Wireless Sensor Network For Monitoring Research Articles

A self-stabilizing algorithm for edge monitoring in wireless sensor networks

Self-monitoring is a simple and effective mechanism for surveilling wireless sensor networks, especially to cope against faulty or compromised nodes. A node v can monitor the communication over a link e if both end-nodes of e are neighbors of v. Finding a set of monitoring nodes satisfying all monitoring constraints is called the edge-monitoring problem. The minimum edge-monitoring problem is known to be NP-complete. In this paper, we present a novel self-stabilizing algorithm for computing a minimal edge-monitoring set under the unfair distributed scheduler. For sparse networks the time complexity of this new algorithm is much lower than the currently best known algorithm.

Implementation of Aggregate Signcryption in Unattended Medical WSNs using Micaz

Healthcare applications are promising fields for wireless sensor networks called wireless medical sensor networks. The main issues in wireless medical sensor networks are reliable communication, patient mobility and security of sensed physiological data. In order to mobile patient monitoring, disconnected or unattended setting of wireless medical sensor networks is considered. The disconnected property causes periodic or offline data delivery of information. Moreover, medical sensors nodes should retain data for long time while they have limited battery and capacity. These challenges provide attacker to threat security of sensed data without being detected. In this paper, we propose an efficient aggregate signcryption technique to provide simultaneously confidentiality, integrity (by encrypting) and authenticating (by signing) for collected data. Moreover, the aggregation property reduces communication and space overhead as well as signcryption provides time efficiency by applying mostly linear operators. We further, compare our technique with the nest alternative works in the literature to show the efficiency and resilience against various attacks

Development of Dynamic Monitoring System of Cement Kiln’s Axis based on WSN

Aiming at the measurement of cement rotary kiln’s axis, the paper presents the design method of a wireless dynamic measurement system for rotary kiln’s axis. A wireless sensor network monitoring system that can collect multiple parameters was designed, which integrates the detection functions for kiln shell axis deviation, kiln tire axis deviation and drive gear synchronizing signal, and has the advantages of wireless transmission, low power consumption, and easy to install. ZigBee tree network was developed, which is beneficial to expand the capacity of wireless network, improve the efficiency of data transmission, reduce the cost, and shorten the development cycle. The sever measurement software was designed, which has the functions of data wireless acquisition and analysis for rotary kiln axis. The related prototypes of the monitoring device were developed, which verified the effectiveness of the system on the cement rotary kiln．

Enhancing barrier coverage with β quality of monitoring in wireless camera sensor networks

Over years, barrier coverage problems in wireless camera sensor networks have received an amount of attention for their important applications such as intrusion detection and battlefield surveillance. Though much work has been done in this field, few works focus on providing high surveillance quality efficiently. Recently, Cheng and Tsai pointed out the breadth of barrier-coverage of camera sensor network was significant to guarantee high quality of monitoring (QoM), and they proposed a β-breadth belt-barrier problem under 2D circumstances whose goal was to select camera sensors as few as possible to construct a β-breadth belt-barrier. In this paper, we study the problem of constructing a β-breadth belt-barrier with the minimum number of sensors thoroughly, both under 2D circumstances and 3D circumstances. Besides, we extend this problem and study how to build up k disjoint β-breadth belt-barriers under both 2D and 3D circumstances. We set many application scenarios in simulation and thoroughly study how our algorithms’ performances are affected by different environmental parameters, including the number of sensors and the breadth of a barrier.

Hybrid wireless sensor network for rescue site monitoring after earthquake

This paper addresses the design of a low-cost, low-complexity, and rapidly deployable wireless sensor network (WSN) for rescue site monitoring after earthquakes. The system structure of the hybrid WSN is described. Specifically, the proposed hybrid WSN consists of two kinds of wireless nodes, i.e., the monitor node and the sensor node. Then the mechanism and the system configuration of the wireless nodes are detailed. A transmission control protocol (TCP)-based request-response scheme is proposed to allow several monitor nodes to communicate with the monitoring center. UDP-based image transmission algorithms with fast recovery have been developed to meet the requirements of in-time delivery of on-site monitor images. In addition, the monitor node contains a ZigBee module that used to communicate with the sensor nodes, which are designed with small dimensions to monitor the environment by sensing different physical properties in narrow spaces. By building a WSN using these wireless nodes, the monitoring center can display real-time monitor images of the monitoring area and visualize all collected sensor data on geographic information systems. In the end, field experiments were performed at the Training Base of Emergency Seismic Rescue Troops of China and the experimental results demonstrate the feasibility and effectiveness of the monitor system.

Encircled Belt-Barrier Coverage in Wireless Visual Sensor Networks

In order to increase the Quality of Monitoring (QoM) of Wireless Visual Sensor Networks (WVSNs), we revisit the barrier coverage problem with three factors, including importance of image, breadth of image and rotation capability. Without consideration of importance of image, camera sensors can capture images of the intruder crossing the barrier but cannot guarantee that the captured images are the important portion of the intruder. Without consideration of breadth of image, image identification may be difficult. If camera sensors have rotation capability, how to select effective camera sensors to reduce the number of camera sensors required for barrier construction is another important issue. In this paper, for WVSNs consisting of camera sensors with and without rotation capability, we will respectively propose an algorithm to find a barrier with encircled coverage capability and β breadth. The proposed algorithms ensure that if any intruder crosses the barrier, important portions of the intruder can be clearly captured. Finally, the success rate of the proposed algorithms in three camera sensor distribution settings, including Uniform distribution, Poisson distribution and Gaussian distribution, will be evaluated through simulations.

Enabling Coverage-Preserving Scheduling in Wireless Sensor Networks for Structural Health Monitoring

Wireless sensor networks (WSNs) have been considered to be the next generation paradigm of structural health monitoring (SHM) systems due to the low cost, high scalability and ease of deployment. Due to the intrinsically energy-intensive nature of the sensor nodes in SHM application, it is highly preferable that they can be divided into subsets and take turns to monitor the condition of a structure. This approach is generally called as ‘coverage-preserving scheduling’ and has been widely adopted in existing WSN applications. The problem of partitioning the nodes into subsets is generally called as the ’maximum lifetime coverage problem (MLCP)’. However, existing solutions to the MLCP cannot be directly applied to SHM application. As compared to other WSN applications, we cannot define a specific coverage area independently for each sensor node in SHM, which is however the basic assumption in all existing solutions to the MLCP. In this paper, we proposed two approaches to solve the MLCP in SHM. The performance of the methods is demonstrated through both extensive simulations and real experiments.

Impact localization by a multi-radio sink–based wireless sensor network for large-scale structures

With the rapid development of wireless sensor network technology, more and more researchers have been interested in taking advantages of wireless sensor network to reduce weight and cost and to solve the installing problem of the wired structural health monitoring systems. A number of wireless-based structural health monitoring methods have been developed over the years to ensure the safety of large-scale structures. However, little research has been reported on wireless impact monitoring of large-scale composite structures due to the limitations of ordinary monitoring methods and wireless sensor networks. In this article, a wireless multi-radio sink which can access multiple communication channels is developed and adopted to build an impact monitoring wireless sensor network. Besides, a corresponding network architecture with an energy-weighted factor–based localization method adopted is presented to enable impact localization within the whole monitoring scope of the network. To verify the performance of the impact monitoring wireless sensor network, the experiments are performed on complex aircraft composite structures and the experimental results prove the effectiveness of the proposed wireless sensor network.

Synthesizing spatiotemporally sparse smartphone sensor data for bridge modal identification

Smartphones as vibration measurement instruments form a large-scale, citizen-induced, and mobile wireless sensor network (WSN) for system identification and structural health monitoring (SHM) applications. Crowdsourcing-based SHM is possible with a decentralized system granting citizens with operational responsibility and control. Yet, citizen initiatives introduce device mobility, drastically changing SHM results due to uncertainties in the time and the space domains. This paper proposes a modal identification strategy that fuses spatiotemporally sparse SHM data collected by smartphone-based WSNs. Multichannel data sampled with the time and the space independence is used to compose the modal identification parameters such as frequencies and mode shapes. Structural response time history can be gathered by smartphone accelerometers and converted into Fourier spectra by the processor units. Timestamp, data length, energy to power conversion address temporal variation, whereas spatial uncertainties are reduced by geolocation services or determining node identity via QR code labels. Then, parameters collected from each distributed network component can be extended to global behavior to deduce modal parameters without the need of a centralized and synchronous data acquisition system. The proposed method is tested on a pedestrian bridge and compared with a conventional reference monitoring system. The results show that the spatiotemporally sparse mobile WSN data can be used to infer modal parameters despite non-overlapping sensor operation schedule.

Joint Optimal Placement, Routing, and Flow Assignment in Wireless Sensor Networks for Structural Health Monitoring

Sensor node placement optimization has a significant role in wireless sensor networks, especially in structural health monitoring. Since sensor node placement affects the routing, optimization should be Jointly done for the node placement and routing. The existing work separately optimizes the node placement and routing (by performing routing after carrying out the node placement). However, this approach does not guarantee the optimality of the overall solution. In this paper, joint optimization of sensor placement, routing, and flow assignment is introduced and solved using mixed integer programming modeling. Finding an optimal solution for this joint problem is too complex. Hence, a near-optimal solution is obtained using genetic algorithms with reduced complexity. In addition, a heuristic algorithm for joint routing and flow assignment with placement is proposed using the effective independence model, which optimizes the information quality and energy consumption for efficient communication. Lastly, results are presented in a nine-floor building to compare the three proposed algorithms with the heuristic algorithm by Li et al. The numerical results show the efficiency of the proposed algorithms and the tradeoff between the efficiency and the complexity.

Simulation of the Core Technology of a Greenhouse-Monitoring System Based on a Wireless Sensor Network

To solve the topology structure of a greenhouse environment-monitoring system and the ductility of joints, this study presents a design of a greenhouse-monitoring system based on the ZigBee wireless sensor network (WSN). The hardware and software designs of the network node are provided, and the process of the ZigBee network coordinator is elucidated. The system uses the microcontroller unit PIC18F4620CC2420 wireless transceiver module to send and receive data. Data from temperature and humidity sensors are collected using an inter-integrated circuit bus through the ZigBee network transmission to the monitoring platform. Test results show that the system has the advantages of having a simple structure, flexible nodes, and low power consumption. It can effectively monitor the temperature and humidity in a wireless environment. WSNs considerably help in greenhouse environment monitoring. The use of advanced technology to control greenhouse temperature and humidity can satisfy the optimum growth environment of greenhouse crops and effectively improve the yield and quality of crops. The application of WSNs in greenhouse monitoring is significant to the development of modern and precision agriculture in China.

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A Study on Data Loss Compensation of WiFi-Based Wireless Sensor Networks for Structural Health Monitoring

In wireless data transmissions processes, data loss is an important factor that reduces the robustness of wireless sensor networks (WSNs). In many practical engineering applications, data loss compensation algorithms are then required to maintain the robustness, and such algorithms are typically based on compressive sensing with a large memory of microcontrollers needed. This paper presents an improved algorithm, based on random demodulator, to overcome the difficulty of microcontroller-dependence in the traditional data loss algorithms. The newly developed algorithm demonstrates the following advantages: 1) low space complexity; 2) low floating-point calculations; and 3) low time complexity. Therefore, it is more suitable to be embedded into ordinary nodes, comparing with the traditional algorithms. In this paper, a WSN based on WiFi is also developed for verifying the effectiveness and feasibility of the proposed algorithm. Field experiment on Xinghai Bay Bridge is done. Experimental results show that the WSN works properly and steady. Moreover, the data loss can be compensated effectively and efficiently through the use of the present algorithm.

Briefing: Advanced sensing technologies for structural health monitoring

The engineering, management, maintenance and upgrading of infrastructure requires fresh thinking to minimise the use of materials, energy and labour while still ensuring resilience. This can only be achieved by a full understanding of the performance of the infrastructure, both during its construction and throughout its design life, through the application of innovative sensor technologies and other emerging technologies. This approach covers the design and commissioning, construction process, exploitation and use and eventual decommissioning. Crucial elements of these emerging technologies are the innovative application of the latest sensor technologies, data management tools, manufacturing processes and supply chain management processes to the construction industry, both during infrastructure construction and throughout its design life. In particular, advances in sensing technologies such as fibre-optic sensors and wireless sensor networks for structural health monitoring have a huge potential to transform the approaches to the design, the construction and the operation of an infrastructure. This briefing article gives some examples of the recent application of these advanced sensing technologies to structural health monitoring for a large number of construction sites and existing infrastructure.

A visualization platform for internet of things in manufacturing applications

Purpose – The purpose of this paper is to present a visualization platform to control and monitor wireless sensor networks (WSNs) in manufacturing applications. Design/methodology/approach – To make the platform flexible and versatile, a modular framework is adopted in modeling and visualizing WSNs. The Eclipse programming environment is used to maximize the scalability and adaptability of the platform. A set of the core functional modules have been designed and implemented to support the system operation. The platform is validated through a case study simulation. Findings – The platform is capable of accommodating different operating systems such as Windows and Linux. It allows integrating new plug-ins developed in various languages such as Java, C, C++, and Matlab. The Graphic User Interface has been applied to process and visualize the acquired real-time data from a WSN, and the embodied methodologies can be used to predict the behaviors of objects in the network. Research limitations/implications – The work has shown the feasibility and potential of the proposed platform in improving the real-time performance of WSN. However, the number of the developed functional modules is limited, and additional effort is required to develop sophisticated functional modules or sub-systems for a customized application. Practical implications – The platform can be applied to monitor and visualize various WSN applications in manufacturing environments such as automated workcells, transportation systems, logistic, and storage systems. Originality/value – The work is motivated by the scarce research on the development tools for monitoring and visualization of WSNs in manufacturing applications. The proposed platform serves for both of system developers and users. It is modularized with a set of core functional modules; it can be extended to accommodate new functional modules with a minimal effort for a different application.

A wireless sensor network for urban environmental health monitoring: UrbanSense

Urban areas are generators of environmental emissions such as carbon dioxide (CO2), harmful air pollutants and noise, all with the potential to negatively impact the health and wellbeing of its human and non-human inhabitants. There is an urgent need to understand the characteristics of urban areas associated with variability in emissions and the potential for exposure to potential harmful environmental conditions. UrbanSense is a wireless sensor network (WSN) infrastructure designed to monitor environmental conditions at different temporal and spatial scales. The scalable infrastructure includes an extended range outdoor wireless sensing and data aggregation system, a web-based data management and visualization platform, and real-time event-based data stream integration. Sensors monitor changes in carbon dioxide (CO2), carbon monoxide (CO), noise (LAeq), as well as several meteorological conditions including wind speed and direction, temperature, relative humidity and precipitation. The implementation will provide opportunities for real-time data integration and an analysis system for environmental quality assessment, and may be realized on top of products arising from spatio-temporal (statistical) analyses and remotely-acquired data products such as satellite data. Sensor swapping and co-location with sensors from projects with different aims (traffic volume modelling and human tracking research) will add value for research in transportation planning, environmental regulation and policy and epidemiological studies focused on associations between environmental exposures and health outcomes.

Design and Implementation of an Industrial Wireless Sensor Network for Temperature Monitoring

Temperature signal is one of the key parameters in industrial processes. Accurate and effective temperature monitoring may provide necessary device information to the operator and prevent unexpected catastrophic equipment faults due to device overheat. Compared with wired monitoring system, wireless sensor networks (WSNs) monitoring system has many advantages, such as low cost and convenient installation. This paper proposes and implements a multichannel temperature monitoring system based on WSNs module, Jennic JN5139. The hardware circuit design of the sensor node and the software design for WSNs nodes and the centralized computer using C language and LabVIEW respectively are given in detailed. An optimization subsection algorithm based on least square for thermocouple nonlinear calibration is also explored to increase the measurement accuracy. The prototype system is evaluated with an electric furnace temperature monitoring system. The experimental results show the feasibility and effectiveness of the proposed system.

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Delay/Disruption Tolerant Network-Based Message Forwarding for a River Pollution Monitoring Wireless Sensor Network Application.

Communications from remote areas that may be of interest is still a problem. Many innovative projects applied to remote sites face communications difficulties. The GOLDFISH project was an EU-funded project for river pollution monitoring in developing countries. It had several sensor clusters, with floating WiFi antennas, deployed along a downstream river’s course. Sensor clusters sent messages to a Gateway installed on the riverbank. This gateway sent the messages, through a backhaul technology, to an Internet server where data was aggregated over a map. The communication challenge in this scenario was produced by the antennas’ movement and network backhaul availability. Since the antennas were floating on the river, communications could be disrupted at any time. Also, 2G/3G availability near the river was not constant. For non-real-time applications, we propose a Delay/Disruption Tolerant Network (DTN)-based solution where all nodes have persistent storage capabilities and DTN protocols to be able to wait minutes or hours to transmit. A mechanical backhaul will periodically visit the river bank where the gateway is installed and it will automatically collect sensor data to be carried to an Internet-covered spot. The proposed forwarding protocol delivers around 98% of the messages for this scenario, performing better than other well-known DTN routing protocols.

Energy Efficient Cross layer Routing Based on Unequal Clustering Mechanism for Wireless Sensor Networks in Tunnel Monitoring

Energy Efficient Cross layer Routing Based on Unequal Clustering Mechanism for Wireless Sensor Networks in Tunnel Monitoring