Search

Owing to their detection performance without the use of any instruments, visual sensing based on gold nanoparticles has become important and attractive for a wide range of applications in various fields, especially in sensing systems. In this study, a novel visual sensing platform for the detection of mercury (II) ion (Hg2+) was developed by using a graphene quantum dots functionalized gold nanoparticles nanocomposite system. To achieve the goal of selective, sensitive, and rapid sensing of Hg2+, gold nanoparticles (AuNPs) were combined with graphene quantum dots (GQDs). GQDs was assembled on AuNPs due to the strong interaction with the terminal amino groups of GQDs. A new procedure for the selective and sensitive detection of Hg2+ has been unveiled based on the prevention of aggregation of AuNPs functionalized with GQDs in the presence of analytes (i.e. Hg2+). [ABSTRACT FROM AUTHOR]

Wireless visual sensor networks have been adopted in different contexts to provide visual information in a more flexible and distributed way, supporting the development of different innovative applications. Although visual data may be central for a considerable set of applications in areas such as Smart Cities, Industry 4.0, and Vehicular Networks, the actual visual data quality may be not easily determined since it may be associated with many factors that depend on the characteristics of the considered application scenario. This entails several aspects from the quality of captured images (sharpness, definition, resolution) to the characteristics of the networks such as employed hardware, power consumption, and networking efficiency. In order to better support quality analysis and performance comparisons among different wireless visual sensor networks, which could be valuable in many monitoring scenarios, this article surveys this area with special concern on assessment mechanisms and quality metrics. In this context, a novel classification approach is proposed to better categorize the diverse applicable metrics for quality assessment of visual monitoring procedures. Hence, this article yields a practical guide for analyzing different visual sensor network implementations, allowing fairer evaluations and comparisons among a variety of research works. Critical analysis are also performed regarding the relevance and usage of the proposed categories and identified quality metrics. Finally, promising open issues and research directions are discussed in order to guide new developments in this research field.

The digital retina excels at providing enhanced visual sensing and analysis capability for city brain in smart cities, and can feasibly convert the visual data from visual sensors into semantic features. With the deployment of deep learning or handcrafted models, these features are extracted on front-end devices, then delivered to back-end servers for advanced analysis. In this scenario, we propose a model generation, utilization and communication paradigm, aiming at strong front-end sensing capabilities for establishing better artificial visual systems in smart cities. In particular, we propose an integrated multiple deep learning models reuse and prediction strategy, which dramatically increases the feasibility of the digital retina in large-scale visual data analysis in smart cities. The proposed multi-model reuse scheme aims to reuse the knowledge from models cached and transmitted in digital retina to obtain more discriminative capability. To efficiently deliver these newly generated models, a model prediction scheme is further proposed by encoding and reconstructing model differences. Extensive experiments have been conducted to demonstrate the effectiveness of proposed model-centric paradigm. [ABSTRACT FROM AUTHOR]

We demonstrate a simple strategy to concoct a competent solid-state opto-chemosensor for the selective and sensitive visual detection of Hg2+ ions. The sensor fabrication involves the utilization of indigenously prepared mesoporous silica and polymer monoliths as probe anchoring templates and 8-hydroxy-7-(4-n-butylphenylazo) quinoline (HBPQ) as the chromo-ionophoric probe for Hg2+ sensing. Both the monoliths are designed with discrete structural and morphological features to serve as efficient host templates. The structural and surface features of the monoliths are characterized using p-XRD, TEM, SEM, SAED, EDAX, XPS, and N2 isotherm analysis. The synergetic features of monolith structural hierarchy along with the probe's selective chelating ability enable rapid signal response and remarkable ion selectivity for Hg2+. The solid-state sensors evince a linear signal response from 0.6 to 150 μg/L for Hg2+ recognition, with superior data authenticity and replication that is preceded by an RSD value of ≤ 2.25% when tested with real water samples. Graphical abstract [ABSTRACT FROM AUTHOR]

The majority of sensors used for quantifying indices related to a pavement management system are costly; however, low-cost sensors such as RGB-D sensors have been recently deployed. The performance of RGB-D sensors in pavement condition data collection has not received enough attention. By providing a thorough literature review on the specification of RGB-D sensors, this paper aims to assess and compare the performance of two RGB-D sensors in pavement condition data collection. First, by collecting data from asphalt, concrete, and mosaic surfaces in wet and dry conditions, the accuracy and precision of the sensors are evaluated. For this purpose, noise reduction techniques are applied to the central region of interest and the inherent trend of depth frames is corrected by implementing the Singular Value Decomposition algorithm. Second, dimensions of artificial objects above the pavement surface are detected via sensors by using the Lease Square Method (LSM) and edge detection techniques to evaluate RGB-D sensors’ ability and performance in measurement of artificial pavement defects of known dimensions. The results of statistical analysis show the difference in error measurement via both sensors in all surfaces in wet and dry conditions. Through conducting extensive field experiments, it is concluded that Kinect one has several advantages over the Kinect Xbox 360 in pavement condition data collection. [ABSTRACT FROM AUTHOR]

• Glucosylrutin was coated on gold nanoparticles using attaching ability of catechol group. • Glucosylrutin-coated gold nanoparticles quantitatively detected particular lectin. • We applied urchin-shaped gold nanoparticles for visual sensing of lectin. Gold nanoparticles combined with a polyphenolic glycoside (α-glucosylrutin) were prepared and applied for the selective detection of proteins. Glucosylrutin was coated onto gold nanoparticles with a particle size of 40 nm, without aggregates and color changes. The glucosylrutin-coated gold surface was preferentially adsorbed with concanavalin A, which has specificity against glucosides and mannosides. When the glucosylrutin-coated gold nanoparticles were mixed with concanavalin A, the color of the dispersion changed from red to reddish violet. The level of chromatic change was dependent on the concentration of concanavalin A. When other proteins (bovine serum albumin and peanut agglutinin) were added to the dispersion, no color change was observed. The molecular recognition site for detection of concanavalin A was the glycoside moiety, because the catechin-coated gold nanoparticles have no function in the detection of concanavalin A. Urchin-shaped glucosylrutin-coated gold nanoparticles were also useful for the visual sensing of concanavalin A. [ABSTRACT FROM AUTHOR]

The dynamic arc behaviors have a significant effect on the process stability and welded joint quality in underwater wet flux-cored arc welding (FCAW). In this study, clear underwater arc images are obtained by using a high-speed camera, which further reveal the complex physical process of underwater wet welding. The mechanism of underwater contact arc ignition is described in detail. Gas ionization and electron emission processes are carried out in bubbles generated by resistance heat. The dynamic arc behaviors are obviously different between bubble growth and separation stages. The high-speed gas flow in the bubble separation stage has a great disturbance to the arc. The arc shapes under water and in air under the same parameters are compared, and the mechanism of arc column shrinkage and arc length shortening is revealed from the aspects of water environment cooling, gas composition in bubbles, disturbance of gas flow, water pressure, and electric field strength. [ABSTRACT FROM AUTHOR]

Ultrahigh precision motion control across different stages in a multistage system plays a central role in many micro/nanoscale applications. However, it remains a challenge due to the mechanical drift. Here, we propose a visual sensing based approach to implement the cooperative motion control in a multistage platform. In this method, microsized beads are attached to individual stages and taken as visual sensing probes. By tracking the motion of visual sensing probes, the positions of individual stages are measured. The principle of the proposed method is presented, followed by the experimental demonstration of the real-time mechanical drift compensation and high-precision cooperative motion control in a home-made dual piezoelectric flexural stage platform. With the proposed method, ultrahigh precision motion control between the two stages are achieved in a 3-D manner, with closed-loop motion control resolution of 1.5, 1.3, and 4.2 nm for X, Y, and Z axes, respectively. The proposed method provides an effective approach for ultrahigh precision motion control across different stages, which is believed to be significant for nanoscale manipulation related applications. [ABSTRACT FROM AUTHOR]

In the last two decades, visual sensor networks have been developed to gather visual data from different monitoring scenarios, directly contributing to the maturation of the Internet of Things (IoT) applications landscape. Such developments have evolved according to the releasing of new hardware platforms for the construction of sensor nodes, as well as the availability of low-power compatible cameras. Since sensor networks deployed for visual data sensing are inherently complex and resource-demanding, knowing how visual sensors have been created can give a better perception of how those networks have evolved and which innovations are expected for the next years. This article reviews past developments of visual sensors concerning the employed hardware platforms and cameras, providing a taxonomy for them and discussing how to choose the most appropriate hardware when designing and implementing modern (wireless) visual sensor networks. [ABSTRACT FROM AUTHOR]

[Display omitted] • A photonic crystal-based early fire warning sensor (EFWS) was fabricated. • The EFWS gives warnings for 0.9 s at 260 °C. • Color change of the EFWS is based on the chain motion of polymers. • A good candidate for non-open flame warnings in the precombustion stage. Fire detection plays a crucial role in maintaining the safety of people's lives and property. However, most early fire detectors are designed to monitor the current or voltage changes of the sensing materials, which require external power supplies. It is still a challenge to make rapid and accurate noncontact early fire detection in precombustion due to the lack of reliable alarm signals. Herein, inspired by the discoloration of chameleon skin, we developed an early fire warning sensor (EFWS) by coating photonic crystals (PCs) on a plastic sheet with thermal expansion properties. Monodispersed zinc sulfide (ZnS) was coated on the plastic sheet as abnormal detection component for EFWS. Combined with the intelligent image recognition algorithm, the EFWS was designed and gave warnings for 0.9 s at 260 °C. For the first time, a photonic crystal-based non-contact real-time monitoring EFWS in precombustion is developed. The sensing material can be directly pasted on the surface of the detected equipment, and combined with existing surveillance cameras in the detection area, early warning of fires can be achieved. The EFWS system can be used in non-open fire alarms for aircraft, buildings, electrical appliances, substations, and other places in the future. [ABSTRACT FROM AUTHOR]

[Display omitted] • An aligned TPU electrospun mat with wave-like structure is selected as the substrate. • The microcrack structure is constructed by pre-stretching technology. • The strain sensor can achieve sign language interpretation and multi-angle recognition. • The visual sensing function expands the application area of the CNTs/AgNWs/TPU sensor. Recently, flexible strain sensors have attracted great attention on account of the application potential in medical treatment, flexible prosthetics and human–machine interaction. Nevertheless, traditional uniaxial strain sensors cannot detect movement in different directions, limiting the applications in sensing technologies. In addition, it is still a significant challenge to simultaneously acquire visualized and high-performance strain sensors. Here, a highly flexible sensor with visual sensing function was fabricated by spraying silver nanowires (AgNWs)/carbon nanotubes (CNTs) ink on the aligned thermoplastic polyurethane (TPU) electrospun mat. The sensing performances of AgNWs/CNTs aligned TPU fluorescent mats (ACUM-F) are individually explored in vertical and parallel directions. Herein, the ACUM-F in vertical can exhibit high sensitivity (gauge factor (GF) up to 244.3), wide working range (0.1 ∼ 380 % strain), fast response/recovery time (80 ms/80 ms), good sensing durability and reproducibility (1000 stretching/releasing test cycles). Furthermore, ACUM-F is assembled as strain sensors to monitor various human body movements, which can achieve sign language interpretation through finger gesture monitoring, demonstrating its great potential in human–machine interaction. The direction-aware application of novel multidirectional sensors with visual sensing functions may bring inspiration for a new era of flexible electronics development. [ABSTRACT FROM AUTHOR]

Melanoma is the most lethal form of skin cancer, and develops from mutation of pigment-producing cells. As it becomes malignant, it usually grows in size, changes proportions, and develops an irregular border. We introduce a system for early detection of such changes, which enables whole-body screening, especially useful in patients with atypical mole syndrome. The paper proposes a procedure to build a 3D model of the patient, relate the high-resolution skin images with the model, and orthorectify these images to enable detection of size and shape changes in nevi. The novelty is in the application of image encoding indices and barycentric coordinates of the mesh triangles. The proposed procedure was validated with a set of markers of a specified geometry. The markers were attached to the body of a volunteer and analyzed by the system. The results of quantitative comparison of original and corrected images confirm that the orthorectification allows for more accurate estimation of size and proportions of skin nevi.

In this work, we proposed a double moving redox boundary (MROB) model to realize the colorless analyte electrophoresis titration (ET) by the two steps of the redox reaction. Single MROB has been proposed for the development of ET sensing (Analyst, 2013, 138, 1137. ACS Sensor, 2019, 4, 126.), and faces great challenges in detecting the analyte without color change during redox reaction. Herein, a novel model of double-MROB electrophoresis, including its mechanisms, equations, and procedures, was developed for titration by using ascorbic acid as a model analyte. The first MROB was created with ferric iron (Fe 3+ ) and iodide ion (I - ) in which Fe 3+ was reduced as Fe 2+ and I - was oxidized as molecular iodine (I 2 ) used as an indicator of visible MROB due to blue starch-iodine complex. The second boundary was then formed between the molecular iodine and model analyte of ascorbic acid. Under given conditions, there was a quantitative relationship between velocity of MROB (V MROB(ii) ) and ascorbic acid concentration (C Vit C ) in the double-MROB system (1/V MROB(ii)  = 0.6502C Vit C  + 4.5165, and R = 0.9939). The relevant relative standard deviation values of intraday and inter-day were less than ∼5.55% and ∼6.64%, respectively. Finally, the titration of ascorbic acid in chewable vitamin C tablets was performed by the developed method, the titration results agreed with those via the classic iodometric titration. All the results briefly demonstrated the validity of the double MROB model, in which Vit C was used as a model analyte. The developed method had potential use in quantitative analysis of redox-active species in biomedical samples., (© 2024 Wiley‐VCH GmbH.)

A facilely in situ fabricated hydrogen-bonded organic framework (HOF) hydrogel film with perfect photoluminescent performance was designed for visual sensing of tetracycline antibiotics (TCs) and information security. Luminescent HOF (MA-IPA) was combined with sodium alginate (SA) through hydrogen bonding actions and electrostatic interactions, then cross-linked with Ca 2+ ions to form HOF hydrogel film (Ca@MA-IPA@SA). The HOF hydrogel film exhibited exceptional mechanical robustness along with stable blue fluorescence and ultralong green phosphorescence. After exposure to TCs, Ca 2+ was combined with TCs to generate a new green fluorescence exciplex (TC-Ca 2+ ) in hydrogel films. Due to fluorescence resonance energy transfer, the fluorescence of MA-IPA was quenched, and the fluorescent color of the HOF hydrogel film was changed from blue to green. This dichromatic fluorescent response is convenient for the visual and rapid detection of TCs. The detection limits of tetracycline (TC), oxytetracycline (OTC), and chlortetracycline (CTC) were 5.1, 7.7, and 32.7 ng mL -1 , respectively. Importantly, this hydrogel sensing platform was free of tedious operation and enabled the ultrasensitive and selective detection of TCs within 6 min. It has been successfully applied to TC detection in pork and milk samples. Based on the stable photoluminescence performance of HOF hydrogel films and fluorescent-responsive properties to TCs, two types of anticounterfeiting arrays were fabricated for information encryption and decryption. This work provides a novel approach for on-site detection of TCs and offers valuable insights into information security.

Methods for optical detection of inorganic cyanide based on the single molecule sensor with high selectivity and sensitivity have attracted increasing interest recently due to the high toxicity of cyanide ions. In this work, a visual sensor (S1) containing both imidazole NH and azo-phenolic OH was synthesised and characterised. The spectral experimental data indicated that protic aqueous solution facilitated enhancing the selectivity of cyanide ions with the nanomolar-level detection limit in semi-aqueous solution. The visual sensing mechanism arising from the deprotonation of azo-phenolic OH and the enhancement of intramolecular charge transfer could be clearly demonstrated by titration experiments of 1H NMR, HR MS and energy changes between the HOMO−LUMO band gaps. Furthermore, the reversibility and reusability of S1 upon alternating addition of CN− and H+ were studied. A visual sensor incorporated by imidazole NH and azo-phenolic OH was developed to detect inorganic CN− via reversible proton transfer based on the deprotonation/protonation of azo-phenolic OH/O− in aqueous solution. [ABSTRACT FROM AUTHOR]

• Visualized lateral flow sensing protocol is developed for rapid authentication of adulterated beef in less than 2 h. • The visualized sensing limit of adulteration ratio is as low as 0.05% (wt) of beef samples. • Real commercial processed beef samples are successfully screened with this visualized lateral flow sensing protocol. A novel high-sensitivity authentication method has been demonstrated for the rapid visual detection of adulterated meat based on both the lateral flow strip (LFS) platform and on polymerase chain reaction (PCR). After the rapid extraction of genomic components from meat, the on-site amplification of the target DNA of adulterated duck meat is carried out with the rationally designed functional FITC- and biotin-modified primer set, thereby producing numerous double-stranded DNA (dsDNA) products dually labelled with FITC and biotin. The FITC-labelled terminal end of the products binds to the pre-immobilized FITC antibody on the test line of the strip, and the biotin-labelled terminal end binds to the streptavidin-conjugated gold nanoparticles, resulting in a visible test line on the LFS for the rapid identification of duck meat in adulterated beef. After optimization, an adulteration ratio as low as 0.05% can be easily measured, which is more sensitive than other common adulteration authentication methods and is even comparable to instrumental methods. Moreover, 22 commercial processed meat samples were tested with this new strategy, and 4 adulterated samples were successfully identified by both the classic method and our method. In essence, the present authentication method is simple in design, convenient in operation, and can be easily extended to the identification of other adulteration components just by replacing the modified primers. [ABSTRACT FROM AUTHOR]

• An effective ratiometric fluorescent sensor is designed for visual detection of Hg2+. • This sensor shows high specificity and sensitivity for Hg2+ detection. • The ratiometric fluorescent sensor shows a vivid color change for Hg2+ level. • This method shows great potential for visual detection of Hg2+ in on-site. Sensitive and selective determination of mercury ion (Hg2+) is critical for human health and environmental monitoring. Herein we construct an effective ratiometric fluorescent sensing platform by combining green fluorescent polymer carbon dots (PCDs) and red fluorescent tetraphenylporphyrin tetrasulfonic acid hydrate (TPPS) for specific and visual detection of Hg2+. The fluorescence of PCDs can be quenched by TPPS through inner filter effect (IEF). In the presence of both Mn2+ and Hg2+, however, Hg2+ can expedite the complexation of TPPS and Mn2+, which causes the decrease in both fluorescence and absorption of TPPS, accompanied by the fluorescence recovery of PCDs due to the subdued IFE between TPPS and PCDs. Based on the change of fluorescence signal, a ratiometric fluorescent sensing platform is constructed for specific and visual detection of Hg2+. The proposed approach presents a fine linear range for Hg2+ over the range of 10–200 nM with a detection limit of 0.038 nM. Moreover, an easily distinguishable fluorescence color change from pink to green with the increase of Hg2+ concentration can be observed by the naked eye under a UV lamp. Such a simple and effective method shows great potential for visual sensing of Hg2+ in on-site and resource-limited settings. [ABSTRACT FROM AUTHOR]

With the Microsoft's RGB-D sensor Kinect and a customized 3- axis pan-tilt-roll machinery, a new intelligent sensing and tracking system was designed and manufactured. In order to simulate human natural visual sensing behavior, this system adopts the sensing function from Kinect installed upon the 3-axis motion machinery, controlled by an expert PID control algorithm based on the adaptive Kalman filter, so as to guarantee automatic real-time visual tracking and to observe human movements and receive his/her position information. This system is designed to be applied directly to the video production of distance education, aiming to improve distance education itself and resolve difficulties in keeping account of users learning state. It also has great potential of functioning as a basic platform where many other human-computer natural interactions can be extended. [ABSTRACT FROM AUTHOR]

This present paper addresses the process monitoring of laser-MAG hybrid welding by using a double high-speed camera sensing system. Different welding parameter experiments are conducted under the normal penetration condition. The real-time surface physical phenomena of top and bottom in welding process are captured by the sensing system. The image processing method is proposed to quantify the process status, such as droplet transition, spatter, keyhole bottom, and metal vapor. The statistical method combined with detail analysis method is used to analyze the effects of droplet transition on keyhole status under different welding parameters. Also, the time distribution of opened keyhole bottom is analyzed. The synchronization analysis is conducted to demonstrate the status of the droplet transition and laser-induced keyhole, and the status of the opened keyhole bottom is separated as two types: opened keyhole bottom occurs during droplet transition or during droplet growing. The experimental analysis results demonstrate that the droplet transition mainly affects the status of keyhole under normal penetration condition, and the opened time of keyhole bottom is quite different which means the effects are unstable. Furthermore, the experimental results confirmed that the process monitoring method in this paper is an effective way for laser-MAG hybrid welding evaluation. [ABSTRACT FROM AUTHOR]

Abstract A porphyrinic metal-organic framework, PCN-222, was employed for the fast and sensitive determination of cysteine (Cys) based on its fluorescence (FL) property. A "turn-on" sensor was easily established based on the instant metalation of PCN-222 with Hg2+, and the sensing for Cys primarily derived from the strong binding between Hg and Cys, with the PCN-222 FL fast recovered via the rapid and efficient release of Hg. A more than two orders of magnitude in the linear dynamic range and a limit of detection as low as 60 nM were obtained by using the proposed method based on FL measurement. In particular, the sensing could also be accomplished in a visual manner, with the color change of Hg-metalated PCN-222 easily observed by naked eyes upon the addition of Cys as low as 100 nM. The proposed strategy for Cys sensing also showed advantages including facile preparation and cyclic usage of the probe, fast response (1 min) to Cys, high sensitivity for both FL and visual sensing, and no extra additives such as catalysts nor chromogenic substrates. Highlights • Porphyrinic MOF is used as the sensing probe for cysteine; • Both fluorescence and visual sensing for cysteine can be accomplished; • The sensing is of high sensitivity, fast response and wide dynamic range; • The preparation of the sensing probe is facile and green. [ABSTRACT FROM AUTHOR]

Abstract In the heavy construction industry, pipe spool assembly is geometrically complex and suboptimal fabrication processes inevitably lead to fabrication errors and costly rework. In an attempt to mitigate fabrication risks and improve product quality, computer aided tools are being developed to provide an additional layer of control. In this paper, the data acquisition capabilities of two low-cost range cameras are investigated for the eventual purpose of pipe fitting process monitoring in a smart fabrication facility environment. Range images of various pipes are systematically taken at varying distances from the sensor. By using the proposed radius estimation algorithm, the utility of the data for accurate geometrical pipe feature detection is evaluated by a radius feature metric. Results show that the algorithm reliably extracts radius information from point clouds representing piping. In conjunction with the algorithm, the low-cost range camera hardware was able to characterize pipes, of radius ranging from 2.41 cm to 8.78 cm at a distance from the sensor ranging from 0.5 m to 3.75 m, with an average error of 18% for Kinect 1 and 10% for Kinect 2. Highlights • Low-cost range cameras are investigated for 3D geometric modeling. • A statistical approach is performed for radius detection and estimation from 3D point clouds. • Optimal nearest neighborhood size for various devices are analyzed. • Range cameras are capable of detecting and estimating cylindrical objects at close ranges. [ABSTRACT FROM AUTHOR]

Highlights • A passive visual sensing technique is proposed based on focal stack and light field imaging. • The 3D visual sensing prototype for the snake robot was realized by the focal stack acquisition system. • The depth, all-in-focus image as well as the 3D point cloud can be reconstructed by the prototype. • This technique could be further applied to visual navigation, SLAM and visual servoing of the robot. Abstract In this paper, we proposed a passive 3D visual sensing technique based on the focal stack and designed the snake robot's 3D visual sensing prototype. The proposed technique consists of depth reconstruction, all-in-focus imaging and 3D point cloud generation based on the theoretical model of light field reconstruction from the focal stack. The 3D visual sensing prototype was realized by the focal stack acquisition system controlled by the servo motor. In the experiment, the depth map with high precision, all-in-focus image with high spatial resolution as well as the 3D point cloud can be reconstructed in the field-of-view (FOV) by the 3D visual sensing prototype. The proposed technique could be further applied to efficient visual navigation, simultaneous-localization-and-mapping (SLAM) and visual servoing of the robot. [ABSTRACT FROM AUTHOR]

This paper proposes a novel metal additive manufacturing process, which is a composition of gas tungsten arc (GTA) and droplet deposition manufacturing (DDM). Due to complex physical metallurgical processes involved, such as droplet impact, spreading, surface pre-melting, etc., defects, including lack of fusion, overflow and discontinuity of deposited layers always occur. To assure the quality of GTA-assisted DDM-ed parts, online monitoring based on visual sensing has been implemented. The current study also focuses on automated defect classification to avoid low efficiency and bias of manual recognition by the way of convolutional neural network-support vector machine (CNN-SVM). The best accuracy of 98.9%, with an execution time of about 12 milliseconds to handle an image, proved our model can be enough to use in real-time feedback control of the process.

In critical industrial monitoring and control applications, dependability evaluation will be usually required. For wireless sensor networks deployed in industrial plants, dependability evaluation can provide valuable information, enabling proper preventive or contingency measures to assure their correct and safe operation. However, when employing sensor nodes equipped with cameras, visual coverage failures may have a deep impact on the perceived quality of industrial applications, besides the already expected impacts of hardware and connectivity failures. This article proposes a comprehensive mathematical model for dependability evaluation centered on the concept of Quality of Monitoring (QoM), processing availability, reliability and effective coverage parameters in a combined way. Practical evaluation issues are discussed and simulation results are presented to demonstrate how the proposed model can be applied in wireless industrial sensor networks when assessing and enhancing their dependability.

The adoption of emergency alerting systems can bring countless benefits when managing urban areas, industrial plants, farms, roads and virtually any area that is subject to the occurrence of critical events, supporting in rescue operations and reducing their negative impacts. For such systems, a promising approach is to exploit scalar sensors to detect events of interest, allowing for the distributed monitoring of different variables. However, the use of cameras as visual sensors can enhance the detection of critical events, which can be employed along with scalar sensors for a more comprehensive perception of the environment. Although the particularities of visual sensing may be challenging in some scenarios, the combination of scalar and visual sensors for the early detection of emergency situations can be valuable for many scenarios, such as smart cities and industry 4.0, bringing promising results. Therefore, in this article, we extend a sensors-based emergency detection and alerting system to also exploit visual monitoring when identifying critical events. Implementation and experimental details are provided to reinforce the use of cameras as a relevant sensor unit, bringing promising results for emergencies management.

Low frequency vibration monitoring has significant implications on environmental safety and engineering practices. Vibration expressed by visual information should contain sufficient spatial information. RGB-D camera could record diverse spatial information of vibration in frame images. Deep learning can adaptively transform frame images into deep abstract features through nonlinear mapping, which is an effective method to improve the intelligence of vibration monitoring. In this paper, a multi-modal low frequency visual vibration monitoring system based on Kinect v2 and 3DCNN-ConvLSTM is proposed. Microsoft Kinect v2 collects RGB and depth video information of vibrating objects in unstable ambient light. The 3DCNN-ConvLSTM architecture can effectively learn the spatial-temporal characteristics of muti-frequency vibration. The short-term spatiotemporal feature of the collected vibration information is learned through 3D convolution networks and the long-term spatiotemporal feature is learned through convolutional LSTM. Multi-modal fusion of RGB and depth mode is used to further improve the monitoring accuracy to 93% in the low frequency vibration range of 0–10 Hz. The results show that the system can monitor low frequency vibration and meet the basic measurement requirements.

With the increasing climatic extremes, the frequency and severity of urban flood events have intensified worldwide. In this study, image-based automated monitoring of flood formation and analyses of water level fluctuation were proposed as value-added intelligent sensing applications to turn a passive monitoring camera into a visual sensor. Combined with the proposed visual sensing method, traditional hydrological monitoring cameras have the ability to sense and analyze the local situation of flood events. This can solve the current problem that image-based flood monitoring heavily relies on continuous manned monitoring. Conventional sensing networks can only offer one-dimensional physical parameters measured by gauge sensors, whereas visual sensors can acquire dynamic image information of monitored sites and provide disaster prevention agencies with actual field information for decision-making to relieve flood hazards. The visual sensing method established in this study provides spatiotemporal information that can be used for automated remote analysis for monitoring urban floods. This paper focuses on the determination of flood formation based on image-processing techniques. The experimental results suggest that the visual sensing approach may be a reliable way for determining the water fluctuation and measuring its elevation and flood intrusion with respect to real-world coordinates. The performance of the proposed method has been confirmed; it has the capability to monitor and analyze the flood status, and therefore, it can serve as an active flood warning system.

Abstract A simple hydrazine carboxamide derivative with intramolecular charge transfer and aggregation induced emission (AIE) properties have been designed and synthesized. The derivative (Probe 1) shows typical AIE characteristic emission in THF-water mixtures and emits yellowish orange color on reaching the water fraction 98%. The probe molecule show selective sensing response for Cu2+ ions via fluorescence turn-off mechanism in aqueous media over other metal ions. The emission changes towards Cu2+ ions that could be clearly observed by the naked eyes under 365 nm UV lamp promote the probe molecule as a promising candidate for practical utilization. Furthermore, from the fluorescence titration data, the detection limit for Cu2+ ions was found to be 0.44 μM. Graphical abstract Unlabelled Image Highlights • A simple caboxamide derivative displaying aggregation induced emission has been synthesized. • It can act as fluorescent probe for Cu2+ions. • The sensing ability of the derivative could be visualized using 365 nm UV lamp. [ABSTRACT FROM AUTHOR]

This paper presents a sophisticated vision-aided flocking system for unmanned aerial vehicles (UAVs), which is able to operate in GPS-denied unknown environments for exploring and searching missions, and also able to adopt two types of vision sensors, day and thermal cameras, to measure relative motion between UAVs in different lighting conditions without using wireless communication. In order to realize robust vision-aided flocking, an integrated framework of tracking-learning-detection on the basis of multifeature coded correlation filter has been developed. To achieve long-term tracking, a redetector is trained online to adaptively reinitialize target for global sensing. An advanced flocking strategy is developed to address the autonomous multi-UAVs' cooperative flight. Light detection and ranging (LiDAR)-based navigation modules are developed for autonomous localization, mapping, and obstacle avoidance. Flight experiments of a team of UAVs have been conducted to verify the performance of this flocking system in a GPS-denied environment. The extensive experiments validate the robustness of the proposed vision algorithms in challenging scenarios. [ABSTRACT FROM AUTHOR]

Sensitive detection and determination of hardness and fluoride in the ground water is an important issue for the water safety. The present work reports a sensitive, selective, rapid and visual hybrid fluorescent nanosensor by hybridizing carbon dots and hexametaphosphate capped gold nanoparticles through intrinsic interactions of the two components. The hybrid nanosensor can be used for hardness (Ca 2+ , Mg 2+ ) detection with the fluorescence intensity decreasing at 439 nm and increasing at 608 nm via the aggregation induced fluorescence resonance energy transfer on mechanism. In addition, the hybrid nanosensor mixed with calcium ions can detect fluoride in water with a lower detection limit of 0.339 ppm with the fluorescence color recovery based on the precipitation induced fluorescence resonance energy transfer off process. Experimental results indicate that the as-synthesized hybrid nanosensor has shown efficient feasibility and practicality for hardness and fluoride detection in actual groundwater samples. Furthermore, a paper-based analytical device has been fabricated by immobilizing the hybrid nanosensor on the cellulose filter paper for the visual and on-site detection of fluoride in water. The hybrid nanosensor would provide new sensing materials and mechanisms for the determination and detection of hardness and fluoride in the groundwater. [ABSTRACT FROM AUTHOR]

Norovirus, which is transmitted by contact with a contaminated object or person who has a norovirus infection, eating contaminated food, or drinking contaminated water, is a highly contagious virus for humans and animals. Among many infection routes, water supply systems from reservoirs or dams become very important due to the possibility of mass infection. Because only a small amount of norovirus (10–100 particles forming unit) can cause the infection, a rapid and easy detection of the virus is required. Once norovirus is detected, the water supply should be quickly shut down. Here, we introduce a dual functional membrane capable of both easy detecting with the naked eye and blocking noroviruses. We employed an anodized aluminum oxide (AAO) membrane with uniform pores. The top and bottom parts of the membrane were grafted with polydiacetylene (PDA) and poly(N-isopropylacrylamide) (PNIPAM), respectively. The top part was further bioconjugated by antibody for feline calicivirus (FCV), which is a model virus whose structure is similar to norovirus. The membrane showed color change from blue to red when the FCVs were attached to the antibodies. Water flux was controlled (turned on and off) by changing water temperature by using the well-known thermosensitive property of PNIPAM chains. On and off control of water flow was quickly established (less than 5 s) when a laser with near infrared (NIR) wavelength was turned on and off, respectively. In addition, the membrane completely blocked the virus influx into the water system by antibody binding before visual sensing followed by flow control. [ABSTRACT FROM AUTHOR]

Measuring pavement roughness and detecting pavement surface defects are two of the most important tasks in pavement management. While existing pavement roughness measurement approaches are expensive, the primary aim of this paper is to use a cost-effective and sufficiently accurate RGB-D sensor to estimate the pavement roughness in the outdoor environment. An algorithm is proposed to process the RGB-D data and autonomously quantify the road roughness. To this end, the RGB-D sensor is calibrated and primary data for estimating the pavement roughness are collected. The collected depth frames and RGB images are registered to create the 3D road surfaces. We found that there is a significant correlation between the estimated International Roughness Index (IRI) using the RGB-D sensor and the manual measured IRI using rod and level. By considering the Power Spectral Density (PSD) analysis and the repeatability of measurement, the results show that the proposed solution can accurately estimate the different pavement roughness.

Several cholesteryl naphthalimide-derived compounds have been sythesized and developed as CO 2 sensors. The derivatives, incorporating ether chains, were found to be capable of gelating various organic solvents, due to the modulation of the hydrophilicity/hydrophobility properties of them. The resulting organogels were well characterized by field emission scanning electron microscopy (FE-SEM), FT-IR spectroscopy, concentration- and temperature-dependent 1 H NMR spectra, and powder X-ray diffraction (PXRD). These gelators can be applied as fluorescent sensors for CO 2 in DMSO solutions via the anion-triggered strategy. Furthermore, the resulting organogelation systems in DMSO could also provide visual sensing means for CO 2 via the reversible solution-to-gel transition. Particularly, the re-gelation of DMSO induced by CO 2 bubbling could be directly observed without the aid of the heating-and-cooling operation. And the reversible sensing process could be repeated several times with the excellent chemical stability of the gelation system after the repeated stimuli of fluoride anion, CO 2 and N 2 with heating. These investigations indicate the developed organogelators own the applicable potential in the CO 2 detection. [ABSTRACT FROM AUTHOR]

As an integral part of many important enzymes, Cu 2+ is involved in a number of vital biological processes, which is linked to the oxidative damage and environmental contamination when Cu 2+ is excessive. In this work, Cu 2+ can be captured by the amino groups of carbon dots (CDs) to form complexes, resulting in a strong fluorescence quenching of CDs via a nonradiative electron transfer process, which offered a rapid, visual, and selective methodology for Cu 2+ detection. The probe exhibited a wide response concentration range (0.01–2 μM) to Cu 2+ with a detection limit of 6.7 nM. Significantly, the CDs presented excellent biocompatibility and high photostability, which were applicable for the visualization of Cu 2+ dynamic invasion into living cells and Tilapia mossambica. Furthermore, the toxicity of Cu 2+ ions to living cells could be inhibited with CDs by the formation of complexes. [ABSTRACT FROM AUTHOR]

Dual cameras were employed to observe the complete topside weld pool from the lateral side and to capture the keyhole entrance from the rear view in plasma arc welding. By image registration, the images were fused into a cohesive whole in the same physical coordinate system. Weld pool and keyhole behaviors were studied under different welding parameters. Possible interaction mechanisms between plasma arc, gas flow, liquid metal and keyhole were discussed. Instant and significant influences on the keyhole entrance shape and geometries originated in the changed forces applied on the surrounded liquid metal. [ABSTRACT FROM AUTHOR]

Mercury ions sensing is an important issue for human health and environmental safety. A novel fluorescence nanosensor was designed for rapid visual detection of ultratrace mercury ions (Hg 2+ ) by using CH 3 NH 3 PbBr 3 perovskite quantum dots (QDs) based on the surface ion-exchange mechanism. The synthesized CH 3 NH 3 PbBr 3 QDs can emitt intense green fluorescence with high quantum yield of 50.28%, and can be applied for Hg 2+ sensing with the detection limit of 0.124 nM (24.87 ppt) in the range of 0 nM–100 nM. Furthermore, the interfering metal ions have no any influence on the fluorescence intensity of QDs, showing the perovskite QDs possess the high selectivity and sensitivity for Hg 2+ detection. The sensing mechanism of perovskite QDs for Hg 2+ is has also been investigated by XPS, EDX studies, showing Pb 2+ on the surface of perovskite QDs has been partially replaced by Hg 2+ . Spot plate test shows that the perovskite QDs can also be used for visual detection of Hg 2+ . Our research indicated the perovskite QDs are promising candidates for the visual fluorescence detection of environmental micropollutants. [ABSTRACT FROM AUTHOR]

Through a combination of wearable cameras, hardware accelerators, and algorithms, a vision-based automatic shopping assistant allows users with limited or no sight to select products from grocery shelves. [ABSTRACT FROM AUTHOR]

The irrational use of tetracycline antibiotics (TCs) leads to the pollution of environmental resources and finally threatens human health, which makes it urgent to develop a sensor for sensitively and selectively detecting the antibiotics. In this work, a Zn-based metal-organic framework (Zn-MOF) anchored on an amino-functionalized aluminum-based metal-organic framework (NH 2 -MIL-53(Al)) was constructed as a fluorescence sensor for TCs determination. The abundant –NH 2 made NH 2 -MIL-53(Al) a self-assembly core, which facilitated the formation of MOF-on-MOF heterojunction by amide reaction with the exposed –COOH of Zn-MOF. The single characteristic emission peak of Zn-MOF-on–NH 2 –MIL-53(Al) at 402 nm could identify TCs by internal filtration effect. Upon introduction of TCs, Zn-MOF-on–NH 2 –MIL-53 (Al) enhanced the intrinsic fluorescence signal of TCs at 517 nm through the coordination via the metal active center (Zn (II)), forming a ratiometric fluorescent sensor with a reverse response. Zn-MOF-on–NH 2 –MIL-53(Al) sensor displayed excellent anti-interference capability with a broader linear range (0.1–80 μM), and a lower limit of detection (LOD) of 8.24 nM for tetracycline (TC), 2.77 nM for oxytetracycline (OTC), and 8.85 nM for doxycycline (DC), respectively. By merit of Zn-MOF-on–NH 2 –MIL-53(Al), a portable smartphone-integrated test hydrogel colorimetric platform was fabricated for visual colorimetric detecting TCs by incorporating the sensor with a smartphone. Additionally, the bimetal-organic framework smartphone sensing platform exhibited satisfactory recovery (95.66–107.65%) and reliability in beef, pork, and chicken. Accordingly, the tactics presented a new strategy for developing an integrated system for environmental pollutant detection. Portable visual ratiometric fluorescence sensing platform for tetracyclines monitoring. [Display omitted] • Zn-MOF is anchored on NH 2 -MIL-53(Al) by the C–N of amide reaction. • Enhanced the innate fluorescence of TCs via coordination with Zn (II) active center. • Reverse response of two signals enhances the sensibility when recognized by the sensor. • Visual multicolor tonality change of test hydrogel facilitates on site detection. [ABSTRACT FROM AUTHOR]

Photonic elastomers that can change colors like a chameleon have shown great promise in the fields of visual sensing, intelligent wearing equipment and others. However, how to improve the performances of photonic elastomers to avoid the inconsistency of color caused by different observation angles remains a major challenge in this field. Recently, Professor Zhu Jintao and Professor Zhang Lianbin at Huazhong University of Science and Technology have made significant contributions to the field of responsive photonic materials, especially in the field of self-healing photonic crystal elastomers. This paper briefly reviews their recent progress in the area of responsive photonic materials. [ABSTRACT FROM AUTHOR]

Environmental monitoring is evolving towards large-scale and low-cost sensor networks operating reliability and autonomously over extended periods of time. Sophisticated analytical instrumentation such as chemo-bio sensors present inherent limitations because of the number of samples that they can take. In order to maximize their deployment lifetime, we propose the coordination of multiple heterogeneous information sources. We use rainfall radar images and information from a water depth sensor as input to a neural network (NN) to dictate the sampling frequency of a phosphate analyzer at the River Lee in Cork, Ireland. This approach shows varied performance for different times of the year but overall produces output that is very satisfactory for the application context in question. Our study demonstrates that even with limited training data, a system for controlling the sampling rate of the nutrient sensor can be set up and can improve the efficiency of the more sophisticated nodes of the sensor network.

Finding the DNA of the human immune deficiency virus (HIV) with simple and sensitive detection is the main challenge in early diagnosis of AIDS. Herein, two-point separation strategies based on the colorimetric and fluorescence are introduced. The naked-eye qualitative and semiquantitative colorimetric, and also accuracy fluorescence quantification of HIV-1 DNA were applied using label-free NiFe 2 O 4 @UiO-66 nanozyme with both functions of peroxidase-mimetic like and emitting fluorescence. The DNA probe-conjugated nanozyme is employed to hybridize a sequence of HIV-1. NiFe 2 O 4 @UiO-66 nanozymes catalyze the decomposition of H 2 O 2 to •OH which can produce a remarkable fluorescent product 2-hydroxyterephthalic acid (TAOH) by the oxidation of the bridging ligand of weakly fluorescent terephthalic acid (TA). The accessibility of H 2 O 2 toward confined-NiFe 2 O 4 MNPs was reduced by increasing the HIV-1 target DNA concentration, resulting in the fluorescence intensity of TAOH being decreased. Meanwhile, remaining the unreacted H 2 O 2 was transferred an acidic colorimetric solution containing FeSO 4 and gold nanorods (AuNRs). Increasing the amount of H 2 O 2 available for longitudinal etching of AuNRs due to •OH-generating Fe+2-catalyzed H 2 O 2 is reponsible for different colors from brownish to colorless depending on the HIV-1 target DNA concentration. The fluorescence intensity and obtained colors have offered the sensitive biosensing methods with a linear range from 0.05 to 300 and 1–200 pM, respectively with a detection limit as low as 1 fM. Our study revealed that the applied sensing assay provides a cost-effective and straightforward qualitative, semiquantitative, and sensitive quantitation visible monitoring without the necessity of high-end instruments for HIV-1 detection in a human blood plasma/serum samples. [Display omitted] • A label-free multicolor colorimetric and fluorescence dual mode biosensing were applied for HIV-DNA detection. • Determination of HIV-1 DNA was achieved by catalyzing and emitting fluorescence of NiFe 2 O 4 @UiO-66 nanozyme. • AuNRs represent different colors from brownish to colorless depending on the HIV-1 target DNA. • Representing of the dual mode biosensing with wide linear range, 0.05 to 300 and 1–200 pM, and low detection limit, 1 fM. [ABSTRACT FROM AUTHOR]

In routine laparoscopic surgeries, the fatigue operation and improper chief-assistant coordination of the assistant surgeon both reduce the stability of the endoscopic field of view (EFOV) and the surgical efficiency. In contrast, the assistant endoscope-holding robot (AEHR) can stably hold the endoscope and adjust the pose of endoscopic image sensor. However, the traditional method simplifies the tracking of surgical instrument tips (SITs) to the tracking of feature points, and lacks the depth optimization of monocular endoscopic image senor. Based on them, this paper proposes a surgical instrument tracking control method based on visual tracking features (VTFs) and hand-eye coordination (HEC) with feedback of multiple sensors, which can control the depth and axial rotational degrees of freedom (DOFs) of endoscope while tracking SITs. Firstly, the motion mapping Jacobian matrix between the endoscopic image sensor and the endoscope-holding manipulator (EHM) end-effector is constructed with joint encoder feedbacks, and the VTFs of endoscopic camera feedback are extracted based on the deep segmentation model of SITs. Secondly, the position adjustment model based on VTFs and the attitude adjustment model based on HEC are established. Thirdly, a complete set of visual servo control (VSC) software and hardware system for AEHRs is designed. Finally, the correctness, effectiveness and operability of the proposed method are comprehensively verified through the simulation and experiment of surgical instrument tracking. The visual tracking distance and radius error of endoscopic image sensor frames are reduced by no less than 34.6% and 42.59% under different experimental backgrounds, respectively. [Display omitted] • An endoscopic pose control method based on VTFs and HEC is established. • An endoscopic position adjustment model is derived. • A VSC experimental platform and simulation system for AEHR is reconstructed. • An open-source semantic segmentation data set for surgical instrument tips is provided. • The system modeling and instrument tracking performance are verified. [ABSTRACT FROM AUTHOR]

We report a simple, facile, selective, and highly sensitive colorimetric sensor for nitroguanidine explosive. The colorimetric sensor utilizes the aggregation of creatinine-modified gold nanoparticles (AuNPs), which was caused by nitroguanidine via hydrogen bond interaction between nitroguanidine and creatinine, leading to a color change from red to blue to colorless dependent on the concentration of nitroguanidine. Under optimum sensing concentrations, the absorbance changes of AuNPs at 519 nm were linear with the concentration of nitroguanidine in the range of 15-55 μM with a correlation coefficient of 0.997. The limit of detection of the colorimetric sensor was 1 μM based on the signal-to-noise of three, which has improved by as much as five orders of magnitude as compared with the traditional volumetric method and up to three orders of magnitude as compared with fluorescence approach as well. Moreover, as low as 15 μM of nitroguanidine can be visually detected by the naked eye without instrumentation. The colorimetric sensor also displayed remarkable selectivity to nitroguanidine against other explosives and common inorganic salts. It was robust and can be employed for reliable sensing of spiked nitroguanidine in real water samples with good recovery and accuracy. [ABSTRACT FROM AUTHOR]

For many visual monitoring scenarios, it may be desired to accurately compute the segment of an object's perimeter that is being viewed by a particular camera, e.g. supporting applications for pattern recognition systems and coverage optimization. As objects may have different formats, generic polygon-based approaches may bring inaccurate results, since some simplifications may be taken. In this context, it is proposed in this paper an algorithm to accurately calculate the objects' contours that can be viewed by a set of cameras, employing a discretization technique. The proposed algorithm computes the percentage of an object's perimeter that is being viewed, which may be used as a parameter of coverage quality. Therefore, besides accurately computing effective viewing of cameras, a visual coverage quality metric for a set of objects is derived, which can be directly exploited for optimizations in camera surveillance systems and visual sensor networks. [ABSTRACT FROM AUTHOR]

This paper focuses on flood-region detection using monitoring images. However, adverse weather affects the outcome of image segmentation methods. In this paper, we present an experimental comparison of an outdoor visual sensing system using region-growing methods with two different growing rules—namely, GrowCut and RegGro. For each growing rule, several tests on adverse weather and lens-stained scenes were performed, taking into account and analyzing different weather conditions with the outdoor visual sensing system. The influence of several weather conditions was analyzed, highlighting their effect on the outdoor visual sensing system with different growing rules. Furthermore, experimental errors and uncertainties obtained with the growing rules were compared. The segmentation accuracy of flood regions yielded by the GrowCut, RegGro, and hybrid methods was 75%, 85%, and 87.7%, respectively [ABSTRACT FROM AUTHOR]