developed for the reliability evaluation. This network state based model can effectively do the evaluation of the probability of successful transmission of data in WSNs with the consideration of the work states of both the sensor node’s different modules. For WSNs we did the evacuation for reliability of in both tasks i.e., single, multi-task modes. At the same time, how different network topologies, affect the reliability of WSNs is also discussed respectively. To evaluate the reliability of WSNs the simulation attempts are shown in results that impacts network state on reliability and the effectiveness in different reliable mechanisms.

Research on wireless sensor network system for structural damage monitoring

In recent years, the application of wireless sensor networks in the field of structural monitoring has been widely concerned by experts and scholars in various countries. The throughput and real-time performance of the wireless sensor network should be considered when the structure health monitoring wireless sensor network is deployed. According to the characteristics and requirements of wireless structure damage monitoring, this paper analyzes the system from three aspects: monitoring system process, node design and damage diagnosis algorithm.

Data Management and Visualization of Coastal Railway in Wireless Sensor Network Monitoring System

Ji, X.R., 2020. Data management and visualization of coastal railway in wireless sensor network monitoring system. In: Al-Tarawneh, O. and Megahed, A. (eds.), Recent Developments of Port, Marine, and Ocean Engineering. Journal of Coastal Research, Special Issue No. 110, pp. 219–222. Coconut Creek (Florida), ISSN 0749-0208.With the continuous progress of industrialization in our country, machinery and equipment are developing to higher frequency and larger scale. How to automate and monitor is the key parts which are widely distributed and in bad working environment in machinery and equipment. Therefore, the realization of scientific life prediction and fault diagnosis is an important issue, which is widely concerned by the industry at present. This paper studies the fusion method of equipment information data and geographic information data in the wireless sensor network (WSN), and realizes the fusion of WSN sensing data based on the proposed development environment. Then, we establish the database model and parses the data file. In addition, we realize data visualization in web environment based on the Silverlight module. Finally, the visual part of the coastal railway monitoring WSN system established in this paper is tested by function test and performance test.

LDAP: Lightweight Dynamic Auto-Reconfigurable Protocol in an IoT-Enabled WSN for Wide-Area Remote Monitoring

IoT (Internet of Things)-based remote monitoring and controlling applications are increasing in dimensions and domains day by day. Sensor-based remote monitoring using a Wireless Sensor Network (WSN) becomes challenging for applications when both temporal and spatial data from widely spread sources are acquired in real time. In applications such as environmental, agricultural, and water quality monitoring, the data sources are geographically distributed, and have little or no cellular connectivity. These applications require long-distance wireless or satellite connections for IoT connectivity. Present WSNs are better suited for densely populated applications and require a large number of sensor nodes and base stations for wider coverage but at the cost of added complexity in routing and network organization. As a result, real time data acquisition using an IoT connected WSN is a challenge in terms of coverage, network lifetime, and wireless connectivity. This paper proposes a lightweight, dynamic, and auto-reconfigurable communication protocol (LDAP) for Wide-Area Remote Monitoring (WARM) applications. It has a mobile data sink for wider WSN coverage, and auto-reconfiguration capability to cope with the dynamic network topology required for device mobility. The WSN coverage and lifetime are further improved by using a Long-Range (LoRa) wireless interface. We evaluated the performance of the proposed LDAP in the field in terms of the data delivery rate, Received Signal Strength (RSS), and Signal to Noise Ratio (SNR). All experiments were conducted in a field trial for a water quality monitoring application as a case study. We have used both static and mobile data sinks with static sensor nodes in an IoT-connected environment. The experimental results show a significant reduction (up to 80%) of the number of data sinks while using the proposed LDAP. We also evaluated the energy consumption to determine the lifetime of the WSN using the LDAP algorithm.

A Survey on DV-Hop localization Techniques in Three- Dimensional Wireless Sensor Networks

Location information is prerequisite for wireless sensor networks (WSNs) monitoring and control applications, since there is no meaning without position information for collected data. Distance vector hop (DV-Hop) localization algorithm as the typical range-free algorithm that has been widely applied in various applications. Nowadays, the research on range-free localization for WSNs is mostly based on two-dimensional (2D) space. Hence, there are few surveys concentrated on range-free localization in three-dimensional (3D) WSNs. This motivated us to present an extensive overview of enhanced DV-Hop localization algorithms in 3D WSNs. This paper focused on critical challenge between 2D and 3D in localization model, representative range-free 3D localization technique surveys. Moreover, a comprehensive taxonomy of most essential enhanced methods applied in 3D DV-Hop is illustrated. A considerable comparison in term of localization error, computational complexity and node type is given. Future research directions dealing with localization under 3D DV-Hop is also discussed.

A Design and Development of a Wireless Sensor Network for Potential Monitoring and Localization

This paper presents an analysis of the received signal strength indicator (RSSI) from the radio frequency signals for human identification in an indoor wireless sensor network (WSN). Instead of using closed-circuit television as the existing security platform, this indoor safety system was improved with a convenient, cheap, and low-power solution. The system was developed using 20 of ESP8266-12F Wi-Fi modules transmitters and another 2 of ESP8266-12F as the access points located in 3 m × 3 m area of interest. With a suitable coordinate of sensor nodes, a WSN telemetry could be established to minimize the blind spot area and limit the movement of the intruder with a minimum area of 0.2 m2. The RSSI measurement was repeatedly conducted for three different conditions, in an empty room, with the presence of a single intruder and the presence of multiple intruders. Based on the RSSI values, we found that there are distinctive features of data that can be utilized as flags for classifying the three above conditions. Besides that, to justify the efficiency of system performance, we also examined the sensitivity of RSSI values towards the variation of temperature. Our results show that the RSSI average values for both morning and night were practically the same. However, during the afternoon, the RSSI signal strength fluctuated by − 1.0 dBm. These results motivate the development of an alarm system that only uses the RSSI statistics to detect human presence.

Wireless sensor network monitoring algorithm for partial discharge in smart grid

With the continuous improvement of power grid intelligent requirements, the Power Internet of Things develops rapidly. Substation is an important part of the power grid. The real-time monitoring of its equipment is conducive to the timely detection and removal of power supply faults. In this paper, a monitoring network is built for partial discharge (PD) of high voltage (HV) equipment. According to the three-dimensional characteristics of the equipment, the deployment strategy of ultrasonic sensors for PD monitoring is discussed. A virtual force algorithm based on adaptive angle adjustment is proposed. It is proved that the application of that algorithm can cover more than 94% of target in the range of controllable convergence. According to the target triggering characteristics of PD, the networking method of wireless sensor network is discussed. A sensor cooperation scheme based on the standing guard protocol is proposed, which verifies its energy saving and time delay shortening effect on the basis of ensuring the target acquisition rate. This paper describes the application of dynamic alliance routing protocol in PD information transmission, designs the process and steps of the protocol. Its performance is better than LEACH and Opportunity Routing protocol.

An intelligent monitoring of greenhouse using wireless sensor networks

Over recent years, the interest for vegetables and fruits in all seasons and places has much increased, from where diverse countries have directed to the commercial production in greenhouse. In this article, we propose an algorithm based on wireless sensor network technologies that monitor the microclimate inside a greenhouse and linear equations model for optimization plant production and material cost. Moreover, we also suggest a novel design of an intelligent greenhouse. We validate our algorithms with simulations on a benchmark based on experimental data made at lNRA of Montfavet in France. Finally, we calculate the statistical estimators RMSE, TSSE, MAPE, EF and R2. The results obtained are promising, which shows the efficiency of our proposed system.

Comparative Study of IoT-Based Topology Maintenance Protocol in a Wireless Sensor Network for Structural Health Monitoring

A structural health monitoring (SHM) system is an approach for identifying the damages caused to various kinds of structures using different system functions and providing the necessary feedback about structure’s conditions. As civil structures are the backbone of our society, to determine its daily operations is a very important issue. The performance measurement of those structures is manual whereas a computer-based monitoring system could automatically assess the structural damages and identify its exact location. Recently, wireless sensor networks (WSNs) have attracted a great deal of attention for remote sensing applications due to flexibility to measure of various activity of large scale network. Since technology is advancing day by day, the overall cost of a monitoring system is also decreased. However, the major challenging fact of a WSNs is to provide scalability for covering a large area. The main question is arisen how much capable have of a monitoring system to turn off unnecessary nodes to save energy while there are no events detected. To support the scalability required of an existing network and save the node energy for future use, we propose a topology maintenance protocol integrated with construction to address the issue of a node’s energy consumption by placing it optimally and extending the monitoring system’s lifetime. As per the authors’ acknowledgement that, a little attention has been paid to developing such a hybrid approach. To mitigate node energy consumption issue with large scale support, an Internet of Things (IoT)-based maintenance approach is the best candidate for obtaining better system lifetime responses. Therefore, the main goal of this work is to develop an ‘on-the-fly’-based topology maintenance monitoring system, which can maintain a network’s infrastructure while gathering a node’s information to switch its state regularly when the present network is no longer optimal.