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With characters of low cost, portability, easy disposal, and high accuracy, as well as bulky reduced laboratory equipment, paper-based sensors are getting increasing attention for reliable indoor/outdoor onsite detection with nonexpert operation. They have become powerful analysis tools in trace detection with ultra-low detection limits and extremely high accuracy, resulting in their great popularity in medical detection, environmental inspection, and other applications. Herein, we summarize and generalize the recently reported paper-based sensors based on their application for mechanics, biomolecules, food safety, and environmental inspection. Based on the biological, physical, and chemical analytes-sensitive electrical or optical signals, extensive detections of a large number of factors such as humidity, pressure, nucleic acid, protein, sugar, biomarkers, metal ions, and organic/inorganic chemical substances have been reported via paper-based sensors. Challenges faced by the current paper-based sensors from the fundamental problems and practical applications are subsequently analyzed; thus, the future directions of paper-based sensors are specified for their rapid handheld testing.

A colorimetric polydiacetylene (PDA) paper strip sensor that can specifically recognize Bacillus thuringiensis (BT) HD-73 spores is described in this work. The target-specific aptamer was combined with PDA, and the aptamer-conjugated PDA vesicles were then coated on polyvinylidene fluoride (PVDF) paper strips by a simple solvent evaporation method. The PDA-aptamer paper strips can be used to detect the target without any pre-treatment. Using the paper strip, the presence of BT spores is directly observable by the naked eye based on the unique blue-to-red color transition of the PDA. Quantitative studies using the paper strip were also carried out by analyzing the color transitions of the PDA. The specificity of this PDA sensor was verified with a high concentration of Escherichia coli, and no discernable change was observed. The observable color change in the paper strip occurs in less than 1 h, and the limit of detection is 3 &times, 107 CFU/mL, much below the level harmful to humans. The PDA-based paper sensor, developed in this work, does not require a separate power or detection device, making the sensor strip highly transportable and suitable for spore analysis anytime and anywhere. Moreover, this paper sensor platform is easily fabricated, can be adapted to other targets, is highly portable, and is highly specific for the detection of BT spores.

Humidity sensors are indispensable for various electronic systems and instrumentations. To develop a new humidity sensing mechanism is the key for the next generation of sensor technology. In this work, a novel flexible paper-based current humidity sensor is proposed. The developed alternating current electroluminescent devices (ACEL) consist of the electroless plating Ni on filter paper and silver nanowires (AgNWs) as the bottom and upper electrodes, and ZnS:Cu as the phosphor layer, respectively. The proposed humidity sensor is based on ACEL with the paper substrate and the ZnS:Cu phosphor layer as the humidity sensing element. The moisture effect on the optical properties of ACELs has been studied firstly. Then, the processing parameters of the paper-based ACELs such as electroless plated bottom electrode and spin-coated phosphor layer as a function of the humidity-sensitive characteristics are investigated. The sensing mechanism of the proposed sensor has been elucidated based on the Q ~ V analysis. The sensor exhibits an excellent linearity ( R 2 = 0.99965 ) within the humidity range from 20% to 90% relative humidity (RH) and shows excellent flexibility. We also demonstrate its potential application in postharvest preservation where the EL light is used for preservation and the humidity can be monitored simultaneously through the current.

We present a rotational terahertz imaging system for inline nondestructive testing (NDT) of press sleeves for the paper industry during fabrication. Press sleeves often consist of polyurethane (PU) which is deposited by rotational molding on metal barrels and its outer surface mechanically processed in several milling steps afterwards. Due to a stabilizing polyester fiber mesh inlay, small defects can form on the sleeve’s backside already during the initial molding, however, they cannot be visually inspected until the whole production processes is completed. We have developed a fast-scanning frequenc-modulated continuous wave (FMCW) terahertz imaging system, which can be integrated into the manufacturing process to yield high resolution images of the press sleeves and therefore can help to visualize hidden structural defects at an early stage of fabrication. This can save valuable time and resources during the production process. Our terahertz system can record images at 0.3 and 0.5 THz and we achieve data acquisition rates of at least 20 kHz, exploiting the fast rotational speed of the barrels during production to yield sub-millimeter image resolution. The potential of automated defect recognition by a simple machine learning approach for anomaly detection is also demonstrated and discussed.

A flexible pressure sensor with a rudimentary, ultra-low cost, and solvent-free fabrication process is presented in this paper. The sensor has a graphite-on-paper stacked paper structure, which deforms and restores its shape when pressure is applied and released, showing an exceptionally fast response and relaxation time of &asymp, 0.4 ms with a sensitivity of &minus, 5%/Pa. Repeatability of the sensor over 1000 cycles indicates an excellent long-term stability. The sensor demonstrated fast and reliable human touch interface, and successfully integrated into a robot gripper to detect grasping forces, showing high promise for use in robotics, human interface, and touch devices.

Food safety and access to systematic approaches for ensuring detection of food hazards is an important issue in most developing countries. With the arrival of paper-based analytical devices (&micro, PADs) as a promising, rapid, easy-to-use, and low-cost analytical tool, we demonstrated a simple microfluidic-based titration study for the analysis of packaged fruit juices. Similar, to the titration experiments using traditional glassware in chemistry laboratories, in this study the titration experiments were developed using paper microfluidics for the analysis of several analytes such as pH, vitamin C, sugars, and preservatives present in the packaged fruit juices. The allergen found commonly in dairy based mixtures and the non-pathogenic biochemical component responsible for food spoilage in cider based fruit juices were also determined. The results obtained using paper microfluidics were compared with those obtained using a conventional spectrophotometric technique. Finally, a paper microfluidics based multiplexed sensor was developed for the analysis of common nutritional ingredients, an allergen, and a non-pathogenic byproduct present in packaged fruit juices on a single platform. Overall, the results presented in this study reveal that the proposed paper microfluidic assisted colorimetric multiplexed sensor offers a quick and reliable tool for on-spot routine analysis for food safety applications.

Breath analysis is considered to be an effective method for point-of-care diagnosis due to its noninvasiveness, quickness and simplicity. Gas sensors for breath analysis require detection of low-concentration substances. In this paper, we propose that reduction of the background current improves the limit of detection of enzymatic biogas sensors utilizing chromatography paper. After clarifying the cause of the background current, we reduced the background current by improving the fabrication process of the sensors utilizing paper. Finally, we evaluated the limit of detection of the sensor with the sample vapor of ethanol gas. The experiment showed about a 50% reduction of the limit of detection compared to previously-reported sensor. This result presents the possibility of the sensor being applied in diagnosis, such as for diabetes, by further lowering the limit of detection.

The electrophoresis of ampholytes such as amino acids on a paper device is difficult because of the variation of pH distribution in time. On the basis of this observation, we propose a paper-based analytical device (PAD) with origami structure. By folding a filter paper, a low operation voltage of 5 V was achieved, where the power was supplied by a 5 V 1.5 A portable power bank through the USB type A receptacle. As a demonstration, we carried out the electrophoretic separation of pI markers (pI 5.5 and 8.7). The separation was achieved within 4 min before the pH distribution on the paper varied. Though the separation distance was small, it could be increased by expanding the origami structure. This result indicates that our proposed PAD is useful for electrophoretic separation on a paper device.

This paper demonstrates the performance of a potential design of a paper substrate-based flexible antenna for intrabody telemedicine systems in the 2.4 GHz industrial, scientific, and medical radio (ISM) bands. The antenna was fabricated using 0.54 mm thick flexible photo paper and 0.03 mm copper strips as radiating elements. Design and performance analyses of the antenna were performed using Computer Simulation Technology (CST) Microwave Studio software. The antenna performances were investigated based on the reflection coefficient in normal and bent conditions. The total dimensions of the proposed antenna are 40 &times, 35 &times, 0.6 mm3. The antenna operates at 2.33&ndash, 2.53 GHz in the normal condition. More than an 8% fractional bandwidth is expressed by the antenna. Computational analysis was performed at different flexible curvatures by bending the antenna. The minimum fractional bandwidth deviation is 5.04% and the maximum is 24.97%. Moreover, it was mounted on a homogeneous phantom muscle and a four-layer human tissue phantom. Up to a 70% radiation efficiency with a 2 dB gain was achieved by the antenna. Finally, the performance of the antenna with a homogeneous phantom muscle was measured and found reliable for wearable telemedicine applications.

An inkjet-printed, fully passive sensor capable of either humidity or gas sensing is presented herein. The sensor is composed of an interdigitated electrode, a customized printable gas sensitive ink and a specialized dipole antenna for wireless sensing. The interdigitated electrode printed on a paper substrate provides the base conductivity that varies during the sensing process. Aided by the porous nature of the substrate, a change in relative humidity from 18% to 88% decreases the electrode resistance from a few Mega-ohms to the kilo-ohm range. For gas sensing, an additional copper acetate-based customized ink is printed on top of the electrode, which, upon reaction with hydrogen sulphide gas (H2S) changes, both the optical and the electrical properties of the electrode. A fast response time of 3 min is achieved at room temperature for a H2S concentration of 10 ppm at a relative humidity (RH) of 45%. The passive wireless sensing is enabled through an antenna in which the inner loop takes care of conductivity changes in the 4–5 GHz band, whereas the outer-dipole arm is used for chipless identification in the 2–3 GHz band.

Timely evaluation and reperfusion have improved the myocardial salvage and the subsequent recovery rate of the patients hospitalized with acute myocardial infarction (MI). Long waiting time and time-consuming procedures of in-hospital diagnostic testing severely affect the timeliness. We present a Poincare pattern ensemble-based method with the consideration of multi-correlated non-stationary stochastic system dynamics to localize the infarct-related artery (IRA) in acute MI by fully harnessing information from paper-based Electrocardiogram (ECG). The vectorcardiogram (VCG) diagnostic features extracted from only 2.5-s long paper ECG recordings were used to hierarchically localize the IRA&mdash, not mere localization of the infarcted cardiac tissues&mdash, in acute MI. Paper ECG records and angiograms of 106 acute MI patients collected at the Heart Artery and Vein Center at Fresno California and the 12-lead ECG signals from the Physionet PTB online database were employed to validate the proposed approach. We reported the overall accuracies of 97.41% for healthy control (HC) vs. MI, 89.41 &plusmn, 9.89 for left and right culprit arteries vs. others, 88.2 &plusmn, 11.6 for left main arteries vs. right-coronary-ascending (RCA) and 93.67 &plusmn, 4.89 for left-anterior-descending (LAD) vs. left-circumflex (LCX). The IRA localization from paper ECG can be used to timely triage the patients with acute coronary syndromes to the percutaneous coronary intervention facilities.

Paper-based sensors are a new alternative technology for fabricating simple, low-cost, portable and disposable analytical devices for many application areas including clinical diagnosis, food quality control and environmental monitoring. The unique properties of paper which allow passive liquid transport and compatibility with chemicals/biochemicals are the main advantages of using paper as a sensing platform. Depending on the main goal to be achieved in paper-based sensors, the fabrication methods and the analysis techniques can be tuned to fulfill the needs of the end-user. Current paper-based sensors are focused on microfluidic delivery of solution to the detection site whereas more advanced designs involve complex 3-D geometries based on the same microfluidic principles. Although paper-based sensors are very promising, they still suffer from certain limitations such as accuracy and sensitivity. However, it is anticipated that in the future, with advances in fabrication and analytical techniques, that there will be more new and innovative developments in paper-based sensors. These sensors could better meet the current objectives of a viable low-cost and portable device in addition to offering high sensitivity and selectivity, and multiple analyte discrimination. This paper is a review of recent advances in paper-based sensors and covers the following topics: existing fabrication techniques, analytical methods and application areas. Finally, the present challenges and future outlooks are discussed.

We demonstrate novel graphite-on-paper piezoresistive devices. The graphite was used as sensing component. The fabrication process can be finished in a short time with simple tools (e.g., a scissor and a pencil). A small array of six paper-based piezoresistive devices is made. The whole device is flexible. The test results showed that the change of resistance was proportional to the applied force. A paper-based weighing balance was also made as an example of applications. This novel array of paper-based piezoresistive devices will open wide applications in force and acceleration sensing areas.

Traditional diagnostic tests for chronic diseases are expensive and require a specialized laboratory, therefore limiting their use for point-of-care (PoC) testing. To address this gap, we developed a method for rapid and low-cost C-reactive protein (CRP) detection from blood by integrating a paper-based microfluidic immunoassay with a smartphone (CRP-Chip). We chose CRP for this initial development because it is a strong biomarker of prognosis in chronic heart and kidney disease. The microfluidic immunoassay is realized by lateral flow and gold nanoparticle-based colorimetric detection of the target protein. The test image signal is acquired and analyzed using a commercial smartphone with an attached microlens and a 3D-printed chip–phone interface. The CRP-Chip was validated for detecting CRP in blood samples from chronic kidney disease patients and healthy subjects. The linear detection range of the CRP-Chip is up to 2 μg/mL and the detection limit is 54 ng/mL. The CRP-Chip test result yields high reproducibility and is consistent with the standard ELISA kit. A single CRP-Chip can perform the test in triplicate on a single chip within 15 min for less than 50 US cents of material cost. This CRP-Chip with attractive features of low-cost, fast test speed, and integrated easy operation with smartphones has the potential to enable future clinical PoC chronic disease diagnosis and risk stratification by parallel measurements of a panel of protein biomarkers.

Since 2011, an annual award system was instituted to recognize outstanding Sensors papers that are related to sensing technologies and applications and meet the aims, scope and high standards of this journal [1–4]. This year, the winners were chosen by the Section Editor-in-Chiefs of Sensors from among all the papers published in 2011 to track citations. Reviews and full research articles were considered separately. We gladly announce that the following eight papers were awarded the Sensors Best Paper Award in 2015.[...]

A fiber optic interferometric sensor with an intrinsic transducer along a length of the fiber is presented for ultrasound measurements of the acoustic emission from partial discharges inside oil-filled power apparatus. The sensor is designed for high sensitivity measurements in a harsh electromagnetic field environment, with wide temperature changes and immersion in oil. It allows enough sensitivity for the application, for which the acoustic pressure is in the range of units of Pa at a frequency of 150 kHz. In addition, the accessibility to the sensing region is guaranteed by immune fiber-optic cables and the optical phase sensor output. The sensor design is a compact and rugged coil of fiber. In addition to a complete calibration, the in-situ results show that two types of partial discharges are measured through their acoustic emissions with the sensor immersed in oil.

With the start of 2011, Sensors is instituting an annual award to recognize outstanding papers related to sensing technologies and applications that meet the aims, scope and high standards of this journal. We are pleased to announce the first “Sensors Best Paper Award” for 2011. Nominations were solicited from the Section Editor-in-Chiefs of Sensors, with all papers published in 2005 eligible for consideration. [...]

Phenolic compounds are particularly dangerous due to their ability to remain in the environment for a long period of time and their toxic effects. They enter in the environment in different ways, such as waste from paper manufacturing, agriculture (pesticides, insecticides, herbicides), pharmaceuticals, the petrochemical industry, and coal processing. Conventional methods for phenolic compounds detection present some disadvantages, such as cumbersome sample preparation, complex and time-consuming procedures, and need of expensive equipment. Therefore, there is a very large interest in developing sensors and new sensing schemes for fast and easy-to-use methods for detecting and monitoring the phenolic compound concentration in the environment, with special attention to water. Good analytical properties, reliability, and adaptability are required for the developed sensors. The present paper aims at revising the most generally used optical methods for designing and fabricating biosensors and sensors for phenolic compounds. Some selected examples of the most interesting applications of these techniques are also proposed.

This paper presents a feasibility study for a non-wearable, conformal, low cost, and disposable antenna-based sensor for non-invasive hydration monitoring using sweat. It is composed of a patch antenna implemented on a cellulose filter paper substrate and operating in the range 2&ndash, 4 GHz. The paper substrate can absorb liquids, such as sweat on the skin, through two slots incorporated within the antenna structure. Thus, the substrate dielectric properties are altered according to the properties of the absorbed liquid. Changes in reflection-based measurements are used to analyze salt solutions and artificial sweat, specifically the amount of sampled solution and the sodium chloride (NaCl) concentration. Using the shift in resonant frequency and magnitude of the reflection coefficient, NaCl concentrations in the range of 8.5&ndash, 200 mmol/L, representing different hydration states, are detected. The measurements demonstrate the feasibility of using microwave based measurements for hydration monitoring using sweat.

Falls are unusual actions that cause a significant health risk among older people. The growing percentage of people of old age requires urgent development of fall detection and prevention systems. The emerging technology focuses on developing such systems to improve quality of life, especially for the elderly. A fall prevention system tries to predict and reduce the risk of falls. In contrast, a fall detection system observes the fall and generates a help notification to minimize the consequences of falls. A plethora of technical and review papers exist in the literature with a primary focus on fall detection. Similarly, several studies are relatively old, with a focus on wearables only, and use statistical and threshold-based approaches with a high false alarm rate. Therefore, this paper presents the latest research trends in fall detection and prevention systems using Machine Learning (ML) algorithms. It uses recent studies and analyzes datasets, age groups, ML algorithms, sensors, and location. Additionally, it provides a detailed discussion of the current trends of fall detection and prevention systems with possible future directions. This overview can help researchers understand the current systems and propose new methodologies by improving the highlighted issues. ispartof: SENSORS vol:21 issue:15 ispartof: location:Switzerland status: published

This paper is a survey of existing and upcoming industrial applications of terahertz technologies, comprising sections on polymers, paint and coatings, pharmaceuticals, electronics, petrochemicals, gas sensing, and paper and wood industries. Finally, an estimate of the market size and growth rates is given, as obtained from a comparison of market reports.

In this paper, we present WaterSpy, a project developing an innovative, compact, cost-effective photonic device for pervasive water quality sensing, operating in the mid-IR spectral range. The approach combines the use of advanced Quantum Cascade Lasers (QCLs) employing the Vernier effect, used as light source, with novel, fibre-coupled, fast and sensitive Higher Operation Temperature (HOT) photodetectors, used as sensors. These will be complemented by optimised laser driving and detector electronics, laser modulation and signal conditioning technologies. The paper presents the WaterSpy concept, the requirements elicited, the preliminary architecture design of the device, the use cases in which it will be validated, while highlighting the innovative technologies that contribute to the advancement of the current state of the art.

The large-scale cultivation of microalgae provides a wide spectrum of marketable bioproducts, profitably used in many fields, from the preparation of functional health products and feed supplement in aquaculture and animal husbandry to biofuels and green chemistry agents. The commercially successful algal biomass production requires effective strategies to maintain the process at desired productivity and stability levels. Hence, the development of effective early warning methods to timely indicate remedial actions and to undertake countermeasures is extremely important to avoid culture collapse and consequent economic losses. With the aim to develop an early warning method of algal contamination, the potentiometric E-tongue was applied to record the variations in the culture environments, over the whole growth process, of two unialgal cultures, Phaeodactylum tricornutum and a microalgal contaminant, along with those of their mixed culture. The E-tongue system ability to distinguish the cultures and to predict their growth stage, through the application of multivariate data analysis, was shown. A PLS regression method applied to the E-tongue output data allowed a good prediction of culture growth time, expressed as growth days, with R2 values in a range from 0.913 to 0.960 and RMSEP of 1.97–2.38 days. Moreover, the SIMCA and PLS-DA techniques were useful for cultures contamination monitoring. The constructed PLS-DA model properly discriminated 67% of cultures through the analysis of their growth media, i.e., environments, thus proving the potential of the E-tongue system for a real time monitoring of contamination in microalgal intensive cultivation.

The increasing demand for smart vehicles with many sensing capabilities will escalate data traffic in vehicular networks. Meanwhile, available network resources are limited. The emergence of AI implementation in vehicular network resource allocation opens the opportunity to improve resource utilization to provide more reliable services. Accordingly, many resource allocation schemes with various machine learning algorithms have been proposed to dynamically manage and allocate network resources. This survey paper presents how machine learning is leveraged in the vehicular network resource allocation strategy. We focus our study on determining its role in the mechanism. First, we provide an analysis of how authors designed their scenarios to orchestrate the resource allocation strategy. Secondly, we classify the mechanisms based on the parameters they chose when designing the algorithms. Finally, we analyze the challenges in designing a resource allocation strategy in vehicular networks using machine learning. Therefore, a thorough understanding of how machine learning algorithms are utilized to offer a dynamic resource allocation in vehicular networks is provided in this study.

In this paper, we propose a paper-based pattern switchable antenna system using inkjet-printing technology for bi-direction sensor applications. The proposed antenna system is composed of two directional bow-tie antennas and a switching network. The switching network consists of a single-pole-double-throw (SPDT) switch and a balun element. A double-sided parallel-strip line (DSPSL) is employed to convert the unbalanced microstrip mode to the balanced strip mode. Two directional bow-tie antennas have different radiation patterns because of the different orientation of the reflectors and antennas. It is demonstrated from electromagnetic (EM) simulation and measurement that the radiation patterns of the proposed antenna are successfully switched by the SPDT switch.

Laser-induced breakdown spectroscopy (LIBS) was tested for all of the relevant issues in forensic examinations of commercial inks, including classification of pen inks on one paper type and on different paper types, determination of the deposition order of layered inks, and analysis of signatures and toners on one questioned document. The scope of this work was to determine the potential of a single LIBS setup that is compatible with portable instruments for different types of ink analysis, rather than building a very large database for inks and papers. We identified up to seven metals characteristic for the examined inks, which allowed to fully discriminate all eight black inks on one type of printing paper. When the inks were tested on ten different papers, the correct classification rates for some of them were reduced for reasons thoroughly studied and explained. The replicated tests on three crossing points, each one involving a pair of blue or black inks, were successful in five cases out of six. In the test simulating documents of forensic interest (questioned documents), LIBS was able to correctly identify the differences in three inks used for signatures on one of the three pages and the use of different printing inks on each page of the document.

In the first hours of a disaster, up-to-date information about the area of interest is crucial for effective disaster management. However, due to the delay induced by collecting and analysing satellite imagery, disaster management systems like the Copernicus Emergency Management Service (EMS) are currently not able to provide information products until up to 4872 h after a disaster event has occurred. While satellite imagery is still a valuable source for disaster management, information products can be improved through complementing them with user-generated data like social media posts or crowdsourced data. The advantage of these new kinds of data is that they are continuously produced in a timely fashion because users actively participate throughout an event and share related information. The research project Evolution of Emergency Copernicus services (E2mC) aims to integrate these novel data into a new EMS service component called Witness, which is presented in this paper. Like this, the timeliness and accuracy of geospatial information products provided to civil protection authorities can be improved through leveraging user-generated data. This paper sketches the developed system architecture, describes applicable scenarios and presents several preliminary case studies, providing evidence that the scientific and operational goals have been achieved. (VLID)2350401

The existing LTE mobile system uses the vertical model to handle the session-based security management. However, the goal of this paper is to propose a packet key-based security management scheme on the blockchain control plane to enhance the existing session key-based security scheme and overcome the limitation that the existing vertical model, as well as the Software-Defined Networking (SDN) based horizontal model, confronts within solving end-to-end security management. The proposed blockchain-based security management (BSM) scheme enables each peer to easily obtain the necessary parameters required to manage the packet key-based security system. The important features of the BSM scheme include the renewal process, which enables the different packet data streams to use completely different security parameters for the security management. In addition, because even blind values cannot be exposed to the possible attackers, our BSM scheme guarantees very secure end-to-end data transfer against active attacks such as falsification of data and transactions. Finally, this paper compares the BSM scheme with the existing vertical model to prove the advantageous effects on latency.

Traditional techniques of active thermography require an external source of energy used for excitation, usually in the form of high power lamps or ultrasonic devices. In this paper, the author presents an alternative approach based on the self-heating effect observable in polymer-based structures during cyclic loading. The presented approach is based on, firstly, determination of bending resonance frequencies of a tested structure, and then, on excitation of a structure with a multi-harmonic signal constructed from the harmonics with frequencies of determined resonances. Following this, heating-up of a tested structure occurs in the location of stress concentration and mechanical energy dissipation due to the viscoelastic response of a structure. By applying multi-harmonic signal, one ensures coverage of the structure by such heated regions. The concept is verified experimentally on artificially damaged composite specimens. The results demonstrate the presented approach and indicate its potential, especially when traditional methods of excitation with an external structure for thermographic inspection cannot be applied.

This paper presents a miniaturized Doppler radar that can be used as a motion sensor for low-cost Internet of things (IoT) applications. For the first time, a radar front-end and its antenna are integrated on a multilayer cellulose-based substrate, built-up by alternating paper, glue and metal layers. The circuit exploits a distributed microstrip structure that is realized using a copper adhesive laminate, so as to obtain a low-loss conductor. The radar operates at 24 GHz and transmits 5 mW of power. The antenna has a gain of 7.4 dBi and features a half power beam-width of 48 degrees. The sensor, that is just the size of a stamp, is able to detect the movement of a walking person up to 10 m in distance, while a minimum speed of 50 mm/s up to 3 m is clearly measured. Beyond this specific result, the present paper demonstrates that the attractive features of cellulose, including ultra-low cost and eco-friendliness (i.e., recyclability and biodegradability), can even be exploited for the realization of future high-frequency hardware. This opens opens the door to the implementation on cellulose of devices and systems which make up the “sensing layer” at the base of the IoT ecosystem.

Food safety issues have recently attracted public concern. The deleterious effects of compromised food safety on health have rendered food safety analysis an approach of paramount importance. While conventional techniques such as high-performance liquid chromatography and mass spectrometry have traditionally been utilized for the detection of food contaminants, they are relatively expensive, time-consuming and labor intensive, impeding their use for point-of-care (POC) applications. In addition, accessibility of these tests is limited in developing countries where food-related illnesses are prevalent. There is, therefore, an urgent need to develop simple and robust diagnostic POC devices. POC devices, including paper- and chip-based devices, are typically rapid, cost-effective and user-friendly, offering a tremendous potential for rapid food safety analysis at POC settings. Herein, we discuss the most recent advances in the development of emerging POC devices for food safety analysis. We first provide an overview of common food safety issues and the existing techniques for detecting food contaminants such as foodborne pathogens, chemicals, allergens, and toxins. The importance of rapid food safety analysis along with the beneficial use of miniaturized POC devices are subsequently reviewed. Finally, the existing challenges and future perspectives of developing the miniaturized POC devices for food safety monitoring are briefly discussed.

This paper presents the integration of an inductor by complementary metal-oxide-semiconductor (CMOS) compatible processes for integrated smart microsensor systems that have been developed to monitor the motion and vital signs of humans in various environments. Integration of radio frequency transmitter (RF) technology with complementary metal-oxide-semiconductor/micro electro mechanical systems (CMOS/MEMS) microsensors is required to realize the wireless smart microsensors system. The essential RF components such as a voltage controlled RF-CMOS oscillator (VCO), spiral inductors for an LC resonator and an integrated antenna have been fabricated and evaluated experimentally. The fabricated RF transmitter and integrated antenna were packaged with subminiature series A (SMA) connectors, respectively. For the impedance (50 Ω) matching, a bonding wire type inductor was developed. In this paper, the design and fabrication of the bonding wire inductor for impedance matching is described. Integrated techniques for the RF transmitter by CMOS compatible processes have been successfully developed. After matching by inserting the bonding wire inductor between the on-chip integrated antenna and the VCO output, the measured emission power at distance of 5 m from RF transmitter was -37 dBm (0.2 μW).

Graphene-based composites have gained great attention in the field of gas sensor fabrication due to their higher surface area with additional functional groups. Decorating one-dimensional (1D) semiconductor nanomaterials on graphene also show potential benefits in gas sensing applications. Here we demonstrate the one-pot and low cost synthesis of W18O49 NWs/rGO composites with different amount of reduced graphene oxide (rGO) which show excellent gas-sensing properties towards toluene and strong dependence on their chemical composition. As compared to pure W18O49 NWs, an improved gas sensing response (2.8 times higher) was achieved in case of W18O49 NWs composite with 0.5 wt. % rGO. Promisingly, this strategy can be extended to prepare other nanowire based composites with excellent gas-sensing performance.

Inkjet printing is an advanced printing technology that has been used to develop conducting layers, interconnects and other features on a variety of substrates. It is an additive manufacturing process that offers cost-effective, lightweight designs and simplifies the fabrication process with little effort. There is hardly sufficient research on tactile sensors and inkjet printing. Advancements in materials science and inkjet printing greatly facilitate the realization of sophisticated tactile sensors. Starting from the concept of capacitive sensing, a brief comparison of printing techniques, the essential requirements of inkjet-printing and the attractive features of state-of-the art inkjet-printed tactile sensors developed on diverse substrates (paper, polymer, glass and textile) are presented in this comprehensive review. Recent trends in inkjet-printed wearable/flexible and foldable tactile sensors are evaluated, paving the way for future research.

This paper discusses a novel dynamic resonant wall shear stress sensor concept based on an oscillating sensor operating near resonance. The interaction between the oscillating sensor surface and the fluid above it is modelled using the unsteady laminar boundary layer equations. The numerical experiment shows that the effect of the oscillating shear stress is well correlated by the Hummer number, the ratio of the steady shear force caused by the outside flow to the oscillating viscous force created by the sensor motion. The oscillating shear stress predicted by the fluid model is used in a mechanical model of the sensor to predict the sensor’s dynamic motion. Static calibration curves for amplitude and frequency influences are predicted. These results agree with experimental results on some extent, and shows some expectation for further development of the dynamic resonant sensor concept.

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately.

Due to the wide potential applications of wireless sensor networks, this topic has attracted great attention. The strict energy constraints of sensor nodes result in great challenges for energy efficiency. This paper proposes an energy-efficient organization method. The organization of wireless sensor networks is formulated for target tracking. Target localization is achieved by collaborative sensing with multi-sensor fusion. The historical localization results are utilized for adaptive target trajectory forecasting. Combining autoregressive moving average (ARMA) model and radial basis function networks (RBFNs), robust target position forecasting is performed. Moreover, an energy-efficient organization method is presented to enhance the energy efficiency of wireless sensor networks. The sensor nodes implement sensing tasks are awakened in a distributed manner. When the sensor nodes transfer their observations to achieve data fusion, the routing scheme is obtained by ant colony optimization. Thus, both the operation and communication energy consumption can be minimized. Experimental results verify that the combination of ARMA model and RBFN can estimate the target position efficiently and energy saving is achieved by the proposed organization method in wireless sensor networks.

This paper reports a micromachined capacitive pressure sensor intended for applications that require mechanical robustness. The device is constructed with two micromachined metal plates and an intermediate polymer layer that is soft enough to deform in a target pressure range. The plates are formed of micromachined stainless steel fabricated by batch-compatible micro-electro-discharge machining. A polyurethane roomtemperature- vulcanizing liquid rubber of 38-μm thickness is used as the deformable material. This structure eliminates both the vacuum cavity and the associated lead transfer challenges common to micromachined capacitive pressure sensors. For frequency-based interrogation of the capacitance, passive inductor-capacitor tanks are fabricated by combining the capacitive sensor with an inductive coil. The coil has 40 turns of a 127-μmdiameter copper wire. Wireless sensing is demonstrated in liquid by monitoring the variation in the resonant frequency of the tank via an external coil that is magnetically coupled with the tank. The sensitivity at room temperature is measured to be 23-33 ppm/KPa over a dynamic range of 340 KPa, which is shown to match a theoretical estimation. Temperature dependence of the tank is experimentally evaluated.

The purpose of this paper is to examine the linkage between rapid urbanization and flood risk in the hinterlands of the Pearl River Delta, P.R. China. Foshan, a typical hinterland city in the Pearl River Delta region, was selected as a case study. Land use and cover change in Foshan during 1988-2003 was analyzed using remote sensing and geographic information system (GIS) techniques. Furthermore, analysis on historical hydrological data during 1962-2005 was performed. Results show that rapid urbanization has resulted in losses of farmland, forest and shrub since 1988. In addition, in order to compensate or offset the loss of farmland due to rapid urban expansion, more than 30 % of the forest and 20 % of the shrub areas were transformed into farmlands. Inevitably, both the urban and agricultural lands increased the pressure on the drainage systems. Furthermore, over the past decades human activities such as dredging up the floodways, excavating sand and building water facilities in the rivers, significantly changed the hydrological conditions, and therefore impaired the rivers’ capacity to buffer floods. Lessons from the Foshan case implied that, in addition to natural processes, human activities driven by socio-economic factors should be considered responsible for the recently increasing level of flood risks. Both economically and environmentally, it is irrational and impractical to encourage encroachment of lands vulnerable to floods. It is also realistic and urgent to effectively prevent and control the adverse ecological consequences of urbanization and economic activities for building their wealth and prominence.

Steel corrosion resulting from the penetration of chloride ions or carbon dioxide is a major cause of degradation for reinforced concrete structures,. The objective of the present investigation was to develop a low-cost sensor for steel corrosion, which is based on a very simple physical principle. The flat end of a cut optical fiber is coated with an iron thin film using the ion sputtering technique. Light is then sent into a fiber embedded in concrete and the reflected signal is monitored. Initially, most of the light is reflected by the iron layer. When corrosion occurs to remove the iron layer, a significant portion of the light power will leave the fiber at its exposed end, and the reflected power is greatly reduced. Monitoring of the reflected signal is hence an effective way to assess if the concrete environment at the location of the fiber tip may induce steel corrosion or not. In this paper, first the principle of the corrosion sensor and its fabrication are described. The sensing principle is then verified by experimental results. Sensor packaging for practical installation will be presented and the performance of the packaged sensors is assessed by additional experiments.

The paper describes a new PC and LabVIEW software package based system for electrochemical research. An overview of well known electrochemical methods, such as potential measurements, galvanostatic and potentiostatic method, cyclic voltammetry and EIS is given. Electrochemical impedance spectroscopy has been adapted for systems containing large capacitances. For signal generation and recording of the response of investigated electrochemical cell, a measurement and control system was developed, based on a PC P4. The rest of the hardware consists of a commercially available AD-DA converter and an external interface for analog signal processing. The interface is a result of authors own research. The software platform for desired measurement methods is LabVIEW 8.2 package, which is regarded as a high standard in the area of modern virtual instruments. The developed system was adjusted, tested and compared with commercially available system and ORCAD simulation.

This paper describes artificial neural network ( ANN) based prediction of the response of a fiber optic sensor using evanescent field absorption (EFA). The sensing probe of the sensor is made up a bundle of five PCS fibers to maximize the interaction of evanescent field with the absorbing medium. Different backpropagation algorithms are used to train the multilayer perceptron ANN. The Levenberg-Marquardt algorithm, as well as the other algorithms used in this work successfully predicts the sensor responses.

This paper is concerned with the networked estimation problem in which sensor data are transmitted over the network. In the event-driven sampling scheme known as level-crossing or send-on-delta, sensor data are transmitted to the estimator node if the difference between the current sensor value and the last transmitted one is greater than a given threshold. The event-driven sampling generally requires less transmission than the time-driven one. However, the transmission rate of the send-on-delta method becomes large when the sensor noise is large since sensor data variation becomes large due to the sensor noise. Motivated by this issue, we propose another event-driven sampling method called area-triggered in which sensor data are sent only when the integral of differences between the current sensor value and the last transmitted one is greater than a given threshold. Through theoretical analysis and simulation results, we show that in the certain cases the proposed method not only reduces data transmission rate but also improves estimation performance in comparison with the conventional event-driven method.

Range and velocity estimation of moving targets using conventional stepped-frequency pulse radar may suffer from the range-Doppler coupling and the phase wrapping. To overcome these problems, this paper presents a new radar waveform named multiple stepped-frequency pulse trains and proposes a new algorithm. It is shown that by using multiple stepped-frequency pulse trains and the robust phase unwrapping theorem (RPUT), both of the range-Doppler coupling and the phase wrapping can be robustly resolved, and accordingly, the range and the velocity of a moving target can be accurately estimated.

Image fusion is a useful tool in integrating a high-resolution panchromatic image (HRPI) with a low-resolution multispectral image (LRMI) to produce a high-resolution multispectral image (HRMI). To date, many image fusion techniques have been developed to try to improve the spatial resolution of the LRMI to that of the HRPI with its spectral property reliably preserved. However, many studies have indicated that there exists a trade- off between the spatial resolution improvement and the spectral property preservation of the LRMI, and it is difficult for the existing methods to do the best in both aspects. Based on one minimization problem, this paper mathematically analyzes the tradeoff in fusing remote sensing images. In experiment, four fusion methods are evaluated through expanded spectral angle mapper (ESAM). Results clearly prove that all the tested methods have this property.

The paper addresses the problem of the mean access delay characteristics in term of the channel load for networked sensor/control systems in LonWorks/EIA-709 technology. The system modelling is focused on the Media Access Control protocol that provides the load prediction and determines the key network characteristics. The network model assumes the consistency of load prediction between the nodes, and that the Transaction Control Sublayer does not introduce limitations on the data transmission. The latter means that the numbers of concurrent outgoing transactions being in progress are unlimited. Furthermore, it is assumed that the destination addresses of transmitted messages are distributed rather than concentrated on particular nodes. The analytical approach based on Markov chains is applied. The calculation of transition probabilities of the Markov chain is exemplified by the load scenario where all the transactions are acknowledged, unicast, and the optional collision detection is enabled. On the basis of the stochastic analysis, the probabilities of a successful transmission and collision, respectively, are computed. Furthermore, the numerical results of the mean access delay are reported. The simulative validation of analytical results is provided.

This paper presents a novel, non-invasive, non-contact system to measure pulse waveforms of artery via applying laser triangulation method to detect skin surface vibration. The proposed arterial pulsation measurement (APM) system chiefly consists of a laser diode and a low cost complementary metal-oxide semiconductor (CMOS) image sensor. Laser triangulation and centroid method are combined with the Fast Fourier Transform (FFT) in this study. The shape and frequency of the arterial pulsation can be detected rapidly by using our APM system. The relative variation of the pulse at different measurement points near wrist joint is used as a prognostic guide in traditional Chinese medicine (TCM). An extensive series of experiments was conducted to evaluate the performance of the designed APM system. From experimental results, the pulse amplitude and frequency at the Chun point (related to the small intestine) of left hand showed an obvious increase after having food. In these cases, the peak to peak amplitudes and the frequencies of arterial pulsations range from 38 to 48 μm and from 1.27 to 1.35 Hz, respectively. The height of arterial pulsations on the area near wrist joint can be estimated with a resolution of better than 4 μm. This research demonstrates that applying a CMOS image sensor in designing a non-contact, portable, easy-to-use, low cost pulse measurement system is feasible. Also, the designed APM system is well suited for evaluating and pre-diagnosing the health of a human being in TCM clinical practice.

Recent advances in devices and applications of high-birefringence fiber loop mirror sensors are addressed. In optical sensing, these devices may be used as strain and temperature sensors, in a separate or in a simultaneous measurement. Other described applications include: refractive index measurement, optical filters for interrogate gratings structures and chemical etching control. The paper analyses and compares different types of high-birefringence fiber loop mirror sensors using conventional and microstructured optical fibers. Some configurations are presented for simultaneous measurement of physical parameters when combined with others optical devices, for example with a long period grating.

This paper presents comparative study of a new type of manometer called concentric tube bulb (C.T.B) manometer. Its performance of measuring differential height is studied against conventional U-shaped manometer. Pressure drops and mass flow rates are calculated by taking various systems comprising of different flow measuring devices such as orifice and venturimeters using both U- shaped and C.T.B manometers. Comparison between the physically measured values of differential pressure drops and mass flow rates with the calculated values based on theoretical equations is also made. Experiments are carried out using mercury and CCl4 in these manometers as sensing fluids. Water is used as flowing fluid for mass flow rate and pressure drop measurements, whereas in gauge pressure measurements air is used.

Wireless multimedia sensor networks (WMSN) have recently emerged as one of the most important technologies, driven by the powerful multimedia signal acquisition and processing abilities. Target classification is an important research issue addressed in WMSN, which has strict requirement in robustness, quickness and accuracy. This paper proposes a collaborative semi-supervised classifier learning algorithm to achieve durative online learning for support vector machine (SVM) based robust target classification. The proposed algorithm incrementally carries out the semi-supervised classifier learning process in hierarchical WMSN, with the collaboration of multiple sensor nodes in a hybrid computing paradigm. For decreasing the energy consumption and improving the performance, some metrics are introduced to evaluate the effectiveness of the samples in specific sensor nodes, and a sensor node selection strategy is also proposed to reduce the impact of inevitable missing detection and false detection. With the ant optimization routing, the learning process is implemented with the selected sensor nodes, which can decrease the energy consumption. Experimental results demonstrate that the collaborative hybrid semi-supervised classifier learning algorithm can effectively implement target classification in hierarchical WMSN. It has outstanding performance in terms of energy efficiency and time cost, which verifies the effectiveness of the sensor nodes selection and ant optimization routing.