This issue of Proceedings gathers the papers presented at the 3rd International Electronic Conference on Sensors and Applications (ECSA-3), held online on 15–30 November 2016 through the sciforum.net platform developed by MDPI. The annual ECSA conference was initiated in 2014 on an online basis only, to allow the participation from all over the world with no concerns of travel and related expenditures. This type of conference looks particularly appropriate and useful because research concerned with sensors is rapidly growing, and a platform for rapid and direct exchanges about the latest research findings can provide a further burst in the development of novel ideas. Full article

Nowadays, monitoring of people and events is a common matter in the street, in the industry or at home, and acoustic event detection is commonly used. This increases the knowledge of what is happening in the soundscape, and this information encourages any monitoring system to take decisions depending on the measured events. Our research in this field includes, on one hand, smart city applications, which aim is to develop a low cost sensor network for real time noise mapping in the cities, and on the other hand, ambient assisted living applications through audio event recognition at home. This requires acoustic signal processing for event recognition, which is a challenging problem applying feature extraction techniques and machine learning methods. Furthermore, when the techniques come closer to implementation, a complete study of the most suitable platform is needed, taking into account computational complexity of the algorithms and commercial platforms price. In this work, the comparative study of several platforms serving to implement this sensing application is detailed. An FPGA platform is chosen as the optimum proposal considering the application requirements and taking into account time restrictions of the signal processing algorithms. Furthermore, we describe the first approach to the real-time implementation of the feature extraction algorithm on the chosen platform. Full article

In this work, a method to analyze the performance of Bluetooth-based Wireless Sensor Networks (WSN) deployed within hospital environments is presented. Due to the complexity that this kind of scenarios exhibit in terms of radio propagation and coexistence with other wireless communication systems and other potential interference sources, the deployment of WSNs becomes a complex task which requires an in-depth radio planning analysis. For that purpose, simulation results obtained with the aid of an in-house developed 3D Ray Launching code are presented. The scenarios under analysis are located at the Hospital of Navarre Complex (HNC), in the city of Pamplona. As hospitals have a wide variety of scenarios, the analysis has been carried out in different zones such as Boxes, where different medical sensors based on Bluetooth communication protocol have been deployed. The simulation results obtained have been validated with measurements within the scenario under analysis, exhibiting Bluetooth-based WSNs performance within hospital environments in terms of coverage/capacity relations. The proposed methodology can aid in obtaining optimal network configuration and hence performance of Bluetooth-based WSNs within medical/health service provision environments. Full article

Poly-hydroxy-alcanoates (PHAs) are biodegradable and biocompatible polymers synthesized and accumulated in intracellular compartments in several bacterial species. Polyhydroxyalcanoates (PHAs) are synthesized by numerous prokaryotes, such as Cupriavidus necator (Ralstonia eutropha), Pseudomonas spp., Comamonas spp., in response to stress conditions, i.e., under high carbon and low nitrogen (24:1 ratio). PHA can be synthesized using recombinant microorganisms (provided with the operon phbA/phbB/phbC), escaping the constrains of nutrient request, except addition of high amount of sugar (glucose, lactose, fructose). Recombinant E. coli systems were studied to produce PHB using metabolic engineering. In biofermentors, the critical points are the excess of fermentable sugars and the ratio of nutrients versus cell optical density. In order to allow production in biofermentors in automated system, sensors are envisaged to evaluate critical parameters such as sugar consumption, bacteria concentration and level of synthesis of PHA. The need of fermentors and operation control has compelled for application of three biosensing units, one linked to a Nanodrop to evaluate OD, one linked to an enzymatic reaction chamber to measure sugars consumed by enzyme linked sugar biosensing tools, and one for sampling the bacteria, Nile Blue staining, and fluorescence intensity reads. These detectors will make possible to exploit the full potential of bioreactors optimizing the time of use and maximizing the number of bacteria synthesizing PHA. Full article

Extracting tiny amounts of energy from non-conventional sources using Peltier cells, piezoelectrics, antennas or inductive probes has become very popular in recent years to power low-consuming sensors in IoT applications and smart grids. These energy harvesting methods rely on the continuous generation of small quantities of electrical energy scavenged from heat, vibration or electromagnetic emissions. This energy is stored in batteries or capacitors reaching low-voltage levels that cannot be used directly to power any device. In general, the voltage is boosted to more appropriate levels with a converter. Using inductive sensors to harvest energy from electrical power lines is common knowledge. Obtaining this energy from high-power low-frequency signals is currently possible and, in some cases, reliable and profitable. The aim of this paper is to evaluate the possibility of harvesting energy from extremely low-power and high-frequency events that occur in electrical assets when the insulation is damaged. These events, called partial discharges, are used in electrical maintenance to detect possible defects in the insulation. Evaluating partial discharge activity is a common protocol in all utilities that requires the use of expensive sensors and acquisition systems, and in most occasions, decommissioning the asset to connect the measuring system. The energy from these phenomena is stored in capacitors and the use of a high-frequency voltage multiplier allows to reach voltages close to 4 V. This voltage is proportional to the number of partial discharges in a certain time span. Therefore, if the number of partial discharges per time-unit has increased noticeably, the insulation has deteriorated and the asset should be decommissioned to evaluate the damages. The paper tests the possibility of using this method as an early-warning system in the maintenance of electrical assets. Full article

The detection of structure-borne sound can be used to monitor the structural health of solid structures and machine parts. One way to achieve such an implementation is to place vibroacoustic sensors in contact with the structure. The sensors will typically generate an electric signal in response to the acoustic emissions caused by specific events, such as fractures in the structure. In this paper, vibroacoustic sensors were used to detect structure-borne sound during static tensile testing of metallic samples until complete fracture. The samples used were sections of longitudinal beams made of S700 MC steel. Two different types of piezoelectric sensors were used: PVDF film sensors glued to the sample, and ceramic sensors attached to the sample with a magnet adapter. The bandwidth of the signals was expected from previous studies to be of up to 2 MHz. Simultaneously, force and displacement were measured at the testing machine. An algorithm was written to process the data acquired from the piezo elements and automatically detect relevant events via a simple comparison with a pre-defined voltage threshold to detect signals above the background noise level. The comparison of the detected events with the force measurements from the tensile test showed a very strong correlation between actual fractures (both the initial fracture and its posterior propagation) and the automatic classification carried out by the algorithm. Thus, the vibroacoustic sensor could with little calibration substitute the other standard measurement systems. Full article

Wearable sensor technologies are a key component in the design of applications for human activity recognition, in areas like healthcare, sports and safety. In this paper, we present an iterative learning method to classify human locomotion activities extracted from the Opportunity dataset by implementing a data-driven architecture. Data collected by twelve 3D acceleration sensors and seven inertial measurement units are de-noised using a wavelet filter, prior to the extraction of statistical parameters of kinematical features, such as Principal Components Analysis and Singular Value Decomposition of roll, pitch, yaw and the norm of the axial components. A novel approach is proposed to minimize the number of samples required to classify walk, stand, lie and sit human locomotion activities based on these features. The methodology consists in an iterative extraction of the best candidates for building the training dataset. The best training candidates are selected when the Euclidean distance between an input data and its cluster’s centroid is larger than the mean plus the standard deviation of all Euclidean distances between all input data and their corresponding clusters. The resulting datasets are then used to train an SVM multi-class classifier that produces the lowest prediction error. The learning method presented in this paper ensures a high level of robustness to variations in the quality of input data while only using a much lower number of training samples and therefore a much shorter training time, which is an important aspect given the large size of the dataset. Full article

The titanium nitride–aluminum oxide–hafnium oxide–silicon oxide–silicon device using aluminum oxide as charge-blocking layer (hereafter TAHOS) could be a candidate for nonvolatile total ionization dose (TID) radiation sensor. In this paper, gamma radiation induces a significant decrease in the threshold voltage V_T of TAHOS and the radiation-induced V_T decrease on TAHOS is nearly 1.3 times of that on a standard titanium nitride–silicon oxide–hafnium oxide–silicon oxide–silicon device (hereafter TOHOS) device after 5 Mrad TID gamma irradiation. The change in V_T of TAHOS after gamma irradiation also has a strong correlation to TID up to 5 Mrad gamma irradiation. Moreover, the V_T 10yrs retention characteristic of TAHOS device can be markedly improved and is nearly 13% better than that of a standard TOHOS device after 5 Mrad gamma irradiation. Therefore, the TAHOS device in this study has demonstrated the possibility using TAHOS for high TID response and good TID data retention for non-volatile TID radiation sensing. Full article

Due to the increasingly growth in population, it is important to better use natural resources for food production and efficiency, driving the use of sensors each time more to monitor several aspects of the soil and of the crops in the field. However, it is known that the harsh conditions of the field environment demands more robust and energy efficient sensor devices. One example is soil water monitoring for irrigation: Brazil, for example, consumes 69% of its freshwater only for irrigation purposes, which shows the need of using adequate water moisture sensors. Based on that, this work proposes a modular architecture that integrates several sensor technologies, including battery-less sensors and low power sensors for soil moisture measurements, but not limited to them. The proposed system relies on a mobile robot that can locate each deployed sensor autonomously, collect its data and make it available on-line using cloud services. As proof of concept, a low-cost mobile robot is built using a centimeter level accuracy location system, that allows the robot to travel to each sensor and collect their data. The robot is equipped with an UHF antenna to provide power to RF powered battery-less sensors, a Bluetooth low energy data collector and a Zigbee data collector. An experimental evaluation compares reading distance and successful rate of sensor location and reading. Full article

This paper presents a system to estimate soil moisture through the reading of standard Ultra High Frequency (UHF) passive Radio Frequency Identification (RFID) tags that can be buried in the soil, allowing wireless moisture measurement without the need of using batteries in the field for long periods. In the proposed system, one or more passive EPC/GEN2 tags acts as sensors buried in the soil. The system dispenses external cables and antennas and may be composed of a single RFID tag buried in a specific soil depth or by several RFID tags buried at different depths. An antenna coupled to a RFID reader can be pointed to the place of installation of these tags, and by measuring the received signal strength indicator (RSSI) and other variables, direct estimation of the water content can be done. In addition to its simplified installation procedure, the system allows manual and automatic robotic reading through irrigation systems or other systems for irrigation scheduling. Full article

The article describes the results of the project “open source Smart lamp” aimed at designing and developing a smart object able to manage and control the Indoor Environmental Quality (IEQ) of the built environment. A first version of this smart object, built following a DIY approach using a microcontroller, an integrated temperature and relative humidity sensor and techniques of Additive Manufacturing, allows for the adjustment of the Indoor thermal Comfort Quality (ICQ), by interacting directly with the air conditioner. An experimental test in a real office showed how the use of the Smart Lamp effectively reduced energy consumption for air conditioning, optimizing the thermal comfort of the workers. As it is well known, the IEQ is a holistic concept including the Indoor Air Quality (IAQ), the Indoor Lighting Quality (ILQ) and Acoustic comfort, besides the thermal comfort. The upgrade of the Smart Lamp bridges this gap providing the possibility to interact with the air exchange unit and lighting system, in order to get an overview of the potential of a nearable device in the management of the IEQ. The upgraded version was tested in an office equipped with a mechanical ventilation and air conditioning system and occupied by 4 workers. The experiment was compared with a baseline scenario and the results showed how the application of the nearable device effectively optimizes both IAQ and ILQ. Full article

Electrical insulation can have imperfections due to manufacturing or ageing. When the insulation is electrically stressed, partial discharge (PD) pulses, with very fast rise-times and short-time durations, may occur. One of the consequences of charges being accelerated within the discharge is the emission of electromagnetic energy. The measurement of these emissions is widely used to identify defective insulation within high voltage equipment and help in predictive and planned maintenance in order to prevent sudden failure. The location of the source of the radiated PD signals may be determined using multi-lateration techniques using an array of at least four antennas. Depending on the relative position between the antennas and the PD source, the pulsed emissions from the PD source arrive at each antenna at different times. The relative time differences of arrivals (TDOA) together with the antenna positions are variables used to locate the PD source in 3D space. This paper investigates the accuracy of the location determination of the source as a consequence of systematic errors on the positioning of the antennas. These errors are analyzed for three different antenna array configurations and for different vector directions from the arrays. Additionally, the least sensitive layout in relation to antenna positioning errors is proposed to assist in improving the location accuracy of PD sources. Full article

A novel brain imager using whole brain Positron Emission is a portable unit which can be worn on a patient’s head to provide a lightweight, low cost unit which conducts AM-PET (Ambulatory Microdose Positron Emission Tomography) scans in diverse locations and social situations. Such allows the subject to move their head and even walk, called Ambulatory Microdose PET (AMPET). This is also conducive to the testing of patients while performing selected activities that stimulate certain brain regions such as walking, playing a game, clapping and other such tasks; this unit is specifically intended for those with Alzheimer’s, cancer, mental health, or any kind of brain injury to learn more about the nature of these conditions as a basis to identify a potential cure and treatment options. The need for this type of device has led to the design of a portable head held unit that currently uses twelve PET module sensors in specific locations around the head. Current PET scanners need a patient to remain still for several minutes, whereas with this novel unit you can see defined parts of the brain working as the patient moves their head comfortably, even while standing. This manuscript is focused on the engineering design aspects of the Am-PET project. The goal of this work is to further design this portable head unit to alleviate weight of the current head unit, improve comfort for the patient, and diversify its application amongst research activities. Specific gains include the design and manufacture of a system that reduces the relative movement of head and helmet significantly and does not restrict the user’s head motion. The continuation of this work includes design review of the current model, design improvements based on the identified project requirements, and development of a working prototype. The success of this work will be measured by comparing the developed prototype to the original device and the newly developed metrics. Full article

Today sensor data processing and information mining become more and more complex concerning the amount of sensor data to be processed, the data dimension, the data quality, and the relationship between derived information and input data. This is the case especially in large-scale sensing and measuring processes embedded in Cloud environments. Measuring uncertainties, calibration errors, and unreliability of sensors have a significant impact on the derivation quality of suitable information. In the technical and industrial context the raising complexity and distribution of data processing is a special issue. Commonly, information is derived from raw input data by using some kind of mathematical model and functions, but often being incomplete or unknown. If reasoning of statements is primarily desired, Machine Learning can be an alternative. Traditionally, sensor data is acquired and delivered to and processed by a central processing unit. In this paper, the deployment of distributed Machine Learning using mobile Agents forming self-organizing and self-adaptive systems (self-X) is discussed and posing the benefit for the enhancement of the sensor and data processing in technical and industrial systems. This also addresses the quality of the computed statements, e.g., an accurate prediction of run-time parameters like mechanical loads or health conditions, the efficiency, and the reliability in the presence of partial system failures Full article

In wireless sensor networks (WSN) localization of the nodes is relevant, especially for the task of identification of events that occur in the environment being monitored. Thus, positioning of the sensors is essential to satisfy such task. In WSN, sensors use techniques for self-localization based on some reference or anchor nodes (AN) that know their own position in advance. These ANs are fusion centers or nodes with more processing power. Assuming that the number of ANs given in the network is N, we carry out the localization algorithm to position sensors sequentially using those N ANs. Now, when a sensor has been localized, it becomes a new AN, and now, other sensors will use N + 1 ANs, this is repeated until all the sensors in the network have been localized. In this sequential localization algorithm, the positioning error (difference between true and estimated position) increases as the sensor to be located is farther away from the group of original ANs in the network. This error becomes critical when propagation issues such as multipath propagation and shadowing in indoor environments are considered. In this paper, we characterize statistically positioning error in WSN for one-dimensional indoor environments when sensors are deployed randomly. We also evaluate the performance of the localization algorithm and determine correcting factors based on the statistical characterization to minimize positioning error. We present results from simulations and measurements in an indoor environment. Full article

Position location estimation in sensor networks is a valuable supplement since it supports the deployment of location-based services. Sensor networks have changing conditions in the environment due to propagation issues, noise and placement of sensors, which represent challenges that position location algorithms must deal with. Accuracy of the location estimation technique is relevant since it allows minimizing positioning error. In indoor environments, propagation issues such as multipath signals, affect adversely the precision of the positioning algorithm. Also, the use of parameters such as time of arrival has a trade-off between the small distances that the signals traverse and the precision of the hardware used to capture such measurements. In this paper, we use received signal strength indicator (RSSI) to estimate the coordinates of individual sensors in an area of study. The RSSI parameter is measured and processed by a set of reference nodes installed in the area. We show that performance of the location estimation algorithm needs additional techniques to obtain improved accuracy rate. We develop additional techniques based on the use of polynomial interpolation and spline functions to balance propagation issues. These techniques help us to implement correcting factors that are used in the propagation model to compensate the RSSI measurements. We use these techniques to show how the positioning error is reduced in the area of study with simulations and measurements using sensors. Full article

Pokhara, city of lakes, is second largest and most beautiful tourist place in Nepal. Out of seven lakes, the large three: Phewa, Begnas and Rupa are famous for tourist attraction, whereas the rest are small and less known. Lakes are not only economic value, but are also ecological and environmental resources. But, these lakes are facing challenges due to climatic and anthropogenic activities. As these changes are slow and takes long time, the damage unnoticed to take measures. Hence, long historic data provided such as of remote sensors are concrete evidence of change, which help us understand the cause and prevent further change. Landsat series provide the continuous data with high temporal resolution freely to the scientific community. For such data, many simple and low cost index methods has been developed to identify water bodies. In this study, we use these indices to detect the change of lakes in Pokhara city using Landsat data of 25 years gap i.e., 1988–2013. Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Modified NDWI (MNDWI) were investigated for the unsupervised extraction of surface water from Landsat data. A model is developed in ArcGIS by differencing the water bodies derived form index methods and difference were calculated for positive and negative change. The results show that the area of Phewa has shrunken, whereas Rupa being increase in surface water area. Began has few changes and other small lakes except Dipang lake, were not detected. Dipang Lake showed increase in surface water area after 25 years of gap. The result can be helpful in reclaiming and restoration of lake area, preserve and maintain the wetland ecosystem in the city. Also, the model presented in the manuscript can be used for change detection of surface water due to flood, or debris blockages in disaster prone countries. Full article

nEMoS (nano Environmental Monitoring System) is an all-in-one, low-cost, web-connected and 3D-printed device aimed at assessing the Indoor Environmental Quality (IEQ) of buildings. It is built using some low-cost sensors connected to an Arduino microcontroller board. The device is assembled in a small size case and the integrated air temperature and relative humidity sensor and the globe thermometer could be affected by thermal effect due to overheating of some nearby components. A thermographic analysis was made to rule out this possibility. The paper shows how the pervasive technique of Additive Manufacturing can be combined with the more traditional thermographic technique to redesign the case and to verify the accuracy of the optimized system in order to prevent instrumental systematic errors in terms of difference between experimental and actual values of air temperature, relative humidity and radiant temperature. Full article

Vehicular ad hoc Networks (VANETs) enable vehicles to communicate with each other as well as with roadside units (RSUs). Although there is a significant research effort in radio channel modelling focused in vehicle to vehicle (V2V), not much work has been done for vehicle to infrastructure (V2I) using 3D ray-tracing tools. This work evaluates some important parameters of a V2I wireless channel link such as Received Power, Power Delay Profile, Delay Spread and Coherence Bandwidth, in an urban scenario using a deterministic simulation model based on an in-house 3D Ray-Launching algorithm. Analysis using Wireless Sensor Networks (WSNs) at 868MHz, 2.4 and 5.9 GHz are presented. Results show the highly impact that the distance, link frequency, location of RSUs and obstacles in the LoS (Line of Sight) have in V2I channel propagation. These results constitute the start point in the deployment of radio-planning in V2I environments. Full article

PMMA/ZnO/glass structure was investigated to enhance Love mode sensor sentivities. The phase velocities and the attenuation of the acoustic wave propagating along the PMMA/30° tilted c-axis ZnO/glass structure contacting a viscous non-conductive liquid were calculated for different PMMA (Polymethyl methacrylate) and ZnO guiding layer thicknesses, added mass thicknesses, and liquid viscosity and density. The sensor velocity and attenuation sensitivities were also calculated for different environmental parameters. The resulted sensitivities to liquid viscosity and added mass were optimized by adjusting the ZnO and PMMA guiding layer thickness corresponding to a sensitivity peak. The present analysis is of importance in manufacturing and applications of the PMMA-ZnO-glass structure Love wave sensors for the detection of liquids properties, such as viscosity, density and mass anchored to the sensor surface. Full article

The propagation of the first symmetric Lamb mode S₀ along ZnO/a-SiC thin composite plates was modeled and analysed aimed at the design of a sensor able to detect the changes of the environmental parameters, such as added mass in vacuum and the liquid viscosity changes in a viscous liquid medium. The Lamb mode propagation was modeled by numerically solving the system of coupled electro-mechanical field equations in the two media. The S₀ acoustic field profile was calculated aimed at finding the proper plate thickness suitable for the propagation of longitudinally polarized modes. The phase velocity and electroacoustic coupling efficiency dispersion curves of the S₀ mode were calculated aimed at the design of enhanced coupling efficiency devices. The gravimetric sensitivity in vacuum, and the attenuation that the S₀ mode soffers when contacting a liquid viscous Newtonian environment were finally calculated for different ZnO layer thicknesses. Recently obtained results on the sputtering deposition of the a-SiC and ZnO thin and thick layers on Si substrates are also reported. Full article

The realistic representation of deformations is still an active area of research, especially for soft objects whose behavior cannot be simply described in terms of elasticity parameters. Most of existing techniques assume that the parameters describing the object behavior are known a priori based on assumptions on the object material, such as its isotropy or linearity, or values for these parameters are chosen by manual tuning until the results seem plausible. This is a subjective process and cannot be employed where accuracy is expected. This paper proposes a data-driven neural-network-based model for capturing implicitly deformations of a soft object, without requiring any knowledge on the object material. Visual data, in form of 3D point clouds gathered by a Kinect sensor, is collected over an object while forces are exerted by means of the probing tip of a force-torque sensor. A novel approach advantageously combining distance-based clustering, stratified sampling and neural gas-tuned mesh simplification is then proposed to describe the particularities of the deformation. The representation is denser in the region of the deformation (an average of 97% perceptual similarity with the collected data in the deformed area), while still preserving the object overall shape (74% similarity over the entire surface) and only using on average 30% of the number of vertices in the mesh. Full article

The recent advances in sensor technology empower adaptable smart systems targeting safety. Smart sensing in ambient intelligence systems enables to enhance safety during cooking which is very important for aging people. Therefore, we worked on a project of building a smart oven system. We studied the principal risks around oven and analyzed the characteristics and the basic functional principles of the existing sensors to select the most appropriate. In this paper, we present the analysis of the sensors used and the test results of each sensor in a real-world cooking environment. Full article

The determination of the pressures affecting vertical marine structures is far from being completely understood. The prototype instrumentation and testing of large-scale channels provide information useful for defining their behaviour at probabilistic level, but neither the above mentioned methods nor existing methods of calculation are able to respond to complex phenomenon of wave reflection on the vertical docks. Obtained results are based on very simplified principles calibrated in accordance with a scale trials, leading to the overestimation of structures, with the high cost that this entails. This research develops a measurement system that allows studying the laws of pressures acting on vertical docks, optimizing their design and sizing. This system has been placed in the dock of Botafoc (Ibiza, Spain). Measured data has led to new results which are very revealing as to the form of the distributions of the pressures, the influence of the wave period on them, and importance of flows induced by waves through bedding layers. Full article

Surface-enhanced Raman Spectroscopy (SERS) is a vibrational spectroscopy holding potentials for a rapid evaluation of quality and composition of food industry products without any need of sample preparation. Among many nanomaterials, gold nanoparticles (GNPs) and their colloidal dispersions have attracted great interest for SERS applications due to their unique properties of small size, large surface area to volume ratio, high reactivity to the living cells, stability over high temperatures. In this frame, a low-cost substrate, based on home-made 30-nm sized GNPs, has been designed and used for the investigation of commercial fruit juices and pulp. Thanks to the use of a wavelet denoising procedure and background subtraction spectra with clear features have been obtained. Their analysis has enabled to evidence the presence of components of great importance for the quality evaluation of the products, such as fructose and pectin. The overall inspection of the results has confirmed the potentialities of SERS in food industry. Full article

This paper deals with all required parts to set up the full variable valve train (FVVT) system to be used in intake and exhaust valves of combustion engines from the electrical/electronic point of view. This includes the displacement and pressure sensors that are needed to conduct research on the fully variable valve train while in operation and the electronic auxiliaries such as the amplifier for the piezo actuator, the dSPACE control system and the used function generator. In particular, the use of displacement transducers for all relevant pistons and stems is crucial for the FVVT system control. As only the piezo actuator is equipped with a displacement sensor, the remaining sensors still need to be chosen. Within the previous FVVT system two different displacement sensors have been used on the engine valve stem. Three displacement sensors and one pressure sensor are implemented into the mechanical core of the system (consisting of lever transmission, control unit, servo valve and engine valve body), which is driven by the piezo actuator and supplied with hydraulic pressure by a pump, that requires a 230 V power supply and a tank, which the hydraulic fluid can return to. While the pressure sensor monitors the hydraulic pressure within the lever transmission, displacement sensors need to be chosen to monitor the motion of the (1) control piston in the control unit; (2) servo piston within the servo valve; (3) engine valves. Measured results are presented. Full article

Robots are expected to perform complex dexterous operations in a variety of applications such as health and elder care, manufacturing, or high-risk environments. In this context, the most important task is to handle objects, the first step being the ability to recognize objects and their properties by touch. This paper concentrates on the issue of surface recognition by monitoring the interaction between a tactile probe in contact with a surface. A sliding motion is performed by a robot finger (i.e., kinematic chain composed of 3 motors) carrying the tactile probe on its end. The probe comprises a 9-DOF MEMs MARG (Magnetic, Angular Rate, and Gravity) sensor and a deep MEMs pressure (barometer) sensor, both embedded in a flexible compliant structure. The sensors are placed such that, when the tip is rubbed over a surface, the MARG unit vibrates and the deep pressure sensor captures the overall normal force exerted. The tactile probe collects data over seven synthetic shapes (profiles). The proposed method to distinguish them, in frequency and time domain, consists of applying multiscale principal components analysis prior to the classification with a multilayer neural network. The achieved classification accuracies of 85.1% to 98.9% for the various sensor types demonstrate the usefulness of traditional MEMs as tactile sensors embedded into flexible substrates. Full article

The need for an efficient Water Management System (WMS) is strongly felt by water utilities, municipalities and by medium to large scale corporates that have to face every day with problems dealing with water usage and supply Leveraging a sensor data network, an automated system to implement fault detection in a water network at an early stage can be a valuable tool that saves water, energy, time and money. This paper introduces a novel FDD (fault detection and diagnosis) approach for water networks developed within the FP7 Waternomics Project by modeling a water network in the simulation environment EPANET and applying an anomaly detection algorithm named ADWICE (Anomaly Detection With fast Incremental ClustEring) to real time data of water flow and pressure to infer performance and operational anomalies. The method is currently being implemented at the Linate Airport water network in Milan, and initial results are presented in this paper. Full article

Nowadays many studies are conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is applied in order to provide solutions for mobility related problems in cities. The interconnected traffic lights controllers (TLC) network adapts traffic lights cycles, based on traffic and air pollution information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease of the pollution level. Then the problem becomes more complex. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach has been followed as design method and a distributed consensus-based control algorithm has been applied. The applied control law contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Furthermore, Discrete Event Systems Specification (DEVS) formalism is applied for modelling and simulation purpose. The proposed solution has been tested and validated in a simulated environment corroborating that the proposed solution is a powerful technique to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks. Full article

Two novel dicyanovinyl derivatives 3a–b were synthesized in moderate to good yields through a Knoevenagel reaction of the corresponding aldehyde precursors and malononitrile. The photophysical properties of the new push-pull systems were studied by UV-vis and fluorescence spectroscopy in acetonitrile. The evaluation of the compounds as colorimetric chemosensors was carried out by performing spectrophotometric titrations in acetonitrile and acetonitrile/water in the presence of relevant organic and inorganic anions, and of alkaline, alkaline-earth and transition metal cations. The benzoindole derivative exhibited great selectivity for the cyanide anion over other anions in acetonitrile/water (8:2) solution showing a distinct color change from colorless to yellow. Full article

Compliance in robotic systems has been exploited to allow rigid mechanisms to come into contact with complex and possibly fragile objects. By incorporating compliance and instrumentation into a single device nearby objects can be detected before direct contact occurs. That way, safer and smoother robot guidance can be achieved both while approaching and while touching surfaces. Furthermore, the path planning and control problem is simplified as position based algorithms can be used regardless of the state of the system, be it in free motion or constrained motion, or even during transitions between the two modes. This paper presents the design and experimental validation of a lightweight, low-cost and stand-alone instrumented compliant wrist mechanism which can be mounted on the tool plate of any rigid robotic manipulator. Embedded arrays of infrared sensors provide distance measurements. Each is finely tuned via a novel calibration procedure that overcomes inter-sensor variability. All signal processing is also embedded and wireless transmission connects the device to the robot controller to support path control. Real-time acquired measurements on the position and orientation of surfaces located in close proximity or in contact with the robot’s end effector permit close guidance of its operation. Experimental work demonstrates how the device provides physical compliance to prevent large impact forces to occur during non-contact to contact transitions by the manipulator’s end effector. It also demonstrates the stability and accuracy of the device outputs. Primary applications of the proposed instrumented compliant wrist include smooth surface following in manufacturing and safe human-robot interaction. Full article

Modal Analysis is an experimental technique widely used to determine the dynamic response of structures. One of the most critical part is the selection of the actuator that will excite the tested structure. In many cases, traditional exciters, such as hammers and shakers, have been used for this purpose. Nevertheless, these exciters may have the disadvantage of modifying the modal parameters (as reported in some cases) and they are difficult to be used when the structure is not accessible (confined and/or submerged). For these cases PZT-patches, that are very light structures (compared to the tested structure), have been recently used as exciters. Although, in the analyzed studies the natural frequencies of the structure have been determined using PZTs, the rest of parameters that determine the FRF (Frequency response Function) have been not obtained. This could be, because the calibration of PZTs as dynamic force transducers is a complicated task and not an information given by the manufacturers, as in other exciters used for the same purpose. This paper analyzes experimentally and analytically the use of PZT-patches as exciters for modal analysis. For this purpose, a tested structure is excited in different ways with a PZT and its response is compared with a reference case, obtained with a classical exciter. Analyses show how to obtain different modal parameters that determine the FRF of the structure, without previous calibration of the PZT. Finally, and in order to show the potential advantages of these exciters for inaccessible structures, the procedure is repeated for the same structure submerged in water, showing that PZT are much more appropriated exciters in these cases. Full article

This paper presents the design, manufacturing and testing of a Dual Accelerometer Vector Sensor (DAVS). The device was built within the activities of the WiMust project, a EU project, supported under the Horizon 2020 Framework Programme, which aims to improve the efficiency of the methodologies used to perform geophysical acoustic surveys at sea by the use of Autonomous Underwater Vehicles (AUVs). The DAVS contributes to this aim in various ways, for example, owing to its spatial filtering capability, it can measure reflections at the desired direction therefore reducing the amount of post processing related to deghosting and multipath removal. Also its compact size allows easier integration with AUVs and hence facilitates the vehicle manoeuvrability compared to the classical towed arrays. The DAVS device consists of two tri-axial accelerometers and one hydrophone moulded in one unit. The device’s directional estimation capabilities were evaluated on an AUV, which was sailing around a deployed sound source. Results of this experiment are presented in this paper. Full article

SPR technique possesses rich potential possibilities for investigation of different aspects of virus-specific agent interaction and modification of structure of viruses, induced by external factors. Аccording to World Health Organization, viruses of Herpesviridae family infect 90% of the Earth’s population. Herpetic infection is urgent for several spheres of medicine: infectology, infectious neurology, transplanthology, haemotology. It is perspective today using of biosensor technologies for developing of diagnostic systems. The aim of this work is develop and characteristics of biosensor chips for detection specific antibodies to herpes simplex virus and Epstein-Barr virus in patients’ blood sera. The study was performed using the device “Plasmon-6”, which is a computer-controlled optoelectronic spectrometer, which uses the SPR phenomenon in the optical configuration Kretschmann. It is developed at the Institute of Semiconductor Physics NAS of Ukraine. The advantage of this device is a compact design; full record of kinetic dependence; the minimum of one measurement: 0.2 s (mode slope); measurement in the gas or liquid; additional analog channel. We used additional channel as a control one. This allowed neutralize influences of environmental (temperature, humidity and another) at its operation. As antigens used purified proteins of viruses derived from cell cultures. The selection of sera was carried out using test kits “HSV-1 IgG ELISA” and «EBV VCA IgG ELISA» (GenWay, San Diego, CA, USA). Immobilization of viral proteins on sensor surface was performed using 0.2% solution of Dextran 17 000 (Sigma, St Louis, MO, USA). It was found direct dependence between amount of immobilized antigen and SPR response. The immobilization 8 × 10⁻⁵ mg/mm² of viral proteins on the surface of the chip was optimal for detection of antibodies. About 200 samples positive and negative blood sera of patients were tested who were previously tested by ELISA and created combined pools with varying degrees load of antibodies to studied virus. The limits of positive and negative response for SPR analysis was determined by using panel of negative blood sera of donors. SPR data were agreed with ELISA results in 84% of samples. The reproducibility of results varied between 85% and 95%. Thus, in this study biosensor chip for detection of specific antibodies to HSV-1 and EBV was successfully developed for express diagnostic of these pathogens. Full article

Load-bearing engineering structures typically have a static shape fixed during design based on expected usage and associated load cases. But neither can all possible loading situations be foreseen, nor could this large set of conditions be reflected in a practical design methodology—and even if either was possible, the result could only be the best compromise and thus deviate significantly from the optimum solution for any specific load case. In contrast, a structure that could change its local properties in service based on the identified loading situation could potentially raise additional weight saving potentials and thus support lightweight design, and in consequence, sustainability. Materials of this kind would necessarily exhibit a cellular architecture consisting of active cells with sensing and actuation capabilities. Suitable control mechanisms both in terms of algorithms and hardware units would form an integral part of these. A major issue in this context is correlated control of actuators and informational organization meeting real-time and and robustness requirements. In this respect, the present study discusses a two-stage approach combining mobile & reactive Multi-agent Systems (MAS) and Machine Learning. While MAS will negotiate property redistribution, machine learning shall recognise known load cases and suggest matching property fields directly. Full article

A novel and highly sensitive non-enzymatic glucose biosensor was developed by nucleating colloidal silver nanoparticles (Ag NPs) on MoS₂. The facile fabrication method, high reproducibility (97.5%) and stability indicates a promising capability for large-scale manufacturing. Additionally, the excellent sensitivity (9044.6 μA·mM⁻¹·cm⁻²), low detection limit (0.03 μM), appropriate linear range of 0.1–1000 μM, and high selectivity, suggests that this biosensor has a great potential to be applied for noninvasive glucose detection in human body fluids, such as sweat and saliva. Full article

Autonomous indoor service robots use the same passages which are used by people for navigation to specific areas. These robots are equipped with visual sensors, laser or sonar based range estimation sensors to avoid collision with obstacles, people, and other moving robots. However, these sensors have a limited range and are often installed at a lower height (mostly near the robot base) which limits the detection of far-off obstacles. In addition, these sensors are positioned to see forward, and robot is often ’blind’ about objects (ex. people and robots) moving behind the robot which increases the chances of collision. In places like warehouses, the passages are often narrow which can cause deadlocks. We propose to use a network of external cameras fixed on the ceiling (ex. surveillance cameras) to guide the robots by informing about moving obstacles from behind and far-off regions. This enables the robot to have a ’birds-eye view’ of the navigation space which enables it to take decisions in real-time to avoid the obstacles efficiently. The camera sensor network is also able to notify the robots about moving obstacles around blind-turns. A mutex based resource sharing scheme in camera sensor network is proposed which allows multiple robots to intelligently share narrow passages through which only one of the robots/person can pass at a given time. Experimental results in simulation and real scenarios show that the proposed method is effective in robot navigation in crowded and narrow passages. Full article

Breath analysis is a powerful technique for detection of respiratory diseases, including asthma and chronic obstructive pulmonary disease (COPD). Nitric oxide (NO), nitrous oxide (N₂O), carbon dioxide (CO₂) and carbon monoxide (CO) present in breath sample acts a marker for respiratory disease. A system is proposed to design a Breath Analyser instrument. Its subsystems consist of a compact fast response laser system for analysis of multiple gases by infrared absorption. For quantitative analysis of trace gases in human breath, patient’s breath sample is collected inside a gas chamber. Two ends of gas chamber are mounted with concave mirrors with special type of mirror holders which have two angle adjustment piezo actuators. Angle adjustment piezo actuators are used to compensate for any angular misalignment in order of micro radians. Third piezo actuator is used for expansion of laser resonator. Special mirror holder consists of three plates which are supported with guide pins. Mirror is mounted on tilt plate which can be rotated in vertical and horizontal direction with the help of two piezo actuators. This mirror holder structure is made of stainless steel and can be used in any type of air and vacuum environment. It is found that for linear misalignment given to any mirror of optical cavity, the angular misalignment exists and vice versa. Thus artifact elimination of laser cavity is sensitive process. With three piezo actuator based special mirror holders, a precise measurement of laser absorption can be done. Full article

Microelectromechanical systems (MEMS) have been already successfully commercialized for around 20 years. The design of novel MEMS sensors currently targets two important features: smaller dimensions and higher reliability. As the characteristic size of the mechanical components of the devices decreases, uncertainties in the mechanical and geometrical properties induced by the microfabrication process become more and more important. To address these issues, an on-chip testing device has been proposed to avoid any visual inspection for the read-out. The electromechanical responses of ten nominally identical specimens have been recorded, and experimental data have shown a significant scattering due to the presence of relevant uncertainty sources. To interpret the response of the device, an analytical reduced-order model of the whole device has been developed. A genetic algorithm has then been adopted to identify features of the mechanical and geometrical uncertainties in the batch of test structures. Full article

In former studies, we proposed a topology optimization approach to maximize the sensitivity to damage of measurements collected through a network of sensors deployed over flexible, thin plates. Within such frame, damage must be intended as a change of the structural health characterized by a reduction of the relevant load-carrying capacity. By properly comparing the response of the healthy, undamaged structure and the response of the damaged one, independently of the location of the source of damage, a procedure to optimally deploy a given set of sensors was provided. In this work we extend the aforementioned approach within a multiscale frame, to account for (at least) three different length-scales: a macroscopic one, linked to the dimensions of the structure to be monitored; a mesoscopic one, linked to the characteristic size of the damaged region(s); a microscopic one, linked to the size of inertial microelectromechanical systems (MEMS) to be used within a marginally invasive health monitoring system. Results are provided for a square plate fully clamped along its border, to show how the micro-sensors are to be deployed to maximize the sensitivity of measurements to damage, and to also discuss the speedup obtained with the proposed multiscale approach in comparison with a standard single-scale one. Full article

Sensors networks for the health monitoring of structural systems ought to be designed to render both accurate estimations of the relevant mechanical parameters and an affordable experimental setup. Therefore, the number, type and location of the sensors have to be chosen so that the uncertainties related to the estimated health are minimized. Several deterministic methods based on the sensitivity of measures with respect to the parameters to be tuned are widely used. Despite their low computational cost, these methods do not take into account the uncertainties related to the measurement process. In former studies, a method based on the maximization of the information associated with the available measurements has been proposed and the use of approximate solutions has been extensively discussed. Here we propose a robust numerical procedure to solve the optimization problem: in order to reduce the computational cost of the overall procedure, Polynomial Chaos Expansion and a stochastic optimization method are employed. The method is applied to a flexible plate. First of all, we investigate how the information changes with the number of sensors; then we analyze the effect of choosing different types of sensors (with their relevant accuracy) on the information provided by the structural health monitoring system. Full article

We propose the design of an environment-responsive, deployable origami-inspired structure to be used as a smart building skin. The folding structure is composed by rigid panels connected to each other through hinge-like connectors. The overall degree of openness of the whole structure is adjusted in response to variations of environmental parameters like lighting and temperature, recorded by a network of embedded sensors. The geometry and kinematics of the origami are selected so as the deployment of each module can be induced at some key points that only slide along a linear axis; in this way, electric motors with a positional control logic can prove efficient. By properly tuning the properties of each panel mounted on the frames, the proposed solution can be adopted as a shading or light refraction system, thus improving the comfort of the building interiors. Through digital prototyping and small-scale models, the effectiveness of the proposed solution is assessed. Some site-specific applications are finally discussed from the self-sensing, self-actuation and self-powering viewpoints. Full article

In this talk, we demonstrate the realization of smart sensors and actuators through the exploitation of principles of nonlinear dynamics at the micro scale. Specifically, we demonstrate combining sensing and actuation into a single device through what is called smart switches triggered by the detection of a desirable physical quantity. The concept aims to reduce the complexity of systems that rely on controllers and complex algorithms to realize on-demand trigger actions. In the first part of the talk, we discuss the category of switches triggered by the detection of gas. Toward this, electrostatically microbeams resonators are fabricated, then coated with highly absorbent polymers (MOFs), and afterward are exposed to gases. Such devices can be useful for instant alarming of toxic gases. In the second part, we demonstrate switches triggered by shock and acceleration. The concept is demonstrated on a millimeter-scale capacitive sensor. The sensor is tested using acceleration generated from shakers. Such devices can be used for the deployment of airbags in automobiles. Full article

The advent of Internet of Things and the evolution of wireless communication systems (towards 4G and 5G systems, as well as wireless sensor networks) is leading towards the implementation of context aware environments. The adoption of such scenarios requires intensive effort in order to optimize coverage/capacity relations, reducing interference and hence, providing optimal Quality of Service and minimum energy consumption. In this work, some of these challenges in relation with wireless system integration, as well as Context Aware scenario examples will be described. Full article

The objective of this article was to compare the performance of two vegetation indices (MODIS EVI (optical) and AMSR-E/ and TMI/TRMM LPRM VOD (microwave)) using an offline Bayesian change-point algorithm to monitor vegetation dynamics (retrospective analysis). We tested this model by simulating 8-day EVI and VOD time series with varying amounts of seasonality, noise, length of the time series and by adding abrupt changes with different magnitudes. This model was applied over real time series (optical and microwave) over a dry forest area in Argentina, Dry Chaco Forest (DCF), where deforestation was common. A comparison with common model used over this region was made (visual inspection). The results compared favorably with Redaf dataset, based on Landsat images. These results show the potential to combine optical and passive microwave indices to identify disturb event. Furthermore, the results obtained in this manuscript were relevant for the DCF region, since they provide a fast and alternative model to the traditional visual analysis made by the national forest service and Redaf. Full article