Real-time Monitoring Applications Research Articles

Energy-efficient and low-delay scheduling scheme for low power wireless sensor network with real-time data flows

In this paper, we propose an energy-efficient and low-delay scheduling EELDS scheme for interruptible preamble sampling-based medium access control MAC protocols e.g., BoX-MAC-2 and X-MAC in IEEE 802.15.4 wireless sensor network WSN, which considers energy efficiency while reducing delay and contention in the context of real-time data gathering and remote monitoring applications. It is built on MAC layer and exploits local information to coordinate the MAC schedules of nodes in a slowly-changing topology, just with light overhead. The scheme also considers the adaptation to data aggregation with real-time data flows. Therefore, our scheme allows for much longer network lifetime while satisfying the delay constraints. The implementation and simulation results show the performance of the proposed scheme.

Vibration Frequencies Extraction of the Forth Road Bridge Using High Sampling GPS Data

This paper proposes a scheme for vibration frequencies extraction of the Forth Road Bridge in Scotland from high sampling GPS data. The interaction between the dynamic response and the ambient loadings is carefully analysed. A bilinear Chebyshev high-pass filter is designed to isolate the quasistatic movements, the FFT algorithm and peak-picking approach are applied to extract the vibration frequencies, and a GPS data accumulation counter is suggested for real-time monitoring applications. To understand the change in the structural characteristics under different loadings, the deformation results from three different loading conditions are presented, that is, the ambient circulation loading, the strong wind under abrupt wind speed change, and the specific trial with two 40 t lorries passing the bridge. The results show that GPS not only can capture absolute 3D deflections reliably, but also can be used to extract the frequency response accurately. It is evident that the frequencies detected using the filtered deflection time series in different direction show quite different characteristics, and more stable results can be obtained from the height displacement time series. The frequency responses of 0.105 and 0.269 Hz extracted from the lateral displacement time series correlate well with the data using height displacement time series.

Absolute group refractive index measurement of air by dispersive interferometry using frequency comb.

The absolute group refractive index of air at 1563 nm is measured by dispersive interferometry, and a combined uncertainty of 1.2 × 10(-8) is achieved. The group refractive index of air is calculated from the dispersive interferograms of the two beams passing through the inner and outer regions of a vacuum cell by fast-Fourier-transform. Experimental results show that the discrepancies between our method and modified Edlén equation are less than 3.43 × 10(-8) and 4.4 × 10(-8) for short-term and long-term experiments, respectively. The interferogram update rate is 15 ms, which makes it suitable for application of real-time monitoring. Furthermore, it is promising to improve the measurement uncertainty to 3.0 × 10(-9) by changing the material of the vacuum cell and measuring its length more accurately through optical interferometry.

A Phasor Measurement Unit Based Fast Real-time Oscillation Detection Application for Monitoring Wind-farm-to-grid Sub–synchronous Dynamics

—The increase of wind power share increasing has lead to operational challenges for its integration and impact on power grids. Regarding this, unexpected dynamic phenomena, such as oscillatory events around 13 Hz, among different wind farms were recorded in the United States Oklahoma Gas & Electric. Such interactions differ from traditional inter-area oscillations, and the ability to detect them is the beyond measurement capabilities of most of existing measurement equipment and monitoring tools in energy management systems. This article presents the development and implementation of algorithms for fast sub-synchronous oscillation detection, focusing on the aforementioned case. It proposes a real-time monitoring application that exploits synchronized phasor measurements, allowing real-time detection of sub-synchronous wind farm dynamics. This tool was built as a prototype for real-time application and utilizes phasor measurement unit data for enhanced monitoring and control. The article focuses on the tool’s design and its algorithms. Also, it will briefly present three approaches carried out for testing and validating the phasor measurement unit based application, one of which compares the proposed tool with an existing tool at Oklahoma Gas & Electric. Through such experiments, the tool presented in the article has been positively validated for real-time applications.

Cross-Layer Admission Control to Enhance the Support of Real-Time Applications in WSN

Real-time monitoring applications may be used in a wireless sensor network (WSN) and may generate packet flows with strict quality of service requirements in terms of delay, jitter, or packet loss. When strict delays are imposed from source to destination, the packets must be delivered at the destination within an end-to-end delay (EED) hard limit in order to be considered useful. Since the WSN nodes are scarce both in processing and energy resources, it is desirable that they only transport useful data, as this contributes to enhance the overall network performance and to improve energy efficiency. In this paper, we propose a novel cross-layer admission control (CLAC) mechanism to enhance the network performance and increase energy efficiency of a WSN, by avoiding the transmission of potentially useless packets. The CLAC mechanism uses an estimation technique to preview packets EED, and decides to forward a packet only if it is expected to meet the EED deadline defined by the application, dropping it otherwise. The results obtained show that CLAC enhances the network performance by increasing the useful packet delivery ratio in high network loads and improves the energy efficiency in every network load.

Real-time monitoring of trace-level VOCs by an ultrasensitive lamp-based VUV photoionization mass spectrometer

Abstract. In this study, we report on the development of a lamp-based vacuum ultraviolet photoionization mass spectrometer (VUV-PIMS) in our laboratory; it is composed of a radio-frequency-powered VUV lamp, a VUV photoionizer, an ion-migration lens assembly, and a reflection time-of-flight mass spectrometer. By utilizing the novel photoionizer consisting of a photoionization cavity and a VUV light baffle, the baselines of the mass spectra decreased from 263.6 ± 15.7 counts to 4.1 ± 1.8 counts. A detection limit (2σ) of 3 pptv was achieved for benzene after an acquisition time of 10 s. To examine its potential for real-time monitoring applications of samples, the developed VUV-PIMS was employed for the continuous measurement of urban air for 6 days in Beijing, China. Strong signals of trace-level volatile organic compounds, such as benzene and its alkylated derivatives, were observed in the mass spectra. These initial experimental results reveal that the instrument can be used for the online monitoring of trace-level species in the atmosphere.

Real-Time Monitoring and Early Warning Method Utilizing FBG Sensors in the Retrofitting Process of Structures

Associated with a project, the application of real-time monitoring and early warning system in the retrofitting process of structures was investigated. Based on the software ANSYS, structural analysis and thermal analysis were carried out to determine the distribution of sensors and the early warning threshold value in monitoring process. SHM system was developed for damage sensing in real-time using FBG sensors. Eight FBG sensor clusters consisting of a strain sensor and a temperature sensor were welded on the steel beam surface. Using these FBG sensors, the real-time strains in key positions during the cutting process of steel beam were measured. The monitoring data provided the early warnings and effective reference for analyzing the stability of steel beam in real-time.

A novel localization and coverage framework for real-time participatory urban monitoring

Participatory sensing is a powerful paradigm in which users participate in the sensing campaign by collecting and crowdsourcing fine-grained information and opinions about events of interest (such as weather or environment monitoring, traffic conditions or accidents, crime scenes, emergency response, healthcare and wellness management), thus leading to actionable inferences and decisions. Based on the nature of user involvement, participatory sensing applications can be of two types—automated and user manipulated. The first type of applications automatically collects data samples from smartphone sensors and sends them to the server. On the other hand, the second type of applications depends on the users to manually collect data samples and upload them at their convenience. Because of the high density of smartphone users in urban population and ease of participation, the automated participatory sensing paradigm can be effectively applied to continuous monitoring of various phenomena in urban scenarios (e.g., fine-grained temperature monitoring, noise or air pollution), leading to what is called participatory urban sensing. However, for creating a fine-grained and real-time map of the monitored area, the data samples need to be collected continuously (at a high frequency) which poses several research challenges. First, how to ensure coverage of the collected data that reflects how well the targeted area is monitored? Second, how to localize the smartphones since continuous usage of the location sensor (e.g., GPS) can drain the battery in few hours? Third, how to provide energy efficiency in the data collection process by collecting necessary data samples in each data collection round? In this article, we propose a novel framework called PLUS to address three major issues in real-time participatory urban monitoring applications, namely, ensuring coverage of the collected data, localization of the participating smartphones, and overall energy efficiency of the data collection process. Specifically the PLUS framework can guarantee a specified requirement of partial data coverage of the monitored area in an energy efficient manner. Additionally we devised a Markov-Predictor based energy efficient outdoor localization scheme for the mobile devices to participate in the data collection process. Simulation studies and real life experiments exhibit that PLUS can significantly reduce energy consumption of the mobile devices for urban monitoring applications as compared to traditional approaches.

Implementation of GPU-accelerated back projection for EPR imaging.

Electron paramagnetic resonance (EPR) Imaging (EPRI) is a robust method for measuring in vivo oxygen concentration (pO2). For 3D pulse EPRI, a commonly used reconstruction algorithm is the filtered backprojection (FBP) algorithm, in which the backprojection process is computationally intensive and may be time consuming when implemented on a CPU. A multistage implementation of the backprojection can be used for acceleration, however it is not flexible (requires equal linear angle projection distribution) and may still be time consuming. In this work, single-stage backprojection is implemented on a GPU (Graphics Processing Units) having 1152 cores to accelerate the process. The GPU implementation results in acceleration by over a factor of 200 overall and by over a factor of 3500 if only the computing time is considered. Some important experiences regarding the implementation of GPU-accelerated backprojection for EPRI are summarized. The resulting accelerated image reconstruction is useful for real-time image reconstruction monitoring and other time sensitive applications.

Efficient Cluster-Based Sleep Scheduling for M2M Communication Network

Machine-to-machine (M2M) communication networks comprise a large number of machine-type communication (MTC) devices such as sensors, radio frequency identification readers, and smart meters. Thus, M2M networks are becoming popular in real-time monitoring, surveillance, and security applications. Scheduling the active and idle states of MTC devices is significantly important to achieve a longer network lifetime and reduce collision during data transmission. Existing node sleep scheduling schemes are mainly designed to reduce the energy consumption of MTC devices. These schemes do not support mobility of MTC devices and thus cannot be used in mobility-centric M2M applications. Thus, we propose a cluster-based energy-efficient, mobility-centric node scheduling scheme for M2M (CENM) communication networks. The proposed CENM scheduling scheme provides (i) network coverage by keeping a minimum number of MTC devices in active state and (ii) fault tolerance by selecting alternative cluster heads and member nodes. Simulation results show that the CENM scheduling scheme is more reliable than the existing CCNS scheduling scheme since the first node in CENM scheme fails much later than that in CCNS scheduling scheme. Simulation results also show that the CENM scheduling scheme outperforms the CCNS, LEACH-M and LEACH-ME scheduling schemes in terms of network energy consumptions, network lifetime, and total message transmissions.

Novel Knob-integrated fiber Bragg grating sensor with polyvinyl alcohol coating for simultaneous relative humidity and temperature measurement.

A novel high performance optical fiber sensor for simultaneous measurement of relative humidity (RH) and temperature based on our newly designed knob-integrated fiber Bragg grating (FBG) is proposed and experimentally demonstrated. The knob-shaped taper followed by an FBG works as a multifunctional joint that not only excites the cladding modes but also recouples the cladding modes reflected by the FBG back into the leading single mode fiber. Polyvinyl alcohol (PVA) film is plated on the fiber surface by dip-coating technique as a humidity-to-refractive index (RI) transducer, and affects the intensity of reflected cladding modes by way of evanescent fields. By monitoring the intensity and wavelength of the reflected cladding modes, the RH and temperature variance can be determined simultaneously. Experimental results show an RH sensitivity of up to 1.2 dB/%RH within an RH range of 30-95%, which is significantly better than previously reported values. And the temperature sensitivity of 8.2 pm/°Ccould be achieved in the temperature range of 25-60°C. A fast and reversible time response has also been demonstrated, enabling to pick up a humidity change as fast as 630 ms. The capability of simultaneous measurement of RH and temperature, the fast response, the reusability and the simple fabrication process make this structure a highly promising sensor for real-time practical RH monitoring applications.

In-cylinder pressure-based direct techniques and time frequency analysis for combustion diagnostics in IC engines

In-cylinder pressure measurement and analysis has historically been a key tool for off-line combustion diagnosis in internal combustion engines, but online applications for real-time condition monitoring and combustion management have recently become popular. The present investigation presents and compares different low computing-cost in-cylinder pressure based methods for the analyses of the main features of combustion, that is, the start of combustion, the end of combustion and the crankshaft angle that responds to half of the overall burned mass. The instantaneous pressure in the combustion chamber has been used as an input datum for the described analytical procedures and it has been measured by means of a standard piezoelectric transducer.Traditional pressure-based techniques have been shown to be able to predict the burned mass fraction time history more accurately in spark ignition engines than in diesel engines. The most suitable pressure-based techniques for both spark ignition and compression ignition engines have been chosen on the basis of the available experimental data. Time–frequency analysis has also been applied to the analysis of diesel combustion, which is richer in events than spark ignited combustion. Time frequency algorithms for the calculation of the mean instantaneous frequency are computationally efficient, allow the main events of the diesel combustion to be identified and provide the greatest benefits in the presence of multiple injection events. These algorithms can be optimized and applied to onboard diagnostics tools designed for real control, but can also be used as an advanced validation tool for refined combustion models.The presented results on the pressure-based techniques, including a time frequency analysis, have been compared with the numerical outcomes from previously developed two- and three-zone thermodynamic combustion models.

Validation of performance of real-time kinematic PPP. A possible tool for deformation monitoring

Structural failures (bridge or building collapses) and geohazards (landslides, ground subsidence or earthquakes) are worldwide problems that often lead to significant economic and loss of life. Monitoring the deformation of both natural phenomena and man-made structures is a major key to assessing structural dynamic responses. Actually, this monitoring process is under real-time demand for developing warning and alert systems.One of the most used techniques for real-time deformation monitoring is the Global Navigation Satellite System (GNSS) real-time procedure, where the relative positioning approach, using a well-known reference station, has been applied.This study was conducted to evaluate the actual quality of the real-time kinematic Precise Point Positioning (PPP) GNSS solution for deformation monitoring, where it can be concluded that a promise tool is under development and should be taken into account on actual and near future real-time deformation monitoring studies and applications.

A low power miniaturized monitoring system of six human physiological parameters based on wearable body sensor network

Purpose – The purpose of this paper is to design a low-power human physiological parameters monitoring system which can monitor six vital parameters simultaneously based on wearable body sensor network. Design/methodology/approach – This paper presents a low-power multiple physiological parameters monitoring system (MPMS) which comprises four subsystems. These are: electrocardiogram (ECG)/respiration (RESP) parameters monitoring subsystem with embedded algorithms; blood oxygen (SpO2)/pulse rate (PR)/body temperature (BT)/blood pressure (BP) parameters monitoring subsystem with embedded algorithms; main control subsystem which is in charge of system-level power management, communication and interaction design; and upper computer software subsystem which manipulates system function and analyzes data. Findings – Results have successfully demonstrated monitoring human ECG, RESP, PR, SpO2, BP and BT simultaneously using the MPMS device. In addition, the power reduction technique developed in this work at the physical/hardware level is effective. Reliability of algorithms developed for monitoring these parameters is assessed by Fluke Prosim8 Vital Signs Simulators (produced by Fluke Corp. USA). Practical implications – The MPMS device provides long-term health monitoring without interference from normal personal activities, which potentially allows applications in real-time daily healthcare monitoring, chronic diseases monitoring, elderly monitoring, human emotions recognization and so on. Originality/value – First, a power reduction technique at the physical/hardware level is designed to realize low power consumption. Second, the proposed MPMS device enables simultaneously monitoring six key parameters. Third, unlike most monitoring systems in bulk size, the proposed system is much smaller (118 × 58 × 18.5 mm3, 140 g total weight). In addition, a comfortable smart shirt is fabricated to accommodate the portable device, offering reliable measurements.

A smart all-in-one theranostic platform for CT imaging guided tumor microwave thermotherapy based on IL@ZrO2 nanoparticles.

This study develops a simple hollow ZrO2 nanostructure as a carrier to encapsulate ionic liquid (IL), which integrates the CT imaging function of the ZrO2 shell and the microwave susceptibility function of the IL core. The simple nanostructure can be used as a multifunctional theranostic agent via combining diagnostic and therapeutic modalities into one "package". Based on the microwave susceptibility properties, the tumor inhibiting ratio can be over 90% in mice models after one-time thermal therapy upon microwave irradiation. In vitro and in vivo imaging results prove the potential of CT imaging application for real-time monitoring of biodistribution and metabolic processes, and assessing therapeutic outcomes. To our best knowledge, our study is the first example to achieve CT imaging and microwave thermal therapy simultaneously through a simple nanostructure. We anticipate that the simple IL@ZrO2 nanostructure may build a useful platform for the clinical imaging guided therapy of tumors.

Ambient intelligence context-based cross-layer design in wireless sensor networks.

By exchanging information directly between non-adjacent protocol layers, cross-layer (CL) interaction can significantly improve and optimize network performances such as energy efficiency and delay. This is particularly important for wireless sensor networks (WSNs) where sensor devices are energy-constrained and deployed for real-time monitoring applications. Existing CL schemes mainly exploit information exchange between physical, medium access control (MAC), and routing layers, with only a handful involving application layer. For the first time, we proposed a framework for CL optimization based on user context of ambient intelligence (AmI) application and an ontology-based context modeling and reasoning mechanism. We applied the proposed framework to jointly optimize MAC and network (NET) layer protocols for WSNs. Extensive evaluations show that the resulting optimization through context awareness and CL interaction for both MAC and NET layer protocols can yield substantial improvements in terms of throughput, packet delivery, delay, and energy performances.

Wireless Sensing of Complex Dielectric Permittivity of Liquids Based on the RFID

A wireless sensing system for the evaluation of the complex dielectric permittivity of solvent liquids is presented. Two sensing tags are proposed for testing of the samples. The first tag is based on a cavity resonator and the second makes use of the epsilon-near-zero effect. Both circuits are designed over the planar substrate-integrated-waveguide (SIW) technology, and operate at 4 GHz. A quartz capillary tube is used for the liquid measurements where only a small amount of sample volume is required. With the addition of planar antennas at the input and output of the sensors, the complete system is implemented for wireless sensing of the materials following the RF identification scheme. The cavity perturbation technique for SIW structures is applied for the dielectric liquid characterization. The proposed sensing tags and system have high potentials for low-cost wireless measurements and real-time monitoring applications.

Facile fabrication of three-dimensional graphene foam/poly(dimethylsiloxane) composites and their potential application as strain sensor.

A three-dimensional (3D) graphene foam (GF)/poly(dimethylsiloxane) (PDMS) composite was fabricated by infiltrating PDMS into 3D GF, which was synthesized by chemical vapor deposition (CVD) with nickel foam as template. The electrical properties of the GF/PDMS composite under bending stress were investigated, indicating the resistance of the GF/PDMS composite was increased with the bending curvature. To improve the bending sensitivity of the GF/PDMS composite, a thin layer of poly(ethylene terephthalate) (PET) was introduced as substrate to form double-layer GF/PDMS-PET composite, whose measurements showed that the resistance of the GF/PDMS-PET composite was still increased when bended to the side of PET, whereas its resistance would be decreased when bended to the side of GF. For both cases, the absolute value of the relative variation of electrical resistance was increased with the bending curvature. More importantly, the relative variation of electrical resistance for double-layer GF/PDMS-PET composite can be up to six times higher than single-layer GF/PDMS composite for the same bending curvature. These observations were further supported by the principle of mechanics of material. The 3D GF/PDMS-PET composite also has higher flexibility and environment stability and can be utilized as a strain sensor with high sensitivity, which can find important applications in real-time monitoring of buildings, such as a bridge, dam, and high-speed railway.

The potential applications of real-time monitoring of water quality in a large shallow lake (Lake Taihu, China) using a chromophoric dissolved organic matter fluorescence sensor.

This study presents results from field surveys performed over various seasons in a large, eutrophic, shallow lake (Lake Taihu, China) using an in situ chromophoric dissolved organic matter (CDOM) fluorescence sensor as a surrogate for other water quality parameters. These measurements identified highly significant empirical relationships between CDOM concentration measured using the in situ fluorescence sensor and CDOM absorption, fluorescence, dissolved organic carbon (DOC), chemical oxygen demand (COD) and total phosphorus (TP) concentrations. CDOM concentration expressed in quinine sulfate equivalent units, was highly correlated with the CDOM absorption coefficient (r2 = 0.80, p < 0.001), fluorescence intensities (Ex./Em. 370/460 nm) (r2 = 0.91, p < 0.001), the fluorescence index (r2 = 0.88, p < 0.001) and the humification index (r2 = 0.78, p < 0.001), suggesting that CDOM concentration measured using the in situ fluorescence sensor could act as a substitute for the CDOM absorption coefficient and fluorescence measured in the laboratory. Similarly, CDOM concentration was highly correlated with DOC concentration (r2 = 0.68, p < 0.001), indicating that in situ CDOM fluorescence sensor measurements could be a proxy for DOC concentration. In addition, significant positive correlations were found between laboratory CDOM absorption coefficients and COD (r2 = 0.83, p < 0.001), TP (r2 = 0.82, p < 0.001) concentrations, suggesting a potential further application for the real-time monitoring of water quality using an in situ CDOM fluorescence sensor.

Simplified Mathematical Model for Calculating the Oxygen Excess Ratio of a PEM Fuel Cell System in Real-Time Applications

The oxygen starvation phenomenon is a dangerous operating condition that reduces the lifetime of PEM fuel cells. The detection and prevention of this undesired phenomenon require estimation of the oxygen excess ratio λO2. The mathematical complexities of the reported methods for obtaining λO2 complicate its real-time calculation and require high-performance computational devices, which significantly increase the costs of the system. In this paper, a mutual information approach is used in obtaining a simplified mathematical model for the calculation of λO2. The usage of such a simplified model requires much less computational power for real-time monitoring of the variable λO2, while it provides comparable results to those obtained by using the complex model. Therefore, it represents a cost-effective solution, suitable for usage within applications that require high sampling frequencies, like emulators, converter and air compressor control loops, simulations, etc. In order to validate the accuracy of this simplified λO2 calculation model, a real-time monitoring system was built and experimentally tested using both the simplified and complex models. The matching experimental results validate the proposed simplification and justify the use of this simplified model within real-time monitoring applications.