Smart Wireless Sensor Networks Research Articles

Wireless Smart Sensor Networks, System, Trends, and the Applications in Engineering

1School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China 2College of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081, China 3Department of Computer Science, University of North Georgia, Oakwood, GA 30566, USA 4Intelligent Systems and Biomedical Robotics Group, School of Computing, University of Portsmouth, Portsmouth PO1 3HE, UK

Efficient time synchronization for structural health monitoring using wireless smart sensor networks

Wireless smart sensor networks (WSSNs) have shown great promise in structural health monitoring (SHM), because of their advantages of low cost, higher flexibility, robust data management, and ability to provide better understanding of structural behavior through dense deployment of sensors. However, implementation of wireless SHM systems poses many challenges, one of which is ensuring adequate synchronization of the collected data. This issue arises in WSSNs because each smart sensor in the network having an independent processor with its own local clock, and this clock is not necessarily synchronized with the clocks of other sensors. Moreover, even though the clocks can be accurately synchronized by exchanging time information through beacon messages, the measured data may still be poorly synchronized because of random delays from both software and hardware sources; that is, synchronized clocks do not necessarily yield synchronized sensing. Various algorithms have been proposed to achieve both synchronized clocks and sensing. However, these protocols still lack the desired performance for SHM applications for reasons of extended data collection time, temperature variations resulting in nonlinear clock drift, requirement for prompt response, and so on. In this paper, the unique features and challenges of synchronized sensing for SHM applications are discussed, followed by a numerical investigation of the effect of nonlinear clock drift on data synchronization accuracy. A new synchronized sensing strategy considering nonlinear clock drift compensation is proposed with two different implementations to meet various application requirements. Experimental results show that the proposed time synchronization approach can compensate for temperature effects on clock drift and provide efficient and accurately synchronized sensing (<50 µs maximum error) for SHM, even for long sensing duration. Copyright © 2015 John Wiley & Sons, Ltd.

A Novel Wireless Mobile Platform to Locate and Gather Data From Optical Fiber SensorsIntegrated Into a WSN

This paper presents a novel design for a wireless mobile platform to locate and gather data from different types of optical fiber sensors, thereby enabling the more effective integration of a number of such optical fiber sensors with an advanced mobile wireless sensor network (WSN). This then more readily permits potential applications, such as monitoring in remote and harsh environments and tracking, exploiting fully the combined advantages offered both by the mobile WSN and the advanced optical fiber sensing technologies. The platform which was designed and implemented consists of an optical fiber sensor module and a smart mobile WSN module, which shows important advantages for mobile sensing and tracking and mesh networking. In this paper, a fiber Bragg grating-based temperature sensor and an intrinsic pH optical fiber sensor were specially designed and integrated successfully into the optical fiber sensor module as an exemplar to investigate the performance of the integrated system based on the mobile WSN platform. The positive experimental results obtained have confirmed the functionality of the platform designed and demonstrated its capacity for real-time optical fiber sensor data monitoring, processing, and wireless transmission. The successful creation of this type of wireless mobile platform with optical fiber sensors can thus be expected to make an important impact on a number of sectors, where either conventional optical sensor designs or WSNs alone cannot meet the systems requirements.

An Overview of a Wireless Sensor Network for Structural Health Monitoring Using X-Bee Pro Module

This paper proposes a new design for structural health monitoring devices system by integrating the strain gauge in digital sensor signal and embedded wireless communication system. X-Bee Pro modules are proposed to be integrated with the system to provide long range wireless connectivity to the devices. This system is designed to enhance the efficiency of structural health monitoring by obtaining real time data remotely from a different place. In order to achieve objectives and to develop a smart wireless system for structural health monitoring, the methodology of this study includes hardware designing and interfacing of a prototype according to the model system. Smart wireless sensor networks for structure health monitoring have the potential to facilitate more economical management in structure monitoring.

Energy Efficiency of Building Envelopes with Window Grid Patterns from Korean Traditional Residences

This study focuses on window patterns of Hanok, Korean traditional residence, and their effects on building performance and adaptabilities as building skins. The purpose of this study is to investigate the possibility of Hanok patterns as a new type of building envelope that satisfy both aesthetic and the efficiency of building space, and to suggest a new method based on Information and Communication Technology (ICT) for optimizing the building performance. For this research, a variety of Korean traditional window patterns were reviewed first, and a typical facade was applied for a comparative analysis in aspect of the effect on the building indoor environment. In addition, this study examines selected window patterns that could minimize heat loss and make it easy to adjust indoor lights with an embedded control system called Wireless Smart Sensor Network (WSSN). In conclusion, it is turned that ICT has played an important role as both a controller for the spatial environment and a simulator for evaluating various building factors such as envelope systems.

Hospital beds wireless sensor network and reducing decubitus ulcer.

Sir, Decubitus ulcer is a common and serious problem for inpatients in hospital. When someone is in sleep mode, pressure of his body weight enters at certain points and in the long-term, this will result in bruises and ultimately incurable wounds; therefore, hospital staff has to rotate these patients on their beds regularly to prevent it from happening. Due to the fact that prevention is more cost-effective than treatment and with the great cooperation of healthcare staff in the prevention of decubitus ulcer, decubitus ulcer is still as a significant problem for certain patients in hospital and society. Using wireless sensor network in hospital beds, which is known as smart beds is an appropriate solution to prevent decubitus ulcer and a way to forger the pressures of decubitus ulcer in patients hospitalized for a long time. In this regard, results of Chenu et al. study in 2013 entitled “an innovative embedded device for pressure ulcer prevention” showed that the decubitus ulcer prevention device for patients with spinal injury, which has the size of cigarette box and is embedded in a wheelchair, can be effective in preventing them. The device sensor is 100% textile, washable and inexpensive. The device function is to announce acquired alarm via watch or SMS in a smartphone before symptoms develop decubitus ulcer and by measuring the pressure between the seat mattress and patient's hip.[1] Yousefi et al. in their study, in 2011 entitled “a smart bed platform for monitoring and ulcer prevention” defined hospital smart bed as a bed with a sensor network, information devices, tile such as surface and computer control. This bed function was to analyze data by creating touch and pressure on surface sensors and creating irritation and then announce acquired alarm to the nurse to prevent ulcer pressure. Thus, the nurse spends more time for assessing events adverse and outcomes and patient's care instead of rotating patient every moment.[2] Since decubitus ulcer is a big problem in health care of patients with spinal injuries and these patients have no feeling for changing their status in comparison with healthy people, using a mattress with sensor is useful to diagnose the patient's problem and patient's tactile response. Using such system is useful in rehabilitation and is suitable for preventing decubitus ulcer. In a study done by Verbunt and Bartneck, in 2010 entitled “tactile feedback for the prevention of decubitus ulcers,” a technology is defined which is able to diagnose patient's inappropriate status and present an instruction to change his status. Changing status resulted in less risk of decubitus ulcer. This device includes a belt that receives a simple tap to a strong pressure as a signal, and this signal announces changing patient's natural status to patient and health care providers.[3] Wireless sensor networks are increasingly changing for telemedicine applications, monitoring patients, both in clinical conditions and at home. Using them will reduce user's discomfort and expenses, and increase mobility. Using smart systems and wireless sensor networks, depending on users’ needs, will also collect information regarding users and their environment.[4] In smart beds, to enhance the capabilities of the bed and its physical characteristics, smart beds are made by a combination of a sensor network, information devices and control by computer, which is able to generate waves and signals for mobility and increasing blood flow in inpatients and prevents decubitus ulcer and lesions resulting from hospitalization. Therefore, for decubitus ulcer prevention smart beds are useful especially for elderly people, patients with prolonged hospitalization or no motion and hospital staff in order to monitor patients’ treatments and decubitus ulcer and widespread use of it needs experienced specialists and relevant systems focus. Financial support and sponsorship This article resulted from part of master thesis in the School of Medical Management and Information Sciences, Isfahan University of Medical Sciences, Iran. Conflicts of interest There are no conflicts of interest.

WML: Wireless Sensor Network based Machine Learning for Leakage Detection and Size Estimation

Abstract Fluid (oil/gas/water) transportation systems present a significant challenge for pipeline health monitoring. With the development of smart devices capable of micro-sensing, on-board processing, and wireless communication capabilities, the wireless sensor networks are able to facilitate online learning and reliable event monitoring and reporting for distribution pipelines. This paper presents the design, development and testing of a smart wireless sensor network (WSN) for leak detection and size estimation in long range pipelines. This system uses wireless communication and machine learning (WML) to learn, make decisions and report the critical events like slow /small leakages in natural gas/oil pipeline autonomously. Machine learning is performed on negative pressure wave (NPW) to identify events based on raw data gathered by individual sensor nodes in network. In machine learning, we use support vector machine (SVM), K-nearest neighbor (KNN) and Gaussian mixture model (GMM) and Naive bayes in multi- dimensional feature space. The proposed technique is investigated for performance and capabilities by a series of trials on a field deployed test bed, with regard to performance of leakage detection and size estimation in pipelines.

An Adaptive Architecture for Ambient Intelligence Based on Meta-modeling, Smart Agents, and Wireless Sensor Networks

In this paper, an Ambient Intelligence (AmI) architecture for devising and implementing a smart laboratory in a university is presented. The architecture relies on a novel meta-model that abstracts the laboratory ambient using a context model, an adaptation model, an end-user model, and a domain model. Thus, the architecture offers, to the end-users, a set of adaptive AmI services that are supplied by smart agents and wireless sensor networks. The architecture was coded using SQLite, Jade, Protege, and CLIPs and simulated under Oracle's Solarium environment. The latency and scalability of the proposed architecture, as well as its ability to supply effectively the AmI services, were tested using both qualitative and quantitative standard performance metrics.

Smart wireless sensor networks for online faults diagnosis in induction machine

Online induction machine faults diagnosis is a concern to guarantee the overall production process efficiency. Nowadays, the industry demands the integration of smart wireless sensors networks (WSN) to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can produce sever damages. The origin of most recurrent faults in rotary machines is in the components: stator, rotor, bearing and others. This work presents a novel methodology for the online faults diagnosis in induction motors. This technique uses the smart WSN to obtain the machine condition based on the motor stator current analysis. The implementation of the proposed smart sensor methodology allows the system to perform online fault detection in a fully automated way. Simulation results presented show the efficiency of the proposed method to detect simple and multiple faults in induction machine. It provides detailed analysis to address challenges in designing and deploying WSNs in industrial environments, and its reliability.

Health Monitoring and Control of Civil Infrastructures using Wireless Smart Sensors

This paper investigates health monitoring and control (HMC) of civil infrastructures using wireless smart sensor networks. Two important requirements are (i) energy efficiency, and (ii) effective control to prevent damage of civil infrastructures. Fuzzy control scheme is incorporated in the system model to provide capability for addressing problems of imprecision and uncertainty that can be associated with values of dynamic response. Moreover, operation of wireless smart sensor networks is characterised as discounted semi-Markov decision process (SMDP) consisting of four states, namely: sleep, sense, store, and transmit. The objective is to choose policy that offers optimal energy-efficient transmission of vibration-based dynamic response, and subsequently activate appropriate control. Relevant mathematical representations are formulated for this model and its efficacy tested via numerical analysis,which is implemented in MATLAB software. It is shown by the results obtained that this HMC model can provide effective control and increase energy efficiency.

Energizing wireless sensor networks by energy harvesting systems: Scopes, challenges and approaches

As the wireless sensor networks (WSNs) technology has great advancement, small and smart WSN systems now can be used for more complicated and challenging applications. WSNs investigation has primarily believed the use of a convenient and inadequate energy source for empowering the sensors. A sensor becomes useless in the absence of energy and becomes unable to contribute to the utility of the network as a group. Therefore, extensive efforts have been used in finding energy-efficient networking protocols for increasing the life span of WSNs. However, there are promising WSN applications where the sensors are obligatory to work for a long time after their deployments. In these cases, batteries are tough or impractical to replace/recharge. Although, a little amount of power is required for these applications, the useable lifetime of WSNs is decreased by the gradual degradation of the batteries. With the motivation of raising the usable WSNs around us and to value a number of economic and environmental limitations, researchers are looking for new green and theoretically unlimited energy sources. Harvesting of energy from the ambient energy is the basement of these new sources. Energy harvesting devices efficiently and effectively capture, accumulate, store, condition, and manage this energy and supply it in a form that can be used to empower WSNs. This harvested energy can be an alternative energy source for adding-on a principal power source and thus increase the consistency of the whole WSN by preventing the disruption of power. A great deal of research has been reviewed and specific ranges of applications have been found. Though there are challenges to overcome, different researchers have taken different approaches to solve those. In this review, we have emphasized on different scopes, challenges, ideas and actions of energy harvesting for WSNs.

Smart Wireless Sensor Network to Detect and Protect Sheep and Goats to Wolf Attacks

The attacks on flocks of goats and sheep are causing great economic losses in some countries. The main causes of these are usually wild animals such as wolves, or thefts of young animals. When an animal feels the presence of people or animals different than the usual ones, it experiences changes in its vital signs. The parameters which are the most altered are the heart rate and body temperature. This paper presents the development of wireless sensor nodes which can monitor vital signs of sheep and goats. These nodes form a network of wireless nodes using IEEE 802.15.4 technology. The network runs a smart algorithm able to detect episodes of collective stress on flocks of goats and sheep caused by any predator attack overnight. When the system detects changes in vital signs of animals, it sends an alarm signal to alert the person in charge of the livestock facility and activates audible and visual alarms able to scare off predators and marauders. Our system can help breeders of goats and sheep to protect their herds avoiding large economic losses that this implies.

SmartPipes: Smart Wireless Sensor Networks for Leak Detection in Water Pipelines

Asset monitoring, specifically infrastructure monitoring such as water distribution pipelines, is becoming increasingly critical for utility owners who face new challenges due to an aging network. In the UK alone, during the period of 2009–2010, approximately 3281 mega litres (106) of water were wasted due to failure or leaks in water pipelines. Various techniques can be used for the monitoring of water distribution networks. This paper presents the design, development and testing of a smart wireless sensor network for leak detection in water pipelines, based on the measurement of relative indirect pressure changes in plastic pipes. Power consumption of the sensor nodes is minimised to 2.2 mW based on one measurement every 6 h in order to prolong the lifetime of the network and increase the sensor nodes’ compatibility with current levels of power available by energy harvesting methods and long life batteries. A novel pressure sensing method is investigated for its performance and capabilities by both laboratory and field trials. The sensors were capable of measuring pressure changes due to leaks. These pressure profiles can also be used to locate the leaks.

A wireless smart sensor network for automated monitoring of cable tension

As cables are primary load carrying members in cable-stayed bridges, monitoring the tension forces of the cables provides valuable information regarding structural soundness. Incorporating wireless smart sensors with vibration-based tension estimation methods provides an efficient means of autonomous long-term monitoring of cable tensions. This study develops a wireless cable tension monitoring system using MEMSIC’s Imote2 smart sensors. The monitoring system features autonomous operation, sustainable energy harvesting and power consumption, and remote access using the internet. To obtain the tension force, an in-network data processing strategy associated with the vibration-based tension estimation method is implemented on the Imote2-based sensor network, significantly reducing the wireless data transmission and the power consumption. The proposed monitoring system has been deployed and validated on the Jindo Bridge, a cable-stayed bridge located in South Korea.

Wireless sensor network for decentralized damage detection of building structures

The smart sensor technology has opened new horizons for assessing and monitoring structural health of civil infrastructure. Smart sensor's unique features such as onboard computation, wireless communication, and cost effectiveness can enable a dense network of sensors that is essential for accurate assessment of structural health in large-scale civil structures. While most research efforts to date have been focused on realizing wireless smart sensor networks (WSSN) on bridge structures, relatively less attention is paid to applying this technology to buildings. This paper presents a decentralized damage detection using the WSSN for building structures. An existing flexibility-based damage detection method is extended to be used in the decentralized computing environment offered by the WSSN and implemented on MEMSIC's Imote2 smart sensor platform. Numerical simulation and laboratory experiment are conducted to validate the WSSN for decentralized damage detection of building structures.

Rapid full-scale expansion joint monitoring using wireless hybrid sensor

Condition assessment and monitoring of bridges is critical for safe passenger travel, public transportation, and efficient freight. In monitoring, displacement measurement capability is important to keep track of performance of bridge, in part or as whole. One of the most important parts of a bridge is the expansion joint, which accommodates continuous cyclic thermal expansion of the whole bridge. Though expansion joint is critical for bridge performance, its inspection and monitoring has not been considered significantly because the monitoring requires long-term data using cost intensive equipment. Recently, a wireless smart sensor network (WSSN) has drawn significant attention for transportation infrastructure monitoring because of its merits in low cost, easy installation, and versatile on-board computation capability. In this paper, a rapid wireless displacement monitoring system, wireless hybrid sensor (WHS), has been developed to monitor displacement of expansion joints of bridges. The WHS has been calibrated for both static and dynamic displacement measurement in laboratory environment, and deployed on an in-service highway bridge to demonstrate rapid expansion joint monitoring. The test-bed is a continuous steel girder bridge, the Founders Bridge, in East Hartford, Connecticut. Using the WHS system, the static and dynamic displacement of the expansion joint has been measured. The short-term displacement trend in terms of temperature is calculated. With the WHS system, approximately 6% of the time has been spent for installation, and 94% of time for the measurement showing strong potential of the developed system for rapid displacement monitoring.

Efficient multihop communication for static wireless sensor networks in the application to civil infrastructure monitoring

SUMMARY Multihop communication is an essential functionality of wireless smart sensor networks used for full-scale civil infrastructure monitoring. It allows sensors to cooperate and deliver data between nodes outside the direct communication range. Multihop communication that can reliably collect a large amount of data generated by the entire monitoring system to a single base-station can be made efficient with the consideration of the specific communication characteristics of civil infrastructure monitoring as well as radio interference and channel contention. This paper proposes an efficient multihop communication service for large static wireless sensor networks in the application to civil infrastructure monitoring. The proposed protocols include a flooding-based routing method that is able to efficiently generate stable static routes and a theoretically efficiency-optimal data collection protocol to promptly retrieve data from the entire network. Additionally, crucial enhancements are introduced for the stable implementation of the proposed methods. Experiments and a full-scale instrumentation are also included to demonstrate the protocols' applicability. Copyright © 2013 John Wiley & Sons, Ltd.

Develoment of high-sensitivity wireless strain sensor for structural health monitoring

Due to their cost-effectiveness and ease of installation, wireless smart sensors (WSS) have received considerable recent attention for structural health monitoring of civil infrastructure. Though various wireless smart sensor networks (WSSN) have been successfully implemented for full-scale structural health monitoring (SHM) applications, monitoring of low-level ambient strain still remains a challenging problem for WSS due to A/D converter (ADC) resolution, inherent circuit noise, and the need for automatic operation. In this paper, the design and validation of high-precision strain sensor board for the Imote2 WSS platform and its application to SHM of a cable-stayed bridge are presented. By accurate and automated balancing of the Wheatstone bridge, signal amplification of up to 2507-times can be obtained, while keeping signal mean close to the center of the ADC span, which allows utilization of the full span of the ADC. For better applicability to SHM for real-world structures, temperature compensation and shunt calibration are also implemented. Moreover, the sensor board has been designed to accommodate a friction-type magnet strain sensor, in addition to traditional foil-type strain gages, facilitating fast and easy deployment. The wireless strain sensor board performance is verified through both laboratory-scale tests and deployment on a full-scale cable-stayed bridge.

Abnormal Human Being Vital Sign Detection Embedded on Smart Sensor with Collision Avoidance for Disaster Temporary Healthcare

In recent years, the production of mobile computing devices has motivated a revolutionary change in the computing world, which motivates the usage of a wireless ad-hoc and smart sensor network for monitoring the patient in disaster. Flow of signal from sensors to sink node may cause congestion in WSNs if a number of events sensing nodes attempt to send event information to the sink at the same time. Thus, this paper takes the advantages of smart sensors and proposes an energy-efficient and congestion avoidance vital signal detection framework to apply to the natural disaster results in a great number of injured people. The framework consists of several stages designed to improve the performance of wireless sensor networks. First, self-organized wireless ad-hoc and sensor network was simulated, in which all nodes try to organize themselves to organize a network. Nodes in the network reconfigure themselves repeatedly to respond to modifications in the number and location of nodes in order to prevent collisions in the receiver. In the second stage, we proposed a smart sensor processing system with the capability to extract the abnormal vital sign, to reduce the overhead in the aggregator and lower power consumption by sending only the abnormal vital sign. Furthermore, we propose to average polling rate to be suitable for both sender and receiver, in which the intermediate node can balance between the packet arrival rate and the packet service rate, thus avoiding congestion and enhancing the response time.

On-Board Computing for Structural Health Monitoring with Smart Wireless Sensors by Modal Identification Using Hilbert-Huang Transform

Smart wireless sensors have been recognized as a promising technology to overcome many inherent difficulties and limitations associated with traditional wired structural health monitoring (SHM) systems. Despite the advances in smart sensor technologies, on-board computing capability of smart sensors has been considered as one of the most difficult challenges in the application of the smart sensors in SHM. Taking the advantage of recent developments in microprocessor which provides powerful on-board computing functionality for smart sensors, this paper presents a new decentralized data processing approach for modal identification using the Hilbert-Huang transform (HHT) algorithm, which is based on signal decomposition technique. It is shown that this method is suitable for implementation in the intrinsically distributed computing environment found in wireless smart sensor networks (WSSNs). The HHT-based decentralized data processing is, then, programmed and implemented on the Crossbow IRIS mote sensor platform. The effectiveness of the proposed techniques is demonstrated through a set of numerical studies and experimental validations on an in-house cable-stayed bridge model in terms of the accuracy of identified dynamic properties.