Sensors and Sensing Research Papers (original) (raw)

- by
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- Sensors and Sensing, Materials Characterisation
- by Ahmet Hakan Turhan
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- Sensors and Sensing
- by Ahmet Hakan Turhan
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- Sensors and Sensing

The aim of this work is to present a model capable to describe the behaviour of a thermal flow sensor under every physical aspect.
Those devices contains a resistive element biased with an external current to locally increase the temperature, surrounded by one or more temperature sensing elements.
The analysis involves three different and coupled physic domains: electric current, heat transfer in solids and laminar flow.
Once the model was ready, it has been used to model an existing SOI CMOS MEMS wall shear stress sensor. The results shows a perfect agreement with the experimental data under every condition, proving the validity of the model.

- by Andrea De Luca
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- Sensors and Sensing
- by Marcos A L Nobre
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- Materials Science, Sensors and Sensing, Sintering, High Temperature Ceramics
- by M Yunus
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- Sensors and Sensing, Precision Agriculture, Wireless Sensor Networks, Agriculture

This paper presents the design, sensing principles and in vitro evaluation of a novel instrumented sock intended for prediction and prevention of acute decompensated heart failure. The sock contains a drift-free ankle size sensor and a leg tissue elasticity sensor. Both sensors are inexpensive and developed using innovative new sensing ideas. Preliminary tests with the sensor prototypes show promising results: The ankle size sensor is capable of measuring 1 mm changes in ankle diameter and the tissue elasticity sensor can detect 0.15 MPa differences in elasticity. A low-profile instrumented sock prototype with these two sensors has been successfully fabricated and will be evaluated in the future in an IRB-approved human study.

- by Song Zhang
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- Sensors and Sensing, Electronics, Digital Signal Processing, Wearable Technologies

Recently, a novel approach to a highly sensitive and quantitative detection of rare earth element (REE) ions including La3+, Eu3+ and Tb3+, by the polymerase chain reaction (PCR) technique, has been reported. The detection of REE ions is based on the catalytic nature of REE ions targeting the deoxyribonucleic acid (DNA), thus monitoring of the ions can be achieved by reading the level of intact DNA by PCR. Despite of its high sensitivity (at ppb to ppt levels), the conventional PCR-based REE detection protocol requires certain length of time (1-2 hours). In the present study, we modified the PCR-based REE detection protocols by employing the high-speed PCR, and performed the automated and rapid detection of La3+ in small-sized aqueous samples within 5min.

- by Tomonori Kawano
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- Environmental Engineering, Biochemistry, Marine Biology, Microbiology

In cases when the information being collected and processed originates by a multi-sensor system, one has to be aware of the impact of the approaches followed in designing the overall system behavior. Typically, there are many steps involved in processing sensory information, from the time a real-world event takes place until the information that describes it and captures its semantics is stored and is available for further exploitation. It this paper we analyze and discuss the options available in the design phase while we underline their respective strengths and weaknesses. The main contribution of the paper lies in the analysis of the factors that affect the behavior and performance of an information system responsible for fusing and integrating sensory information. The main components that constitute such systems are presented in depth, while every choice and the respective effects are discussed in an organized and complete manner.

- by Nikolaos Konstantinou
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- Sensors and Sensing, Semantic Web, RDF

(1) Background: Since early yield prediction is relevant for resource requirements of harvesting and marketing in the whole fruit industry, this paper presents a new approach of using image analysis and tree canopy features to predict early yield with artificial neural networks (ANN); (2) Methods: Two back propagation neural network (BPNN) models were developed for the early period after natural fruit drop in June and the ripening period, respectively. Within the same periods, images of apple cv. " Gala " trees were captured from an orchard near Bonn, Germany. Two sample sets were developed to train and test models; each set included 150 samples from the 2009 and 2010 growing season. For each sample (each canopy image), pixels were segmented into fruit, foliage, and background using image segmentation. The four features extracted from the data set for the canopy were: total cross-sectional area of fruits, fruit number, total cross-section area of small fruits, and cross-sectional area of foliage, and were used as inputs. With the actual weighted yield per tree as a target, BPNN was employed to learn their mutual relationship as a prerequisite to develop the prediction; (3) Results: For the developed BPNN model of the early period after June drop, correlation coefficients (R 2) between the estimated and the actual weighted yield, mean forecast error (MFE), mean absolute percentage error (MAPE), and root mean square error (RMSE) were 0.81, −0.05, 10.7%, 2.34 kg/tree, respectively. For the model of the ripening period, these measures were 0.83, −0.03, 8.9%, 2.3 kg/tree, respectively. In 2011, the two previously developed models were used to predict apple yield. The RMSE and R 2 values between the estimated and harvested apple yield were 2.6 kg/tree and 0.62 for the early period (small, green fruit) and improved near harvest (red, large fruit) to 2.5 kg/tree and 0.75 for a tree with ca. 18 kg yield per tree. For further method verification, the cv. " Pinova " apple trees were used as another variety in 2012 to develop the BPNN prediction model for the early period after June drop. The model was used in 2013, which gave similar results as those found with cv. " Gala " ; (4) Conclusion: Overall, the results showed in this research that the proposed estimation models performed accurately using canopy and fruit features using image analysis algorithms.

- by Michael Blanke
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- Horticulture, Sensors and Sensing, Digital Image Processing, Fruit Science
- by Piero Zappi
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- Air Quality, Sensors and Sensing, Public Health, Pervasive Health

The aim of our research work was to quantify total flavonoid contents in the leaves of 13 plant species family Asteraceae, 8 representatives of family Lamiaceae and 9 plant species belonging to family Rosaceae, using the multiplex fluorimetric sensor. Fluorescence was measured using optical fluorescence apparatus Multiplex(R) 3 (Force-A, France) for non-destructive flavonoids estimation. The content of total flavonoids was estimated by FLAV index (expressed in relative units), that is deduced from flavonoids UV absorbing properties. Among observed plant species, the highest amount of total flavonoids has been found in leaves of Helianthus multiflorus (1.65 RU) and Echinops ritro (1.27 RU), Rudbeckia fulgida (1.13 RU) belonging to the family Asteraceae. Lowest flavonoid content has been observed in the leaves of marigold (Calendula officinalis) (0.14 RU) also belonging to family Asteraceae. The highest content of flavonoids among experimental plants of family Rosaceae has been estima...

- by Oksana Sytar
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- Sensors and Sensing, Biology, Medicinal Plants, Flavonoids

Poly(m-aminophenol)/amine groups functionalized multi-walled carbon nanotube composite was prepared by in-situ chemical polymerization and the film of the nanocomposite have been demonstrated as chemo-resistive sensor for ethanol. The functionalization of nanotube and the interfacial interaction between the poly(m-aminophenol) and functionalized nanotube within their composite was confirmed by Fourier transform infrared spectroscopy, X-beam photoelectron spectroscopy and Raman spectroscopy. Formation of polymer layers on the surfaces of nanotube was demonstrated form the morphological analysis of the nanocomposite by scanning electron microscopy and transmission electron microscopy. The percentage of functionalized nanotube was optimized as 2 wt% within the polymer matrix in terms of highest average DC-conductivity achieved as 32×10 −2 S cm −1 for that composition. The responses of nanocomposite with optimized composition toward various aliphatic alcohols vapor under dynamic flow with air were examined. The good response times and reasonable recovery times with significantly selective response for ethanol vapor was recorded.

In this paper, we have described a whole new approach of rationalization of existing traffic control systems by means of Fuzzy logic based control system and Vision sensors based vehicle counting method. As Conventional traffic control systems are inefficient because they provide fixed time-delay though no vehicle is present in that lane. So it results in congestion of vehicles on the adjacent side. And it generates the Noise and Air pollution, which is undesirable and not favorable. In an Intelligent traffic control system (ITCS), vision sensors will measure the number of vehicles on arrival as well as on queue side, and fuzzy logic rule based system will provide the rational time-delay, which is dependent on vehicle density on both arrival and queue side. So it will give zero delays if no vehicle is present in that lane. So ITCS works with intelligence given by the Fuzzy logic system.

In this study was investigated the effect of manure
and cocoa shell biomass addition on soil chemical
properties and microflora, when the above mentioned
organic materials areused in different proportions in
soil mixtures. For this reason different amounts (0.2,
0.4, and 0.6g) of air dried cocoa beans residue, were
mixed with 50g of soil and 5.0g of manure. The
control mixtures that contained only soil and manure
as well as the mixtures which contained different
amount of cocoa shells, were placed in incubator at
28oC for a period of 21 weeks. The organic matter
and the concentration of nutrient elements in the soil,
manure, cocoa shells biomass and in their mixtures,
were measured before and after the incubation
period. The results showed that the addition of more
than 1% of cocoa shell biomass to soil-manure
mixtures, may influence the mineralization of N, C
and K, and reduce the time needed for mixtures
maturation. The higher organic P content measured
in mixtures contained lower than 1% cocoa shell
biomasswhere the microbial activity was still high.
However the concentration of the available P was not
affected from the addition of cocoa shell biomass to
the soil-manure mixtures.

- by Christos Lykas and +1
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- Sensors and Sensing, Landscape Architecture, Plant Nutrition, Floriculture

The upcoming summit aims to examine how sensor systems support
sustainability and how emerging artificial intelligence (AI)-based processing
methods can help with that. This includes the sensors themselves
and the accompanying architectures, infrastructure, and systems necessary
for creating value, such as communications, computing, data storage,
and power. A further objective is to uncover opportunities and challenges
for such sensor systems across various applications in environments ranging from space to mobile platforms, such as automobiles and unmanned aerial vehicles, ground-based rural and urban settings, and widely deployed
personal mobile devices.

- by Adam Drobot
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- Artificial Intelligence, Sensors and Sensing, Machine Learning, Green Computing

Understanding animal emotions is a key to unlocking methods for improving animal welfare. Currently there are no ‘benchmarks’ or any scientific assessments available for measuring and quantifying the emotional responses of farm animals. Using sensors to collect biometric data as a means of measuring animal emotions is a topic of growing interest in agricultural technology. Here we reviewed several aspects of the use of sensor-based approaches in monitoring animal emotions, beginning with an introduction on animal emotions. Then we reviewed some of the available technological systems for analyzing animal emotions. These systems include a variety of sensors, the algorithms used to process biometric data taken from these sensors, facial expression, and sound analysis. We conclude that a single emotional expression measurement based on either the facial feature of animals or the physiological functions cannot show accurately the farm animal’s emotional changes, and hence compound expression recognition measurement is required. We propose some novel ways to combine sensor technologies through sensor fusion into efficient systems for monitoring and measuring the animals’ compound expression of emotions. Finally, we explore future perspectives in the field, including challenges and opportunities.

- by Suresh Neethirajan
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- Sensors and Sensing, Animal Welfare, Animal health, Digital farming

This publication presents a method responsible for counting tracking and monitoring visitors inside a building. The site examined is Manos Hatzidakis' House, situated in Xanthi. Specifically, we have conducted a study, which provides recommendations, regarding the installation of sensors in the building. We also present the communication protocols of the computer network used in order to ensure the efficient communication between the space examined and the sensor network. Finally, we describe the process of creating a website, which is designed to store and view the data.

- by Alexandros Gazis
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- Remote Sensing, Sensors and Sensing, Sensor, Wireless Sensor Networks

The development of systems capable of recognizing and categorising emotions is of interest to researchers in various scientific areas including artificial intelligence. The traditional notion that emotions and rationality are two separate realms has gradually been challenged. The work of neurologists has shown the strong relationship between emotional episodes and the way humans think and act. Furthermore, emotions not only regulate human decisions but could also contribute to a more satisfactory response to the environment, i.e., faster and more precise actions. In this paper an analysis of physiological signals employed in real-time emotion detection is presented in the context of Intelligent Inhabited Environments (IIE). Two studies were performed to investigate whether physical exertion has a significant effect on bodily signals stemming from emotional episodes with subjects having various degrees of affect intensity: 1) a statistical analysis using the Wilcoxon Test, and 2) a cluster analysis using the Davies- Bouldin Index. Preliminary results demonstrated that the heart rate and skin resistance consistently showed similar changes regardless of the physical stimuli while blood volume pressure did not show a significant change. It was also found that neither physical stress nor affect intensity played a role in the separation of neutral and non-neutral emotional states.

- by Victor Callaghan and +1
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- Instrumentation Engineering, Bioinformatics, Physiology, Human Physiology

The paper stands for a layered architecture approach of the sensor software component stack for the Internet of Things applications. A well-defined architecture is one of the key success factors for a project, as it improves the maintainability, reusability, and other things related to the efficiency in software development. The concept is inspired by the AUTomotive Open System ARchitecture (AUTOSAR) approach of the Software component Development with the proposal to extend the architecture with the Sensor and Actuator component stacks as parts of so named, here, Extended Software (ESW). The first part presents a generic architecture for an IoT device, following with a generic software component stack proposal, applied for any component from the proposed architecture, going through the description of all layers from the Service down to Hardware abstraction, with an implementation proposal, also covering the HW/SW association. In the end, an architecture example for environmental data acquisition is presented.

The 𝐀𝐗 = 𝐘𝐁 sensor calibration problem is very important in multiple fields such as robotics, computer vision or machine vision. In this type of problem, 𝐀 and 𝐁 are parameterizations of rigid body motions, while 𝐗 and 𝐘 is an unknown’s transformations. This research proposes a new approach for solving the 𝐀𝐗 = 𝐘𝐁 sensor calibration problem by mapping the 𝑺𝑬𝟑 classic formulation into an orthogonal dual tensors set representation. Using an isomorphism between 𝑺𝑬𝟑 and an orthogonal dual tensors set , these solutions are free of coordinates and can easily be put into practice.

- by Daniel Condurache
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- Robotics, Sensors and Sensing, Mechatronics, Model Calibration

Overlapping is one of the topics in wireless sensor networks that is considered by researchers in the last decades. An appropriate overlapping management system can prolong network lifetime and decrease network recovery time. This paper proposes an intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks, called IKOCP. This protocol uses some of the intelligent and knowledge‐based systems to construct a robust overlapping strategy for sensor networks. The overall network is partitioned to several regions by a proposed multicriteria decision‐making controller to monitor both small‐scale and large‐scale areas. Each region is managed by a sink, where the whole network is managed by a base station. The sensor nodes are categorized by various clusters using the low‐energy adaptive clustering hierarchy (LEACH)‐improved protocol in a way that the value of p is defined by a proposed support vector machine–based mechanism. A proposed fuzzy system determines that noncluster heads associate with several clusters in order to manage overlapping conditions over the network. Cluster heads are changed into clusters in a period by a suggested utility function. Since network lifetime should be prolonged and network traffic should be alleviated, a data aggregation mechanism is proposed to transmit only crucial data packets from cluster heads to sinks. Cluster heads apply a weighted criteria matrix to perform an inner‐cluster routing for transmitting data packets to sinks. Simulation results demonstrate that the proposed protocol surpasses the existing methods in terms of the number of alive nodes, network lifetime, average time to recover, dead time of first node, and dead time of last node.

- by Mohammad Samadi
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- Sensors and Sensing, Data Mining, Sensor, Clustering and Classification Methods

Ficha técnica realizada para el sensor SQUID aplicado en ingeniería biomédica

- by youssef cheddadi
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- Computer Science, Photovoltaics, Sensors and Sensing, Embedded Systems

This paper introduces novel sensors based on the combination of planar meander and interdigital electromagnetic sensors for monitoring the level of contamination in water sources. A series of experiments was conducted to determine the sensors characteristics.Two nitrates forms, namely sodium nitrates and ammonium nitrates, were mixed in several different ratios dissolved in 1 L of distilled water and were used to observe the response of the sensors. Initial results show that the sensors can detect very well the presence of nitrate added in distilled water. Furthermore, the contamination level of water samples which were taken from various sources and locations in New Zealand have been determined using the sensor, and the results was compared with the results obtained using nuclear magnetic resonance (NMR) technique. The outcomes show a very good correlation of contamination level with the output response of the sensor. The work and improvement for future consideration are discussed in this paper.

Sensor air yang digunakan pada rangkaian ini dapat dibuat menggunakan PCB yang dibuat jalur seperti yang ditunjukkan pada gambar dengan menyablon jalur berdekatan antara masukan dan keluaran. Masukan dihubungkan dengan pin ATMega8, sedangkan keluaran dihubungkan dengan ground. Prinsip penting dari sensor ini adalah ketika sensor terkena air hujan maka jalur antara masukan dan keluaran akan terhubung, sehingga nilai tegangan di pin ATMega8 akan bernilai nol karena langsung ter-ground-kan. sensor hujan adalah alat yang mudah untuk mendeteksi hujan. Sensor ini dapat digunakan sebagai saklar ketika hujan jatuh melalui papan hujan dan juga untuk mengukur intensitas curah hujan. Output analog digunakan dalam pendeteksi tetes hujan berbentuk jumlah curah hujan.

- by Bang Egon
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- Remote Sensing, Sensors and Sensing, Sensor, Wireless Sensor Networks
- by Gijs Krijnen and +1
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- Sensors and Sensing, Biomimetics, Biomimicry, MEMS design: Sensors and Actuators

The use of mobile interactive technology, in museum settings, has the potential of providing young audiences engaging and enjoyable learning activities. As museum visitors are increasingly looking for entertaining experiences inside museums, the dichotomy between learning and entertainment is blurring. In this paper, we present the Ocean Game, a treasure-hunt based mobile game in which 9-10 years old children search and collect a plethora of marine animals and learn about their key characteristics in the context of the Natural History Museum of Funchal (NHMF), Portugal. In this study, our aim was to fuse engagement and entertainment by offering a gaming experience in line with the learning goals of the museum. To evaluate the overall enjoyment and the information that was gained by the children, we compared the performance of players that were engaged with the Ocean Game with the performance of children taking a traditional guided tour. Analysis of the data supports our initial supposition, as children preferred to explore and enjoy the museum space through a gamified approach. Nevertheless, several shortcomings were found in the informal learning aspects of the game. Discussion and future work sections will tackle next steps regarding these issues.

- by Vanessa Cesário, PhD
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- Sensors and Sensing, Mobile Learning, Children's Media, Museums

Non-destructive test Brix %Pol One of the existing serious technical challenges in the sugarcane industry is the lack of a low cost technique for the non-destructive measurement of sugar concentration as Brix (percent soluble solids) or %Pol (percent sucrose) from either standing sugarcane in the field or sugarcane stalk/internode samples in laboratory. This study aimed at investigating the potential of dielectric power spectroscopy as a simple technique for this purpose. A parallel-plate capacitor was developed and supplied with sinusoidal voltage waves swept within a frequency range of 0e10 MHz where the consumed power of the capacitor was monitored as a function of frequency by a spectrum analyser. Seventy five internode samples from four sugarcane cultivars were measured by the dielectric sensor and then analysed for Brix and %Pol in laboratory. Multiple linear regression (MLR) models were developed for prediction of Brix and %Pol as functions of dielectric power at the swept frequencies with R 2 > 0.99 and RMSE < 0.31. The water content of the internode samples was also strongly predicted by the dielectric power spectra with a RMSE of 0.17%. It was concluded that dielectric power spectroscopy can be implemented as a potent and simple technique for the non-destructive measurement of Brix and %Pol of sugarcane.

- by V SUNDARA S I V A KUMAR
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- Computer Engineering, Sensors and Sensing

The virtual testing and validation of advanced driver assistance system and automated driving (ADAS/AD) functions require efficient and realistic perception sensor models. In particular, the limitations and measurement errors of real perception sensors need to be simulated realistically in order to generate useful sensor data for the ADAS/AD function under test. In this paper, a novel sensor modeling approach for automotive perception sensors is introduced. The novel approach combines kernel density estimation with regression modeling and puts the main focus on the position measurement errors. The modeling approach is designed for any automotive perception sensor that provides position estimations at the object level. To demonstrate and evaluate the new approach, a common state-of-the-art automotive camera (Mobileye 630) was considered. Both sensor measurements (Mobileye position estimations) and ground-truth data (DGPS positions of all attending vehicles) were collected during a la...

- by Selim Solmaz
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- Computer Science, Analytical Chemistry, Sensors and Sensing, Medicine

Cardiovascular stent angioplasty represents the pre‐eminent choice for the treatment of coronary artery disease. Despite the widespread developments in this arena such as new‐generation drug‐eluting stents and transient bioabsorbable stents, the stent technologies are still associated with several clinical complications associated with stent thrombosis and in‐stent restenosis. Pertinent ‘smart stent’ systems incorporated with sensors are garnering immense research interest in view of their potential to mitigate/reduce several adverse outcomes associated with stents. In this minireview, we attempt to provide a timely overview on the most recent developments in the field of smart stent systems with embedded sensors. The first two sections of this review discuss about the smart stent technology to detect stent endothelialization and in‐stent restenosis. Next, we briefly summarize the propitious bioabsorbable smart stent systems, and the review concludes by highlighting the future perspectives that can foster this research arena. The latest advancements in this research field by integrating sensors in stents have demonstrated immense potentiality in mitigating the risks associated with cardiovascular clinical complications to ameliorate the problems associated with millions of people worldwide.

- by Jithin Vishnu
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- Sensors and Sensing, Biomaterials, Biosensors, Wireless Sensor Networks

The paper introduces a viable short range signal triangulation method, which will enable users to identify and monitor animals in a given area. “Zig-bee- Zig bee pairs” are used as a more precise and a relatively long-lasting alternative to the traditional radio collars. Additionally, the collar itself ‘broadcasts’ the animal’s current state (EEG, ECG , EMG) and can trigger an S.O.S signal in case of an emergency. Allowing authorities to react to certain cases where the animal might be in critical danger (for rescue) and also allow end users to map certain behavioral patterns in animals.

The issue of noise pollution is very paramount in India, especially cites with huge traffic. One of the major reasons for noise pollution is increasing vehicular honking. Therefore we intend to aid in vehicular honking by bringing in a hardware that involves an individual vehicle to communicate with the other vehicle and blow the horn for the vehicle in front but the horn’s sound will be heard only by the person inside the vehicle. The implementation of directing the horn is achieved through sensors mounted on the vehicles. The vehicles will communicate using Vehicular AdHoc Network (VANET). The use of microcontroller, LCD Display, keypad, sensors and some other electronic devices coupled together will help in accomplishment of our project. Here, we are using transmitters and receivers to form network. Each transmitter and receiver has its own power, range and angle for transmitting and receiving signals. The transmitter will send a signal to the receiver, if the signal is received by the receiver then an acknowledgement is sent to the transmitter, which is indicated by the blinking of a light. On the receiver side, sound is generated by the speaker. If acknowledgement is not received then secondary horn is blown for the concerned person. LCD Display is used for communication between the two vehicles with a standard set of options defined.

Due to the continuous monitoring process of critical patients, Intensive Care Units (ICU) generate large amounts of data, which are difficult for healthcare personnel to analyze manually, especially in overloaded situations such as those present during the COVID-19 pandemic. Therefore, the automatic analysis of these data has many practical applications in patient monitoring, including the optimization of alarm systems for alerting healthcare personnel. In this paper, explainable machine learning techniques are used for this purpose, with a methodology based on age-stratification, boosting classifiers, and Shapley Additive Explanations (SHAP) proposed. The methodology is evaluated using MIMIC-III, an ICU patient research database. The results show that the proposed model can predict mortality within the ICU with AUROC values of 0.961, 0.936, 0.898, and 0.883 for age groups 18–45, 45–65, 65–85 and 85+, respectively. By using SHAP, the features with the highest impact in predicting mortality for different age groups and the threshold from which the value of a clinical feature has a negative impact on the patient’s health can be identified. This allows ICU alarms to be improved by identifying the most important variables to be sensed and the threshold values at which the health personnel must be warned.

In modern greenhouses, several measurement points at plant level are required to create an objective and detailed view of the climate at various regions around the covered space. Specific climatic gradients can cause significant differences in terms of yield, productivity, quantitative and qualitative characteristics of the plants, as well as the development of various diseases. This work presents the development of a distributed monitoring system using a wireless sensor network (WSN) in a commercial greenhouse, towards the realization of a spatially distributed control methodology, based on specific spatial variations of the measured environmental variables. The distributed measurements acquired by the wireless nodes are analyzed to represent the spatial variation of the environmental conditions inside the greenhouse, which can subsequently be used to develop precise control strategies leading to more uniform conditions throughout the entire cultivation area. In this way, uniform q...

Being an alternative to conventional wired sensors, wireless sensor networks (WSNs) are extensively used in Structural Health Monitoring (SHM) applications. Most of the Structural Damage Detection (SDD) approaches available in the SHM literature are centralized as they require transferring data from all sensors within the network to a single processing unit to evaluate the structural condition. These methods are found predominantly feasible for wired SHM systems; however, transmission and synchronization of huge data sets in WSNs has been found to be arduous. As such, the application of centralized methods with WSNs has been a challenge for engineers. In this paper, the authors are presenting a novel application of 1D Convolutional Neural Networks (1D CNNs) on WSNs for SDD purposes. The SDD is successfully performed completely wireless and real-time under ambient conditions. As a result of this, a decentralized damage detection method suitable for wireless SHM systems is proposed. The proposed method is based on 1D CNNs and it involves training an individual 1D CNN for each wireless sensor in the network in a format where each CNN is assigned to process the locally-available data only, eliminating the need for data transmission and synchronization. The proposed damage detection method operates directly on the raw ambient vibration condition signals without any filtering or preprocessing. Moreover, the proposed approach requires minimal computational time and power since 1D CNNs merge both feature extraction and classification tasks into a single learning block. This ability is prevailingly cost-effective and evidently practical in WSNs considering the hardware systems have been occasionally reported to suffer from limited power supply in these networks. To display the capability and verify the success of the proposed method, large-scale experiments conducted on a laboratory structure equipped with a state-of-the-art WSN are reported.

Most metalworking fluids (MWFs), widely used for cooling and lubrication, consist of oils diluted in water in concentration ranging from 1% to 10%. To guarantee good performance and reliability of both machines and processes, oil concentration should be maintained (approximately) constant, hence also measured at regular intervals to compensate for significant deviations from the optimal value. The official technique to measure oil concentration in MWFs is titration with 0.5 M HCl solution and endpoint detection obtained measuring the sample pH. Such a method is accurate and substantially insensitive to sample contamination, but must be carried out in a laboratory, while fast, inexpensive and in-situ measurements would be desirable for effective process and machine control. This paper presents a system to measure oil concentration in MWFs that is new in that: (a) titration is made automatic using a stepper motor; (b) the end-point is detected by means of electrical conductance measurements. Experimental results show a very good correlation (R 2 = 0.9793) between the oil concentrations of prepared solutions and those measured with the proposed technique, while the presented system is suitable for in-situ operation within working environment.

- by Marco Grossi and +1
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- Sensors and Sensing, Sensor, Embedded Systems, Impedance Spectroscopy

Navigation and guidance systems are a critical part of any autonomous vehicle. In this paper, a novel sensor grid using 40 KHz ultrasonic transmitters is presented for adoption in indoor 3D positioning applications. In the proposed technique, a vehicle measures the arrival time of incoming ultrasonic signals and calculates the position without broadcasting to the grid. This system allows for conducting silent or covert operations and can also be used for the simultaneous navigation of a large number of vehicles. The transmitters and receivers employed are first described. Transmission lobe patterns and receiver directionality determine the geometry of transmitter clusters. Range and accuracy of measurements dictate the number of sensors required to navigate in a given volume. Laboratory experiments were performed in which a small array of transmitters was set up and the sensor system was tested for position accuracy. The prototype system is shown to have a 1-sigma position error of about 16 cm, with errors between 7 and 11 cm in the local horizontal coordinates. This research work provides foundations for the future development of ultrasonic navigation sensors for a variety of autonomous vehicle applications.

- by Roberto Sabatini and +3
- •
- Aerospace Engineering, Sensors and Sensing, Aeronautical Engineering, Sensor

- by Eli Katsiri
- •
- Environmental Engineering, Remote Sensing, Sensors and Sensing, Sensor

The characteristic bio-impedance spectra of a biological sample can provide important information about its cellular structure, and further, infer useful information about the physical and chemical condition of the sample. In this paper, we present the background detail of a magnetic induction spectroscopy system for non-contact bio-impedance measurements, and some results using this system to obtain the relative permittivity spectra of a range of fruit and vegetable samples, over a frequency range from 160 kHz to 2.5 MHz. Relative permittivity is found to decrease with respect to frequency for each sample tested. This shows clear evidence of dispersion occurring within the samples across the investigated bandwidth.

- by Yee Mei Tan and +3
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- Sensors and Sensing, Spectroscopy, Magnetic Induction Tomography, Non Destructive Testing

Pulse oximetry is a ubiquitous non-invasive medical sensing method for measuring pulse rate and arterial blood oxygenation. Conventional pulse oximeters use expensive optoelectronic components that restrict sensing locations to finger tips or ear lobes due to their rigid form and area-scaling complexity. In this work, we report a pulse oximeter sensor based on organic materials, which are compatible with flexible substrates. Green (532 nm) and red (626 nm) organic light-emitting diodes (OLEDs) are used with an organic photodiode (OPD) sensitive at the aforementioned wavelengths. The sensor’s active layers are deposited from solution-processed materials via spin-coating and printing techniques. The all-organic optoelectronic oximeter sensor is interfaced with conventional electronics at 1 kHz and the acquired pulse rate and oxygenation are calibrated and compared with a commercially available oximeter. The organic sensor accurately measures pulse rate and oxygenation with errors of 1% and 2%, respectively.

- by Yasser Khan
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- Medical Sciences, Sensors and Sensing, Wearable Technologies, Organic Electronics

The era of modernization like this technology is an important role in everyday life. The development of technological knowledge has brought people to a better era. so with the development of many people who often do research, In this study the author aims to design a microcontroller-based pull up device using ultrasonic sensors, to facilitate the pull up counter, this system consists of various electronic components such as Adruino Nano, bluetooth sensors, ultrasonic sensors, and Text Running LEDs, this tool will be operated using an Android cell phone that has been connected to Bluetooth HC-05 then press (start / stop) to turn the device on and off. The ultrasonic sensor is used to measure radio waves from sensors to objects. The results of these sensors will be displayed via LED Text Running and Android phones. One of the uses of this tool is in health sciences for the selection of TNI and POLRI admission. Perform medical tests with manual pull up calculations, longer than using a microcontroller-based pull up counter using ultrasonic sensors. Intisari-Dizaman modernisasi seperti ini teknologi merupakan peranan penting dalam kehidupan sehari-hari, Perkembangan ilmu pengetahuan teknologi telah membawa manusia kepada Era yang lebih baik. sehingga dengan perkembangan jaman banyak orang yang sering melakukan penelitian. Pada penelitian ini penulis bertujuan untuk merancang sebuah alat penghittung pull up berbasis mikrokontroler mengunakan sensor ultrasonik, untuk mempermudah melakukkan penghitung pull up, sistem ini terdiri berbagai komponen elektronik seperti Adruino Nano, sensor bluetooth, sensor ultrasonik, dan LED Text Running, Alat ini akan di operasikan menggunakan HP Android yang telah terkoneksi dengan Bluetooth HC-05 kemudian menekan (start/stop) untuk menghidupkan dan mematikan alat tersebut. Adapun sensor ultrasonik digunakan untuk mengukur gelombang radio dari sensor ke objek. Hasil dari sensor tersebut akan ditampilkan melalui LED Text Running dan HP android. Salah satu pengunaan alat ini yaitu pada ilmu kesehatan untuk seleksi masuk TNI maupun POLRI. Melakukan test kesehatan dengan penghitungan pull up manual, lebih lama daripada menggunakan alat penghitung pull up berbasis mikrokontroller dengan menggunakan sensor ultrasonik. Kata Kunci-Arduino Nano, sensor ultrasonik, Bluetooth Terminal HC-05, LED Text Running.

- by JTE UNIBA and +1
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- Sensors and Sensing, Ultrasonic Sensor

This study employed Support Vector Machine (SVM) in the classification and prediction of fire outbreak based on fire outbreak dataset captured from the Fire Outbreak Data Capture Device (FODCD). The fire outbreak data capture device (FODCD) used was developed to capture environmental parameters values used in this work. The FODCD device comprised DHT11 temperature sensor, MQ-2 smoke sensor, LM393 Flame sensor, and ESP8266 Wi-Fi module, connected to Arduino nano v3.0.board. 700 data point were captured using the FODCD device, with 60% of the dataset used for training while 20% was used for testing and validation respectively. The SVM model was evaluated using the True Positive Rate (TPR), False Positive Rate (FPR), Accuracy, Error Rate (ER), Precision, and Recall performance metrics. The performance results show that the SVM algorithm can predict cases of fire outbreak with an accuracy of 80% and a minimal error rate of 0.2%. This system was able to predict cases of fire outbreak with a higher degree of accuracy. It is indicated that the use of sensors to capture real world dataset, and machine learning algorithm such as support vector machine gives a better result to the problem of fire management

Environmental nanotechnology is considered to play a key role in the shaping of current environmental engineering and science. Environmental nanotechnology is considered to play a key role in the shaping of current environmental engineering and science. Environmental nanotechnology is considered to play a key role in the shaping of current environmental engineering and science. The issue of environmental pollution has become a hot subject in today's world. Environmental pollution, mainly caused by toxic chemicals, includes air, water, and soil pollution. This pollution results not only in the destruction of biodiversity, but also the degradation of human health. Pollution levels that are increasing day by day need better developments or technological discoveries immediately. Nanotechnology is an upcoming technology that can provide solution for combating pollution by controlling shape and size of materials at the nanoscale. Nanotechnology has three main capabilities that can be applied in the fields of environment, including the cleanup (remediation) and purification, the detection of contaminants (sensing and detection), and the pollution prevention. This article provides comprehensive information regarding the role of nanotechnology in pollution prevention. Due to its large surface area and high surface energy, the nanoparticles have the ability to absorb large amount of pollutants or catalyze reactions at a much faster rate, thus reducing energy consumption during degradation or helps in preventing release of contaminants.

Application of information and computer control technologies in yogurt production is considered in the paper. The main functional features of the integrated distributed measurement and control systems are explained in details. The main tasks in the management of stationary production systems in yogurt production are defined and their implementation is illustrated. Described are the main information sources of – sensors that are used for control, visualization, quality assessment.

- by Stanka Baycheva
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- Sensors and Sensing, Computer Control, yogurt fermentation