Journal articles on the topic 'BTX sensors'
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Ruiz, Elisa, Thiaka Gueye, Claire Masson, Christelle Varenne, Alain Pauly, Jérôme Brunet, and Amadou L. Ndiaye. "Macrocycle-Functionalized RGO for Gas Sensors for BTX Detection Using a Double Transduction Mode." Chemosensors 9, no. 12 (December 7, 2021): 346. http://dx.doi.org/10.3390/chemosensors9120346.
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To fabricate mass and resistive sensors based on reduced graphene oxide (RGO), we investigated the functionalization of RGO by tetra tert-butyl phthalocyanine (PcH2tBu), which possesses a macroring and tert-butyl peripheral groups. Herein, we present the gas sensor responses of the functionalized RGO toward benzene, toluene, and xylene (BTX) vapors. The RGO was obtained by the reduction of graphene oxide (GO) using citrate as a reducing agent, while the functionalization was achieved non-covalently by simply using ultrasonic and heating treatment. The sensor devices based on both QCM (quartz crystal microbalance) and resistive transducers were used simultaneously to understand the reactivity. Both the GO and the RGO showed less sensitivity to BTX vapors, while the RGO/PcH2tBu presented enhanced sensor responses. These results show that the p-network plays a very important role in targeting BTX vapors. The resistive response analysis allowed us to state that the RGO is a p-type semiconductor and that the interaction is governed by charge transfer, while the QCM response profiles allowed use to determine the differences between the BTX vapors. Among BTX, benzene shows the weakest sensitivity and a reactivity in the higher concentration range (>600 ppm). The toluene and xylene showed linear responses in the range of 100–600 ppm.
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Ndiaye, A., J. Brunet, C. Varenne, P. Bonnet, A. Pauly, M. Dubois, K. Guerin, and B. Lauron. "Functionalized Carbon Nanotubes-Based Gas Sensors for Pollutants Detection: Investigation on the Use of a Double Transduction Mode." Key Engineering Materials 605 (April 2014): 75–78. http://dx.doi.org/10.4028/www.scientific.net/kem.605.75.
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With an objective to fabricate Carbon nanotubes (CNTs) based sensors, the solution route is investigated. The dispersion routes are chosen here to avoid the CNTs to form bundles which can reduce their surface area. The results show that SWNTs-based gas sensors made by the surfactant method is possible if the annealing temperature is correctly chosen. The use of a surfactant allows preparing sensing layers which present responses to NO2 exposure in the 50-200 ppb Range. In a second procedure the CNTs are noncovalently functionalized and used as sensing material for BTX (Benzene, Toluene and Xylenes) detection. The noncovalent functionalisation occurs through p-p stacking between the SWNTs framework and the highly delocalized π-system of the macrocycle which are phthalocyanines and porphyrines derivatives. The SWNTs materials are characterized by standard techniques (UV-Vis spectroscopy, TGA, TEM, Raman analysis). For BTX detection, we used a double transduction mode: IDEs (Interdigitated electrodes) and QCM (Quartz Crystal Microbalance) in order to get insight into the sensing mechanism.
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Mirzaei, Ali, Jae-Hun Kim, Hyoun Woo Kim, and Sang Sub Kim. "Resistive-based gas sensors for detection of benzene, toluene and xylene (BTX) gases: a review." Journal of Materials Chemistry C 6, no. 16 (2018): 4342–70. http://dx.doi.org/10.1039/c8tc00245b.
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Matatagui, Daniel, Fabio Andrés Bahos, Isabel Gràcia, and María del Carmen Horrillo. "Portable Low-Cost Electronic Nose Based on Surface Acoustic Wave Sensors for the Detection of BTX Vapors in Air." Sensors 19, no. 24 (December 8, 2019): 5406. http://dx.doi.org/10.3390/s19245406.
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A portable electronic nose based on surface acoustic wave (SAW) sensors is proposed in this work to detect toxic chemicals, which have a great potential to threaten the surrounding natural environment or adversely affect the health of people. We want to emphasize that ferrite nanoparticles, decorated (Au, Pt, Pd) and undecorated, have been used as sensitive coatings for the first time in these types of sensors. Furthermore, the proposed electronic nose incorporates signal conditioning and acquisition and transmission modules. The electronic nose was tested to low concentrations of benzene, toluene, and xylene, exhibiting excellent performance in terms of sensitivity, selectivity, and response time, indicating its potential as a monitoring system that can contribute to the detection of toxic compounds.
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Kumar, Abhishek, Christelle Varenne, Amadou L. Ndiaye, Alain Pauly, Marcel Bouvet, and Jérôme Brunet. "Improvement in metrological performances of phthalocyanine-based QCM sensors for BTX detection in air through substituent’s effect." Sensors and Actuators B: Chemical 368 (October 2022): 132253. http://dx.doi.org/10.1016/j.snb.2022.132253.
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Ndiaye, Amadou L., Jérôme Brunet, Christelle Varenne, and Alain Pauly. "Functionalized CNTs-Based Gas Sensors for BTX-Type Gases: How Functional Peripheral Groups Can Affect the Time Response through Surface Reactivity." Journal of Physical Chemistry C 122, no. 37 (August 29, 2018): 21632–43. http://dx.doi.org/10.1021/acs.jpcc.8b05379.
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Pauly, A., J. Brunet, C. Varenne, and A. L. Ndiaye. "Insight in the interaction mechanisms between functionalized CNTs and BTX vapors in gas sensors: Are the functional peripheral groups the key for selectivity?" Sensors and Actuators B: Chemical 298 (November 2019): 126768. http://dx.doi.org/10.1016/j.snb.2019.126768.
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Yoon, Sungmin, Youngwoong Choi, Jabeom Koo, Yejin Hong, Ryunhee Kim, and Joowook Kim. "Virtual Sensors for Estimating District Heating Energy Consumption under Sensor Absences in a Residential Building." Energies 13, no. 22 (November 18, 2020): 6013. http://dx.doi.org/10.3390/en13226013.
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District heating (DH) is an energy efficient building heating system that entails low primary energy consumption and reduced environmental impact. The estimation of the required heating load provides information for operators to control district heating systems (DHSs) efficiently. It also yields historical datasets for intelligent management applications. Based on the existing virtual sensor capabilities to estimate physical variables, performance, etc., and to detect the anomaly detection in building energy systems, this paper proposes a virtual sensor-based method for the estimation of DH energy consumption in a residential building. Practical issues, including sensor absences and limited datasets corresponding to actual buildings, were also analyzed to improve the applicability of virtual sensors in a building. According to certain virtual sensor development processes, model-driven, data-driven, and grey-box virtual sensors were developed and compared in a case study. The grey-box virtual sensor surpassed the capabilities of the other virtual sensors, particularly for operation patterns corresponding to low heating, which were different from those in the training dataset; notably, a 16% improvement was observed in the accuracy exhibited by the grey-box virtual sensor, as compared to that of the data-driven virtual sensor. The former sensor accounted for a significantly wider DHS operation range by overcoming training data dependency when estimating the actual DH energy consumption. Finally, the proposed virtual sensors can be applied for continuous commissioning, monitoring, and fault detection in the building, since they are developed based on the DH variables at the demand side.
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Tsaramirsis, Georgios, Seyed Buhari, Mohammed Basheri, and Milos Stojmenovic. "Navigating Virtual Environments Using Leg Poses and Smartphone Sensors." Sensors 19, no. 2 (January 13, 2019): 299. http://dx.doi.org/10.3390/s19020299.
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Realization of navigation in virtual environments remains a challenge as it involves complex operating conditions. Decomposition of such complexity is attainable by fusion of sensors and machine learning techniques. Identifying the right combination of sensory information and the appropriate machine learning technique is a vital ingredient for translating physical actions to virtual movements. The contributions of our work include: (i) Synchronization of actions and movements using suitable multiple sensor units, and (ii) selection of the significant features and an appropriate algorithm to process them. This work proposes an innovative approach that allows users to move in virtual environments by simply moving their legs towards the desired direction. The necessary hardware includes only a smartphone that is strapped to the subjects’ lower leg. Data from the gyroscope, accelerometer and campus sensors of the mobile device are transmitted to a PC where the movement is accurately identified using a combination of machine learning techniques. Once the desired movement is identified, the movement of the virtual avatar in the virtual environment is realized. After pre-processing the sensor data using the box plot outliers approach, it is observed that Artificial Neural Networks provided the highest movement identification accuracy of 84.2% on the training dataset and 84.1% on testing dataset.
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Purbakawaca, R., A. S. Yuwono, I. D. M. Subrata, and H. Alatas. "Low-Cost Calibration MOS Gas Sensor for Measuring SO2 Pollutants in Ambient Air." Nature Environment and Pollution Technology 21, no. 1 (March 6, 2022): 339–47. http://dx.doi.org/10.46488/nept.2022.v21i01.041.
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Air pollution has evolved into a global issue that necessitates immediate and accurate pollution control. The usage of the Metal Oxide Semiconductor (MOS) sensor as a monitoring system for air pollution levels is one possible answer to this challenge. The MQ-136 sensor is calibrated using standard SO2 (0, 5, 10, 20, 30, 40, 50, 60, 70) ppm as the test gas in this study. To collect the sensor output signal, a variety of equipment was created, including a gas test box, a voltage divider, and follower circuit, and a gas flow control unit operated by a microcontroller. The test gas can be pumped into the test box at a constant rate of 1.0 L.min-1 by the apparatus. To evaluate a significant difference (= 0.05), an analysis of variance was performed on the response signal generated by a series of sensors due to the concentration of the test gas. To examine the correlation between the sensor response signal and the test gas concentration treatment, as well as the sensor performance, linear regression analysis was used. The ANOVA results demonstrate no significant differences amongst the sensors, indicating that they all follow the same routine. Furthermore, ANOVA analysis reveals that the sensors respond differently at each level of SO2 concentration. According to linear regression, the relationship between gas concentration and sensor-1, sensor-2, and sensor-3 output signals is reflected by coefficients of determination of 0.94, 0.91, and 0.93, respectively.
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Enlund, Desirée, Katherine Harrison, Rasmus Ringdahl, Ahmet Börütecene, Jonas Löwgren, and Vangelis Angelakis. "The role of sensors in the production of smart city spaces." Big Data & Society 9, no. 2 (July 2022): 205395172211102. http://dx.doi.org/10.1177/20539517221110218.
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Smart cities build on the idea of collecting data about the city in order for city administration to be operated more efficiently. Within a research project gathering an interdisciplinary team of researchers – engineers, designers, gender scholars and human geographers – we have been working together using participatory design approaches to explore how paying attention to the diversity of human needs may contribute to making urban spaces comfortable and safe for more people. The project team has deployed sensors collecting data on air quality, sound and mobility in a smart city testbed in Norrköping, Sweden. While these sensors are meant to capture an accurate ‘map’ of the street and what is going on along it, our interdisciplinary conversations around the sensors have revealed the heterogeneity both of smart city planning and spatial formulations of the city. The discussions have given rise to questions regarding the work that goes into constructing the sensor box itself, as well as the work of deploying it, and how these influence the ‘map’ that the sensors produce. In this paper, we draw on Lefebvre to explore how the sensors themselves produce smart spaces. We analyze how the box depends on perceived space to function (e.g. requiring electricity), and simultaneously it produces conceptualizations of space that are influenced by the materiality of the box itself (e.g. sensors being affected by heat and noise). Further, we explore how the (in)visibility of sensor technology influences lived space.
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Hetzroni, Amots, Denys J. Charles, Jules Janick, and James E. Simon. "Electronic Sensing of Apple Ripeness Based on Volatile Gas Emissions." HortScience 30, no. 4 (July 1995): 816D—816. http://dx.doi.org/10.21273/hortsci.30.4.816d.
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A prototype of a nondestructive electronic sensory system (electronic sniffer) that responds to volatile gases emitted by fruit during ripening was developed. The electronic sniffer is based upon four semiconductor gas sensors designed to react with a range of reductive gases, including aromatic volatiles. In 1994, we examined the potential of using the electronic sniffer as a tool to nondestructively determine ripeness in `Golden Delicious' and `Goldrush' apples. Fruit were harvested weekly from 19 Sept. to 17 Oct. (`Golden Delicious') and 27 Sept. to 18 Nov. (`Goldrush'). Each week, apples of each cultivar were evaluated individually for skin color, weight size, and headspace volatiles. Each fruit was then evaluated by the electronic sniffer, and headspace ethylene was sampled from air within the testing box. Individual fruits were then evaluated for total soluble solids, firmness, pH, total acidity, and starch index value. The electronic sniffer was able to distinguish and accurately classify the apples into three ripeness stages (immature, ripe, and over-ripe). Improved results were obtained when multiple gas sensors were used rather than a single gas sensor.
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Yudianto, Renangga, and Anton Yudhana. "Sistem Pemantau Suhu Cooler Box Berbasis Telemetri Dengan Thermoelectric Cooler Sebagai Bakteriostatik Pada Ikan." Jurnal ELTIKOM 6, no. 2 (November 17, 2022): 126–39. http://dx.doi.org/10.31961/eltikom.v6i2.551.
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Indonesia has enormous marine resource potential, which can be explored as a prime mover of national economic development, one of which is fisheries resources. The factor that determines the selling value of fish is the freshness of the fish. This study aims to utilize Thermoelectric Cooler (TEC) in cooler boxes as a bacteriostatic system for fish that is environmentally friendly and monitored using telemetry based DS18B20 ESP8266 temperature sensor. The temperature data includes the temperature of the cooler box, the temperature of the Thermoelectric Cooler (TEC), and the temperature of the room. The parameters used to test the quality of DS18B20 temperature sensor are accuracy, normality test, homogeneity test, and independent samples t-test. The data of DS18B20 temperature sensor system is processed at nodeM-CU then sent and displayed via the thingspeak website and LCD in real time. Organoleptically, the obser-vation results of fish A placed in a cooler box are categorized as fresh, and the observation results of fish B which are placed at room temperature are categorized as not fresh according to (SNI 2729:2013). The sensor test results obtained in this study showed value of the temperature accuracy of cooler box was 97.8%, the temperature accuracy value of Thermoelectric Cooler (TEC) was 98.56%, the room tempera-ture accuracy value was 99.67%, the results of normality test of three temperature sensors are normally distributed, the results of homogeneity test of three temperature sensors are homogeneous, and the results of independent samples t-test are not significantly different, which indicates that three DS18B20 tempera-ture sensors are accurate.
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Shen, Sheng, and Shao-Fei Jiang. "Distributed Deformation Monitoring for a Single-Cell Box Girder Based on Distributed Long-Gage Fiber Bragg Grating Sensors." Sensors 18, no. 8 (August 8, 2018): 2597. http://dx.doi.org/10.3390/s18082597.
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Distributed deformation based on fiber Bragg grating sensors or other kinds of strain sensors can be used to monitor bridges during operation. However, most research on distributed deformation monitoring has focused on solid rectangular beams rather than box girders—a kind of typical hollow beam widely employed in actual bridges. The deformation of a single-cell box girder contains bending deflection and also two additional deformations respectively caused by shear lag and shearing action. This paper revises the improved conjugated beam method (ICBM) based on the long-gage fiber Bragg grating (LFBG) sensors to satisfy the requirements for monitoring the two additional deformations in a single-cell box girder. This paper also proposes a suitable LFBG sensor placement in a box girder to overcome the influence of strain fluctuation on the flange caused by the shear lag effect. Results from numerical simulations show that the theoretical monitoring errors of the revised ICBM are typically 0.3–1.5%, and the maximum error is 2.4%. A loading experiment for a single-cell box gilder monitored by LFBG sensors shows that most of the practical monitoring errors are 6–8% and the maximum error is 11%.
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Sundararajan, A., J. Kurowski, T. Yan, D. M. Klingeman, M. P. Joachimiak, J. Zhou, B. Naranjo, J. A. Gralnick, and M. W. Fields. "Shewanella oneidensis MR-1 Sensory Box Protein Involved in Aerobic and Anoxic Growth." Applied and Environmental Microbiology 77, no. 13 (May 20, 2011): 4647–56. http://dx.doi.org/10.1128/aem.03003-10.
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ABSTRACTAlthough little is known of potential function for conserved signaling proteins, it is hypothesized that such proteins play important roles to coordinate cellular responses to environmental stimuli. In order to elucidate the function of a putative sensory box protein (PAS domains) inShewanella oneidensisMR-1, the physiological role of SO3389 was characterized. The predicted open reading frame (ORF) encodes a putative sensory box protein that has PAS, GGDEF, and EAL domains, and an in-frame deletion mutant was constructed (ΔSO3389) with approximately 95% of the ORF deleted. Under aerated conditions, wild-type and mutant cultures had similar growth rates, but the mutant culture had a lower growth rate under static, aerobic conditions. Oxygen consumption rates were lower for mutant cultures (1.5-fold), and wild-type cultures also maintained lower dissolved oxygen concentrations under aerated growth conditions. When transferred to anoxic conditions, the mutant did not grow with fumarate, iron(III), or dimethyl sulfoxide (DMSO) as electron acceptors. Biochemical assays demonstrated the expression of differentc-type cytochromes as well as decreased fumarate reductase activity in the mutant transferred to anoxic growth conditions. Transcriptomic studies showed the inability of the mutant to up-express and down-express genes, includingc-type cytochromes (e.g., SO4047/SO4048, SO3285/SO3286), reductases (e.g., SO0768, SO1427), and potential regulators (e.g., SO1329). The complemented strain was able to grow when transferred from aerobic to anoxic growth conditions with the tested electron acceptors. The modeled structure for the SO3389 PAS domains was highly similar to the crystal structures of FAD-binding PAS domains that are known O2/redox sensors. Based on physiological, genomic, and bioinformatic results, we suggest that the sensory box protein, SO3389, is an O2/redox sensor that is involved in optimization of aerobic growth and transitions to anoxia inS. oneidensisMR-1.
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Kozeev, Evgeniy Viktorovich, Oleg Sergeevich Samoshkin, Evgeniy Nikolaevich Popov, and Valeriy Evgenyevich Volkov. "Development of tests of increased reliability sensors for inspection system of axle box heating." Transport of the Urals, no. 3 (2021): 39–45. http://dx.doi.org/10.20291/1815-9400-2021-3-39-45.
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All the domestic passenger cars since 1960 are produced only on bogies with roller bearings. A transition to roller bearings demanded the cars to be equipped with inspection system of axle box heating. It is necessary because axle box be heated over a specified temperature that leads to deterioration of the oil lubricity. The main element of the inspection system of axle box heating is a thermal sensor that is installed on each axle box. Nowadays, bolster bogies of all models are equipped with type 393 thermal sensors. At introduction of new bolsterless bogies the installation of the type 393 thermal sensors on the axle boxes was carried out with the use of special brass adapter. The observations in operation showed insufficient reliability of the inspection system of axle box heating in bolsterless bogies. Consequently, the authors have carried out research on new increased reliability thermal sensors. The pilot batch has passed preliminary and acceptance rig tests. On the results of the rig tests it has been decided to carry out an under-control operation on mainline passenger cars. The under-control operation with new sensors has been carried out on the basis of the Novosibirsk passenger wagon depot. On the basis of its results the authors have established the required temperature of the inspection system of axle box heating actuation.
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Oussar, Yacine, Cedric Margo, Jérôme Lucas, and Stéphane Holé. "Fast circular shapes detection in cylindrical ECT sensors by design selection and nonlinear black-box modeling." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 36, no. 1 (January 3, 2017): 2–17. http://dx.doi.org/10.1108/compel-09-2015-0352.
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Purpose Within the framework of image reconstruction in cylindrical electrical capacitance tomography (ECT) sensors, the purpose of this study is to select the structure of a sensor in terms of number and size of the electrodes, to predict the radius and the position of a single circular shape lying in the cross-section defined by the sensor electrodes. Design/methodology/approach Nonlinear black-box models using a set of physically independent capacitances and least-square support vector machines models selected with a sophisticated validation method are implemented. Findings The coordinates of circular shapes are well estimated in fixed and variable permittivity environments even with noisy data. Various numerical experiments are presented and discussed. Sensors formed by three or four electrodes covering 50 per cent of the sensor perimeter provide the best prediction performances. Research limitations/implications The proposed method is limited to the detection of a single circular shape in a cylindrical ECT sensor. Practical implications This method can be advantageously implemented in real-time applications, as it is numerically cost-effective and necessitates a small amount of measurements. Originality/value The contribution is two-fold: a fast computation of a circular shape position and radius with a satisfactory precision compared to the sensor size, and the determination of a cylindrical ECT sensor architecture that allows the most efficient predictions.
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Chen, Xi Yuan, and Lin Fang. "Performance Analysis and Experimental Verification for FBG Sensors Applied for Smart Structure." Key Engineering Materials 336-338 (April 2007): 1357–60. http://dx.doi.org/10.4028/www.scientific.net/kem.336-338.1357.
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Among a variety of fiber sensors, the fiber Bragg grating (FBG) sensor has numerous advantages over other optical fiber sensors. One of the major advantages of this type of sensors is attributed to wavelength-encoded information given by the Bragg grating. Since the wavelength is an absolute parameter, signal from FBG may be processed such that its information remains immune to power fluctuations along the optical path. This inherent characteristic makes the FBG sensors very attractive for application in smart material structure, health monitoring field et al. But FBG sensors are sensitive to temperature and strain simultaneously; it is necessary to analyze the characteristics of temperature and strain of FBG applied for smart structure. Short overview of the FBG sensing principle as well as theoretical analyses is presented at first; then the paper proposes a simple, convenient, and low cost experimental method to verify the performance of FBGs. The improved high-accuracy experimental instrument of thermal deformation, which consists of an accurate temperature controlling and measuring subsystem, supporting and adjusting subsystem, collimating and positioning subsystem and fine motion and measuring sub-system, is simply introduced. The proposed experimental method involves bonding one uniform FBG to the center of the pole, which is about 89.5mm long; another FBG temperature sensor is free in the temperature-control box. The temperature in the box is -20°C-+50°C is adjusted according to experimental schedule. The characteristics of the FBG are analyzed by actual datum, which are simultaneously collected by a PC through a FBG interrogator. Comparing the data of FBG bonded to the pole with another FBG temperature sensor in the free state, the characteristics of the temperature and the thermal strain of the FBG can be obtained. The experimental result shows the FBGs used to the smart material have good agreement characteristics with theoretical calculation of the FBGs.
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Aloni, Sukhada, and Divya Shekhawata. "Detection of suspicious activity using mobile sensor data and Modified Sub-space K-NN for criminal investigations." YMER Digital 21, no. 08 (August 17, 2022): 578–91. http://dx.doi.org/10.37896/ymer21.08/49.
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With the bulk availability of mobile sensors, the data collected from them mustn’t be wasted. Nowadays the creation of black-box software that collects this data is not a very difficult task. It is possible to detect suspicious unlawful events using this black-box data. In this paper, we present a novel way of doing forensic investigation using a modified sub-space K-NN (MSK) algorithm. The MSK algorithm is capable of detecting suspicious activities from mobile sensor data. Using this technique, we could detect any normal activity versus suspicious activity with 99.7 % accuracy. We expect the future researcher to develop on this idea and build a solid digital forensic system capable of doing bias-free decisions. Keywords: Forensic, Mobile sensor data, Black box, mobile data collection
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Esposito, Daniele, Jessica Centracchio, Emilio Andreozzi, Paolo Bifulco, and Gaetano Gargiulo. "Design and Evaluation of a Low-Cost Electromechanical System to Test Dynamic Performance of Force Sensors at Low Frequencies." Machines 10, no. 11 (November 2, 2022): 1017. http://dx.doi.org/10.3390/machines10111017.
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Piezoresistive or piezoelectric force sensors are widely available today. These sensors are preferred to loadcells because of their extremely reduced size, slimness, and low cost, which allow their easy inclusion in a large variety of devices including wearables. In particular, many applications are devoted to monitoring human body movements, such as those related to breathing, muscle contraction, walking, etc. However, such sensors offer variable performance, and they need to be individually calibrated and tested to ensure accurate measurements. An automated electromechanical system that allows simple mechanical tests of force sensors is proposed. The system by means of an electrical motor; a gear box; a connecting rod-crank mechanism; two pistons, and a coupling spring between them, impress sinusoidal axial forces onto the sensor under test. The system is designed as modular so that it can be customized: the force range to which the sensor is subjected, the frequency range, and the coupler with the sensor can be changed to resemble the actual application context. The actual force (read from a loadcell coupled to the sensor under test), a piston displacement, and the sensor output are simultaneously recorded. The electromechanical system generates nearly pure sinusoidal stresses at varying low frequencies (mean total harmonic distortion of 2.77%). The energy dissipated for a single stress cycle was 3.62 gf mm on average. The developed system was used to test a Force Sensitive Resistor (FSR)-based sensor and a piezoelectric (PZT) sensor. The tests revealed significant differences from the actual force values (particularly at very low frequencies), output drifts of the FSR sensor in measurements, and non-linear behaviors. The system was found to be able to provide dynamic performances, accurate calibration, and non-linear behavior of the individual sensor.
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Chen, Junxiang, Jilin Zhang, Ruixiang Qian, Junfeng Yuan, and Yongjian Ren. "An Anomaly Detection Method for Wireless Sensor Networks Based on the Improved Isolation Forest." Applied Sciences 13, no. 2 (January 4, 2023): 702. http://dx.doi.org/10.3390/app13020702.
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With the continuous development of technologies such as the Internet of Things (IoT) and cloud computing, sensors collect and store large amounts of sensory data, realizing real-time recording and perception of the environment. Due to the open characteristics of WSN, the security risks during information transmission are prominent, and network attack or intrusion is likely to occur. Therefore, effective anomaly detection is vital for IoT systems to keep the system safe. The original Isolation Forest algorithm is an anomaly detection algorithm with linear time complexity and has a better detection effect on perceptual data. However, there are also disadvantages such as strong randomness, low generalization performance, and insufficient stability. This paper proposes a data anomaly detection method named BS-iForest (box plot-sampled iForest) for wireless sensor networks based on a variant of Isolation Forest to address the problems. This method first uses the sub-dataset filtered by the box graph to train and construct trees. Then, isolation trees with higher accuracy are selected in the training set to form a base forest anomaly detector. Next, the base forest anomaly detector uses anomaly detection to judge data outliers during the next period. These experiments were performed on datasets collected from sensors deployed in a data center of a university, and the Breast Wisconsin (BreastW) dataset, showing the performance of the variant of the Isolation Forest algorithm. Compared with the traditional isolation forest, the area under the curve (AUC) increased by 1.5% and 7.7%, which verified that the proposed method outperforms the standard Isolation Forest algorithm with the two datasets we chose.
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Gajek, Andrzej, Wiesław Pieniążek, Robert Janczur, and Stanisław Wolak. "Verification of Sensors for Yaw Rate and Lateral Acceleration in Car ESP System." Archives of Automotive Engineering – Archiwum Motoryzacji 88, no. 2 (June 30, 2020): 61–67. http://dx.doi.org/10.14669/am.vol88.art5.
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This study analyzed the possibilities to validate the indications of sensors for yaw rate and lateral acceleration within the scope of extended diagnostic routine of the car ESP system at Vehicle Inspection Stations (SKP). The stand tests were performed using the reference sensors and a standard diagnostic tester. The comparison of the yaw rate and lateral acceleration results obtained from the working sensor under examination, recorded with the V box unit, and the results from the reference sensor demonstrated a good conformity both in quality and quantity. But these tests were demonstrated also a pure conformity (both in quality and quantity) with runs obtained from tester. The Root Mean Square (RMS) was used as factor of qualitative estimation. These inconveniences were caused from in sampling frequency incompatibility and lack of recording synchronization for signals from the tester and from reference sensors. The primary importance question is a firmware modification for selected testers. Such a tester should be able to record signals from a reference sensor and have a set sampling frequency for signals from a working sensor. On the basis of already carried out research analyses the suggested frequency should be no fewer than about of 10 Hz. It resulted from a spectral analysis carried out for possessed runs maintaining the Nyquist limit frequency.
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Ito-Masui, Asami, Eiji Kawamoto, Ryo Esumi, Hiroshi Imai, and Motomu Shimaoka. "Sociometric wearable devices for studying human behavior in corporate and healthcare workplaces." BioTechniques 71, no. 1 (July 2021): 392–99. http://dx.doi.org/10.2144/btn-2020-0160.
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Wearable sensor technology enables objective data collection of direct human interactions. The authors review sociometric wearable devices (SWD) and their application in healthcare. Human interactions captured by wearable sensors have been shown to correlate with social constructs such as teamwork and productivity in the office. Application of SWD in the field of healthcare requires special considerations: validation studies have shown technological disadvantages in acute medical settings. Application of SWD in healthcare should be considered based on the strengths and weaknesses of the methodology. SWD can also play an important role in investigation of human interaction and epidemic spread. When study designs and methodologies are carefully considered, incorporation of SWD in healthcare research has promising potential for new insights.
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Nas, Mardhiyah, Misnawati, Megha Rahmawaty Marsing, and Fadlia. "Prototipe Pemantauan Level Air Pada Bendungan Berbasis IOT." Journal of Applied Smart Electrical Network and Systems 1, no. 02 (December 31, 2020): 63–69. http://dx.doi.org/10.52158/jasens.v1i02.120.
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The purpose of making this prototype is to make a water level pemantauan tool in the dam using ultrasonic sensors and an IoT system. To support the manufacture of this tool, several other electronic components are used, including the NodeMCU microcontroller, ultrasonic sensors, water pumps, relays, and buzzers. The process of the water level pemantauan system in the IoT-based dam works as a whole. The process begins with filling water from box 1 (analogous to river) to box 2 (analogous to a dam) assisted by a water pump to fill the water box. Then the ultrasonic sensor reads the water distance data from the dam and is sent to the microcontroller and then displayed on ThingSpeak via PC / HP. When box 2 is filled with water and reaches the maximum limit, the buzzer will sound and the relay will turn off the water pump automatically. The test results show that the data obtained is accurate. When the sensor reads the water level capacity data at a distance of 6 cm, the dam capacity will be fully read, the buzzer will sound and turn off the relay automatically then send the information to ThingSpeak. Reading or pemantauan the water level in the dam can be an alternative to control the water level in the dam and facilitate the dam guard.
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Badura, Marek, Piotr Batog, Anetta Drzeniecka-Osiadacz, and Piotr Modzel. "Evaluation of Low-Cost Sensors for Ambient PM2.5 Monitoring." Journal of Sensors 2018 (October 31, 2018): 1–16. http://dx.doi.org/10.1155/2018/5096540.
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Low-cost sensors are an opportunity to improve the spatial and temporal resolution of particulate matter data. However, such sensors should be calibrated under conditions close to the final ones before any monitoring actions. The paper presents the results of a collocated comparison of four models of low-cost optical sensors with a TEOM 1400a analyser. SDS011 (Nova Fitness), ZH03A (Winsen), PMS7003 (Plantower), and OPC-N2 (Alphasense) sensors were used in this research. Three copies of each sensor model were placed in a common box to compare the sensor performance under the same measurement conditions. Monitoring of the PM2.5 fraction was conducted for almost half a year from 21 August 2017 to 19 February 2018 in Wrocław (Poland). Reproducibility between sensor units was assessed on the basis of coefficient of variation (CV). CV values were lower than 7% in the case of SDS011 and PMS7003 sensors and equal to 20% for OPC-N2 units. CV was higher than 50% for ZH03A, mainly due to malfunctions. During the measurements, the trends of outputs from sensors were generally similar to TEOM data, but significant overestimation of PM2.5 concentrations was observed for the sensor raw data. A high linear relationship between TEOM and sensors was noticed for 1 min, 15 min, and 1-hour averaged data for PMS7003 sensors (R2≈0.83–0.89), for SDS011 units (R2≈0.79–0.86), and for one unit of ZH03A (R2≈0.74–0.81). R2 values for daily averages were at the level 0.91–0.93 for PMS7003, 0.87–0.90 for SDS011, and 0.89 for ZH03A. OPC-N2 had only a moderate linear relationship with TEOM (R2≈0.53–0.69 for daily data and 0.43–0.61 for shorter time averages). Quite large dispersion of data and high relative errors of PM2.5 estimation were observed for concentration ranges below 20–30 μg/m3. The impact of high relative humidity level was observed for SDS011 and OPC-N2 devices—clear overestimation of outputs was observed above 80% RH.
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Wang, Chun Sheng, Mu Sai Zhai, and Lei Tian. "Damage Monitoring and Evaluation Using AE Sensors for Existing Concrete Bridges." Key Engineering Materials 525-526 (November 2012): 141–44. http://dx.doi.org/10.4028/www.scientific.net/kem.525-526.141.
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The existing concrete bridges are often required to carry an increasing volume of traffic, higher speed and heavier trucks, so the bridge owners pay more attention to the actual fatigue damage and service safety of such structures. In this paper, Acoustic Emission (AE) sensors are used to monitor and evaluate the fatigue and damage of Yaoxian Bridge, which is the first field AE monitoring using Physical Acoustics Company equipment and sensors in China existing concrete bridge. This AE sensor has fine frequency bandwidth of interest to bridge monitoring, which is applicable to local cracking and damage positions and can monitor fatigue cracks and damage in close-range. In the field inspection, healthy monitoring was conducted at several locations, including the box concrete girder webs, bottom plates and deck plates using AE sensors. Based on AE monitoring data, the fatigue and damage conditions of box concrete girders was analyzed in order to propose theoretical basis and the rational advices for Yaoxian Bridge maintenance.
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Bagheri, H., M. Schmitt, P. d’Angelo, and X. X. Zhu. "EXPLORING THE APPLICABILITY OF SEMI-GLOBAL MATCHING FOR SAR-OPTICAL STEREOGRAMMETRY OF URBAN SCENES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 43–48. http://dx.doi.org/10.5194/isprs-archives-xlii-2-43-2018.
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Nowadays, a huge archive of data from different satellite sensors is available for diverse objectives. While every new sensor provides data with ever higher resolution and more sophisticated special properties, using the data acquired by only one sensor might sometimes still not be enough. As a result, data fusion techniques can be applied with the aim of jointly exploiting data from multiple sensors. One example is to produce 3D information from optical and SAR imagery by employing stereogrammetric methods. This paper investigates the application of the semi-global matching (SGM) framework for 3D reconstruction from SAR-optical image pairs. For this objective, first a multi-sensor block adjustment is carried out to align the optical image with a corresponding SAR image using an RPC-based formulation of the imaging models. Then, a dense image matching, SGM is implemented to investigate its potential for multi-sensor 3D reconstruction. While the results achieved with Worldview-2 and TerraSAR-X images demonstrate the general feasibility of SARoptical stereogrammetry, they also show the limited applicability of SGM for this task in its out-of-the-box formulation.
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Fan, Guangpeng, Yanqi Dong, Danyu Chen, and Feixiang Chen. "New Method for Forest Resource Data Collection Based on Smartphone Fusion with Multiple Sensors." Mobile Information Systems 2020 (May 18, 2020): 1–11. http://dx.doi.org/10.1155/2020/5736978.
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Tree parameter measurement is an important part of forest resource monitoring. Smartphones play an important role in forest resource surveys. Although sensors inside smartphones, such as gyroscopes and angle sensors, can meet the needs of the public for entertainment or games, the measurement accuracy in professional forest resource monitoring is slightly insufficient. In this paper, a method of collecting tree measurement factors based on personal smart space fusion with a variety of high-precision sensors is proposed. First of all, a high-precision attitude sensor measurement module and a laser ranging module are organically integrated and packaged in a black box. The smartphone is then connected to the sensor box using a magnet sheet, and the working personnel can determine key parameters in the forest stand by holding it. Finally, in order to verify the accuracy of the method, the measured values in this paper are compared with the reference values. The root mean square error (RMSE) of the tree position in the X and Y directions was 0.114 m and 0.147 m, the relative deviations (rBias) were 0.95% and 0.39%, and the average RMSE was 0.186 m. The RMSEs measured by tree height and diameter at breast height (DBH) were 0.98 m and 2.24 cm, the relative root mean square error (rRMSE) was 5.87% and 13.46%, and the relative deviations (rBias) were −1.40% and −1.06%, respectively. Therefore, the method of forest stand parameter measurement based on personal smart space fusion multitype sensors proposed in this paper can be effectively applied to forest resource data collection.
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Vogt, Matthias, Philipp Schneider, Nuria Castell, and Paul Hamer. "Assessment of Low-Cost Particulate Matter Sensor Systems against Optical and Gravimetric Methods in a Field Co-Location in Norway." Atmosphere 12, no. 8 (July 27, 2021): 961. http://dx.doi.org/10.3390/atmos12080961.
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The increased availability of commercially-available low-cost air quality sensors combined with increased interest in their use by citizen scientists, community groups, and professionals is resulting in rapid adoption, despite data quality concerns. We have characterized three out-the-box PM sensor systems under different environmental conditions, using field colocation against reference equipment. The sensor systems integrate Plantower 5003, Sensirion SPS30 and Alphasense OCP-N3 PM sensors. The first two use photometry as a measuring technique, while the third one is an optical particle counter. For the performance evaluation, we co-located 3 units of each manufacturer and compared the results against optical (FIDAS) and gravimetric (KFG) methods for a period of 7 weeks (28 August to 19 October 2020). During the period from 2nd and 5th October, unusually high PM concentrations were observed due to a long-range transport episode. The results show that the highest correlations between the sensor systems and the optical reference are observed for PM1, with coefficients of determination above 0.9, followed by PM2.5. All the sensor units struggle to correctly measure PM10, and the coefficients of determination vary between 0.45 and 0.64. This behavior is also corroborated when using the gravimetric method, where correlations are significantly higher for PM2.5 than for PM10, especially for the sensor systems based on photometry. During the long range transport event the performance of the photometric sensors was heavily affected, and PM10 was largely underestimated. The sensor systems evaluated in this study had good agreement with the reference instrumentation for PM1 and PM2.5; however, they struggled to correctly measure PM10. The sensors also showed a decrease in accuracy when the ambient size distribution was different from the one for which the manufacturer had calibrated the sensor, and during weather conditions with high relative humidity. When interpreting and communicating air quality data measured using low-cost sensor systems, it is important to consider such limitations in order not to risk misinterpretation of the resulting data.
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Antunes, Ricardo, Paul Jacob, Andrew Meyer, Michael A. Conditt, Martin W. Roche, and Matthias A. Verstraete. "Accuracy of Measuring Knee Flexion after TKA through Wearable IMU Sensors." Journal of Functional Morphology and Kinesiology 6, no. 3 (July 5, 2021): 60. http://dx.doi.org/10.3390/jfmk6030060.
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Wearable sensors have the potential to facilitate remote monitoring for patients recovering from knee replacement surgery. Using IMU sensors attached to the patients’ leg, knee flexion can be monitored while the patients are recovering in their home environment. Ideally, these flexion angle measurements will have an accuracy and repeatability at least on par with current clinical standards. To validate the clinical accuracy of a two-sensor IMU system, knee flexion angles were measured in eight subjects post-TKA and compared with other in-clinic angle measurement techniques. These sensors are aligned to the patients’ anatomy by taking a pose resting their operated leg on a box; an initial goniometer measurement defines the patients’ knee flexion while taking that pose. The repeatability and accuracy of the system was subsequently evaluated by comparing knee flexion angles against goniometer readings and markerless optical motion capture data. The alignment pose was repeatable with a mean absolute error of 1.6 degrees. The sensor accuracy through the range of motion had a mean absolute error of 2.6 degrees. In conclusion, the presented sensor system facilitates a repeatable and accurate measurement of the knee flexion, holding the potential for effective remote monitoring of patients recovering from knee replacement surgery.
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Stefanou, Thekla, David Guiraud, Charles Fattal, Christine Azevedo-Coste, and Lucas Fonseca. "Frequency-Domain sEMG Classification Using a Single Sensor." Sensors 22, no. 5 (March 2, 2022): 1939. http://dx.doi.org/10.3390/s22051939.
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Working towards the development of robust motion recognition systems for assistive technology control, the widespread approach has been to use a plethora of, often times, multi-modal sensors. In this paper, we develop single-sensor motion recognition systems. Utilising the peripheral nature of surface electromyography (sEMG) data acquisition, we optimise the information extracted from sEMG sensors. This allows the reduction in sEMG sensors or provision of contingencies in a system with redundancies. In particular, we process the sEMG readings captured at the trapezius descendens and platysma muscles. We demonstrate that sEMG readings captured at one muscle contain distinct information on movements or contractions of other agonists. We used the trapezius and platysma muscle sEMG data captured in able-bodied participants and participants with tetraplegia to classify shoulder movements and platysma contractions using white-box supervised learning algorithms. Using the trapezius sensor, shoulder raise is classified with an accuracy of 99%. Implementing subject-specific multi-class classification, shoulder raise, shoulder forward and shoulder backward are classified with a 94% accuracy amongst object raise and shoulder raise-and-hold data in able bodied adults. A three-way classification of the platysma sensor data captured with participants with tetraplegia achieves a 95% accuracy on platysma contraction and shoulder raise detection.
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Roh, Hyeonhee, Inkyum Kim, Jinsoo Yu, and Daewon Kim. "Self-Power Dynamic Sensor Based on Triboelectrification for Tilt of Direction and Angle." Sensors 18, no. 7 (July 22, 2018): 2384. http://dx.doi.org/10.3390/s18072384.
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With the great development of the Internet of Things (IoT), the use of sensors have increased rapidly because of the importance in the connection between machines and people. A huge number of IoT sensors consume vast amounts of electrical power for stable operation and they are also used for a wide range of applications. Therefore, sensors need to operate independently, sustainably, and wirelessly to improve their capabilities. In this paper, we propose an orientation and the tilt triboelectric sensor (OT-TES) as a self-powered active sensor, which can simultaneously sense the tilting direction and angle by using the two classical principles of triboelectrification and electrostatic induction. The OT-TES device consists of a rectangular acrylic box containing polytetrafluoroethylene (PTFE) balls moved by gravity. The output voltage and current were 2 V and 20 nA, respectively, with a PTFE ball and Al electrode. The multi-channel system was adopted for measuring the degree and direction of tilt by integrating the results of measured electrical signals from the eight electrodes. This OT-TES can be attached on the equipment for drones or divers to measure their stability. As a result, this proposed device is expected to expand the field of TES, as a sensor for sky and the underwater.
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Badura, Marek, Piotr Batog, Anetta Drzeniecka-Osiadacz, and Piotr Modzel. "Low- and Medium-Cost Sensors for Tropospheric Ozone Monitoring—Results of an Evaluation Study in Wrocław, Poland." Atmosphere 13, no. 4 (March 29, 2022): 542. http://dx.doi.org/10.3390/atmos13040542.
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The paper presents the results of a 1.5-year evaluation study of low- and medium-cost ozone sensors. The tests covered electrochemical sensors: SensoriC O3 3E 1 (City Technology) and semiconductor gas sensors: SM50 OZU (Aeroqual), SP3-61-00 (FIS) and MQ131 (Winsen). Three copies of each sensor were enclosed in a measurement box and placed near the reference analyser (MLU 400). In the case of SensoriC O3 3E 1 sensors, the R2 values for the 1-h data were above 0.90 for the first 9 months of deployment, but a performance deterioration was observed in the subsequent months (R2 ≈ 0.6), due to sensor ageing processes. High linear relationships were observed for the SM50 devices (R2 > 0.94), but some periodic data offsets were reported, making regular checking and recalibration necessary. Power-law functions were used in the case of SP3-61-00 (R2 = 0.6–0.7) and MQ131 (R2 = 0.4–0.7). Improvements in the fittings were observed for models that included temperature and relative humidity data. In the case of SP3-61-00, the R2 values increased to above 0.82, while for MQ131 they increased to above 0.86. The study also showed that the measurement uncertainty of tested sensors meets the EU Directive 2008/50/EC requirements for indicative measurements and, in some cases, even for fixed measurements.
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Ying, Song, Lei Wang, and Wen Yuan Zhao. "The Noise Analysis of Fluid Systemsin Solid-State Nanopore Sensors." Applied Mechanics and Materials 419 (October 2013): 517–20. http://dx.doi.org/10.4028/www.scientific.net/amm.419.517.
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The solid-state nanopore sensor offers a versatile platform for the rapid, label-free electrical detection and analysis of single molecules, especially on DNA sequencing. However, the overall signal-to-noise ratio (SNA) is a major challenge in sequencing applications. In our work, two different fluid systems made by metal and plexiglass have been designed to improve the signal to noise ratio of the solid-state nanopore sensor. From the measurements on the noise power spectra with a variety of conditions, it is found that plexiglass fluid system coupled with shielding box produces a good quality of electric signals on nanopore sensors.
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Maier, Guenther A., Martin Krobath, Clemens Kremsner, and Anton Köck. "A Novel Device for Functional Evaluation of Gas Sensing Layers." Proceedings 2, no. 13 (December 3, 2018): 1012. http://dx.doi.org/10.3390/proceedings2131012.
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Chemical gas sensors are operated at elevated temperatures and the actual temperature has a tremendous influence on sensitivity and selectivity. From that perspective, precise temperature control over the chip is an absolute requirement. Next to a stable heating system, a controlled gas flow in the test box is required. The test gases should not cool down the sensor surface too much and not be heated up by the heater. To make the material integration easy and reduce the costs for sensor platforms, often rather large sensor devices are fabricated. We demonstrate that a combined approach of thermal analysis and computational fluid dynamics enables the co-design of gas flow path and heater to archive precise temperature conditions at the sensor material and in the surrounding test gas atmosphere.
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Andreou, Alexandra Z. "DDX41: a multifunctional DEAD-box protein involved in pre-mRNA splicing and innate immunity." Biological Chemistry 402, no. 5 (March 15, 2021): 645–51. http://dx.doi.org/10.1515/hsz-2020-0367.
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Abstract DEAD-box helicases participate in nearly all steps of an RNA’s life. In recent years, increasing evidence has shown that several family members are multitasking enzymes. They are often involved in different processes, which may be typical for RNA helicases, such as RNA export and translation, or atypical, e.g., acting as nucleic acid sensors that activate downstream innate immune signaling. This review focuses on the DEAD-box protein DDX41 and summarizes our current understanding of its roles as an innate immunity sensor in the cytosol and in pre-mRNA splicing in the nucleus and discusses DDX41’s involvement in disease.
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Kim, Min-Joong, Sung-Hun Yu, Tong-Hyun Kim, Joo-Uk Kim, and Young-Min Kim. "On the Development of Autonomous Vehicle Safety Distance by an RSS Model Based on a Variable Focus Function Camera." Sensors 21, no. 20 (October 11, 2021): 6733. http://dx.doi.org/10.3390/s21206733.
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Today, a lot of research on autonomous driving technology is being conducted, and various vehicles with autonomous driving functions, such as ACC (adaptive cruise control) are being released. The autonomous vehicle recognizes obstacles ahead by the fusion of data from various sensors, such as lidar and radar sensors, including camera sensors. As the number of vehicles equipped with such autonomous driving functions increases, securing safety and reliability is a big issue. Recently, Mobileye proposed the RSS (responsibility-sensitive safety) model, which is a white box mathematical model, to secure the safety of autonomous vehicles and clarify responsibility in the case of an accident. In this paper, a method of applying the RSS model to a variable focus function camera that can cover the recognition range of a lidar sensor and a radar sensor with a single camera sensor is considered. The variables of the RSS model suitable for the variable focus function camera were defined, the variable values were determined, and the safe distances for each velocity were derived by applying the determined variable values. In addition, as a result of considering the time required to obtain the data, and the time required to change the focal length of the camera, it was confirmed that the response time obtained using the derived safe distance was a valid result.
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Brunello, Andrea, Andrea Urgolo, Federico Pittino, András Montvay, and Angelo Montanari. "Virtual Sensing and Sensors Selection for Efficient Temperature Monitoring in Indoor Environments." Sensors 21, no. 8 (April 13, 2021): 2728. http://dx.doi.org/10.3390/s21082728.
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Real-time estimation of temperatures in indoor environments is critical for several reasons, including the upkeep of comfort levels, the fulfillment of legal requirements, and energy efficiency. Unfortunately, setting an adequate number of sensors at the desired locations to ensure a uniform monitoring of the temperature in a given premise may be troublesome. Virtual sensing is a set of techniques to replace a subset of physical sensors by virtual ones, allowing the monitoring of unreachable locations, reducing the sensors deployment costs, and providing a fallback solution for sensor failures. In this paper, we deal with temperature monitoring in an open space office, where a set of physical sensors is deployed at uneven locations. Our main goal is to develop a black-box virtual sensing framework, completely independent of the physical characteristics of the considered scenario, that, in principle, can be adapted to any indoor environment. We first perform a systematic analysis of various distance metrics that can be used to determine the best sensors on which to base temperature monitoring. Then, following a genetic programming approach, we design a novel metric that combines and summarizes information brought by the considered distance metrics, outperforming their effectiveness. Thereafter, we propose a general and automatic approach to the problem of determining the best subset of sensors that are worth keeping in a given room. Leveraging the selected sensors, we then conduct a comprehensive assessment of different strategies for the prediction of temperatures observed by physical sensors based on other sensors’ data, also evaluating the reliability of the generated outputs. The results show that, at least in the given scenario, the proposed black-box approach is capable of automatically selecting a subset of sensors and of deriving a virtual sensing model for an accurate and efficient monitoring of the environment.
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Demir, Ugur, Pelin Süle, and Mustafa Caner Aküner. "Investigation on the Output Signal of Rotational Speed Sensor for Different Flux Surfaces between Gear Wheel and Sensor." Applied Mechanics and Materials 850 (August 2016): 172–78. http://dx.doi.org/10.4028/www.scientific.net/amm.850.172.
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Rotational Speed Sensors are typically used to measure rotational speed in automotive application such as ABS (Anti-lock Braking System), ASR (Anti Slip Regulation) or Gear Box. In terms of application area, rotational speed sensors transmit very important signal from gear wheel to ECU (Electronic Control Units). The output signal of rotational speed sensor (RSS) may not provide exact solution in high speed situation because RSS is a kind of inductive sensor which has discharge and charge time. Thus, response time of RSS may lead a problem for exact speed measurement while the output signal is settling. In this study to evaluate different flux surfaces, both low speed @0.8RPM and high speed @3992 RPM, 6 experiments were performed for normal, convex and concave teeth setups. It has been seen that the output signal form of convex teeth setup is more appropriate than normal teeth setup and concave teeth setup for sinus signal.
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Lee, Sung-Kyu, Seung-Hyun Hong, Won-Ho Jun, and Youn-Sik Hong. "Multi-Sensor Data Fusion with a Reconfigurable Module and Its Application to Unmanned Storage Boxes." Sensors 22, no. 14 (July 19, 2022): 5388. http://dx.doi.org/10.3390/s22145388.
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We present a multi-sensor data fusion model based on a reconfigurable module (RM) with three fusion layers. In the data layer, raw data are refined with respect to the sensor characteristics and then converted into logical values. In the feature layer, a fusion tree is configured, and the values of the intermediate nodes are calculated by applying predefined logical operations, which are adjustable. In the decision layer, a final decision is made by computing the value of the root according to predetermined equations. In this way, with given threshold values or sensor characteristics for data refinement and logic expressions for feature extraction and decision making, we reconstruct an RM that performs multi-sensor fusion and is adaptable for a dedicated application. We attempted to verify its feasibility by applying the proposed RM to an actual application. Considering the spread of the COVID-19 pandemic, an unmanned storage box was selected as our application target. Four types of sensors were used to determine the state of the door and the status of the existence of an item inside it. We implemented a prototype system that monitored the unmanned storage boxes by configuring the RM according to the proposed method. It was confirmed that a system built with only low-cost sensors can identify the states more reliably through multi-sensor data fusion.
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Lee, Ju-hwan, Junesuk Lee, and Soon-Yong Park. "3D Pose Recognition System of Dump Truck for Autonomous Excavator." Applied Sciences 12, no. 7 (March 29, 2022): 3471. http://dx.doi.org/10.3390/app12073471.
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The purpose of an excavator is to dig up materials and load them onto heavy-duty dump trucks. Typically, an excavator is positioned at the rear of the dump truck when loading. In order to automate this process, this paper proposes a system that employs a combined stereo camera and two LiDAR sensors to determine the three-dimensional (3D) position of the truck’s cargo box and to analyze its loading space. Sparse depth information acquired from the two LiDAR sensors is used to detect points on the door of the cargo box and establish the plane on its rear side. Dense depth information of the cargo box acquired from the stereo camera sensor is projected onto the plane of the box’s rear to estimate its initial 3D position. In the next step, the point cloud sampled along the long shaft of the edge of the cargo box is used as the input of the Iterative Closest Point algorithm to calculate a more accurate cargo box position. The data collected from the stereo camera are then used to determine the 3D position of the cargo box and provide an estimate of the volume of the load along with the 3D position of the loading space to the excavator. In order to demonstrate the efficiency of the proposed method, a mock-up of a heavy-duty truck cargo box was created, and the volume of the load in the cargo box was analyzed.
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Gebregiorgis, Abebe Sine, Pierre-Emmanuel Kirstetter, Yang E. Hong, Nicholas J. Carr, Jonathan J. Gourley, Walt Petersen, and Yaoyao Zheng. "Understanding Overland Multisensor Satellite Precipitation Error in TMPA-RT Products." Journal of Hydrometeorology 18, no. 2 (January 12, 2017): 285–306. http://dx.doi.org/10.1175/jhm-d-15-0207.1.
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Abstract The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) has provided the global community a widely used multisatellite (and multisensor type) estimate of quasi-global precipitation. One of the TMPA level-3 products, 3B42RT/TMPA-RT (where RT indicates real time), is a merged product of microwave (MW) and infrared (IR) precipitation estimates, which attempts to exploit the most desirable aspects of both types of sensors, namely, quality rainfall estimation and spatiotemporal resolution. This study extensively and systematically evaluates multisatellite precipitation errors by tracking the sensor-specific error sources and quantifying the biases originating from multiple sensors. High-resolution, ground-based radar precipitation estimates from the Multi-Radar Multi-Sensor (MRMS) system, developed by the National Severe Storms Laboratory (NSSL), are utilized as reference data. The analysis procedure involves segregating the grid precipitation estimate as a function of sensor source, decomposing the bias, and then quantifying the error contribution per grid. The results of this study reveal that while all three aspects of detection (i.e., hit, missed-rain, and false-rain biases) contribute to the total bias associated with IR precipitation estimates, overestimation bias (positive hit bias) and missed precipitation are the dominant error sources for MW precipitation estimates. Considering only MW sensors, the TRMM Microwave Imager (TMI) shows the largest missed-rain and overestimation biases (nearly double that of the other MW estimates) per grid box during the summer and winter seasons. The Special Sensor Microwave Imagers/Sounders (SSMIS on board F17 and F16) also show major error during winter and spring, respectively.
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Kapp, Sebastian, Frederik Lauer, Fabian Beil, Carl C. Rheinländer, Norbert Wehn, and Jochen Kuhn. "Smart Sensors for Augmented Electrical Experiments." Sensors 22, no. 1 (December 30, 2021): 256. http://dx.doi.org/10.3390/s22010256.
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With the recent increase in the use of augmented reality (AR) in educational laboratory settings, there is a need for new intelligent sensor systems capturing all aspects of the real environment. We present a smart sensor system meeting these requirements for STEM (science, technology, engineering, and mathematics) experiments in electrical circuits. The system consists of custom experiment boxes and cables combined with an application for the Microsoft HoloLens 2, which creates an AR experiment environment. The boxes combine sensors for measuring the electrical voltage and current at the integrated electrical components as well as a reconstruction of the currently constructed electrical circuit and the position of the sensor box on a table. Combing these data, the AR application visualizes the measurement data spatially and temporally coherent to the real experiment boxes, thus fulfilling demands derived from traditional multimedia learning theory. Following an evaluation of the accuracy and precision of the presented sensors, the usability of the system was evaluated with n=20 pupils in a German high school. In this evaluation, the usability of the system was rated with a system usability score of 94 out of 100.
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Zhang, Ling, Jianye Liu, Jizhou Lai, and Zhi Xiong. "Performance Analysis of Adaptive Neuro Fuzzy Inference System Control for MEMS Navigation System." Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/961067.
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Characterized by small volume, low cost, and low power, MEMS inertial sensors are widely concerned and applied in navigation research, environmental monitoring, military, and so on. Notably in indoor and pedestrian navigation, its easily portable feature seems particularly indispensable and important. However, MEMS inertial sensor has inborn low precision and is impressionable and sometimes goes against accurate navigation or even becomes seriously unstable when working for a period of time and the initial alignment and calibration are invalid. A thought of adaptive neuro fuzzy inference system (ANFIS) is relied on, and an assistive control modulated method is presented in this paper, which is newly designed to improve the inertial sensor performance by black box control and inference. The repeatability and long-time tendency of the MEMS sensors are tested and analyzed by ALLAN method. The parameters of ANFIS models are trained using reasonable fuzzy control strategy, with high-precision navigation system for reference as well as MEMS sensor property. The MEMS error nonlinearity is measured and modulated through the peculiarity of the fuzzy control convergence, to enhance the MEMS function and the whole MEMS system property. Performance of the proposed model has been experimentally verified using low-cost MEMS inertial sensors, and the MEMS output error is well compensated. The test results indicate that ANFIS system trained by high-precision navigation system can efficiently provide corrections to MEMS output and meet the requirement on navigation performance.
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Espinoza, Juan Diego Arias, Viacheslav Sazhnikov, Sami Sabik, Dmitriy Ionov, Edsger Smits, Sandeep Kalathimekkad, Geert Van Steenberge, et al. "Flexible Optical Chemical Sensor Platform for BTX." Procedia Engineering 47 (2012): 607–10. http://dx.doi.org/10.1016/j.proeng.2012.09.220.
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Zhu, Yuanguang, Bin Liu, Sheng Wang, and Zhanbiao Yang. "Development of a FBG Stress Sensor for Geostress Measurement Using RSR Method in Deep Soft Fractured Rock Mass." Applied Sciences 12, no. 4 (February 9, 2022): 1781. http://dx.doi.org/10.3390/app12041781.
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The rheological stress recovery (RSR) method was proposed to obtain measurements of in-situ stress. Rock stress can be evaluated by monitoring the recovery process of stress sensors embedded in rock mass. In order to achieve this application, a novel stress sensor employing the fiber Bragg grating (FBG) technique was designed and manufactured. This stress sensor consisted of three parts: A sensing spherical head, connecting rod, and coupler box. In the sensing spherical head, six independent pressure sensing units were assembled together with a temperature compensation unit. In addition, wavelength division multiplexing (WDM) technology was adopted to ensure that only one fiber splice for each stress sensor is output. The fiber splicing of the sensing units was assembled in the coupler box. The transformation equations from the six pressure sensing units to the stress sensor were established. Furthermore, a calibrating device for the stress sensor was designed, and the general calibration and long-term stability tests were carried out to investigate the characteristic indexes (maximum range, full-range output, and sensitivity) and measurement error (zero drift index, hysteresis index, and repeatability index). Measurement errors showed that the degrees of linearity, zero drift, hysteresis, and repeatability were all below 1.5%. The stability test indicated that the creep of the stress sensor can gradually stabilize in 24 days, and the errors were less than 1.5%. As a result, the stress sensor developed here satisfies the requirements for the RSR method and can be used in field.
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Khan, Fozia Hanif, Rehan Shams, M. Umair, and M. Waseem. "2 Deployment of Sensors to Optimize the Network Coverage Using Genetic Algorithm." Sir Syed Research Journal of Engineering & Technology 1, no. 1 (December 20, 2012): 4. http://dx.doi.org/10.33317/ssurj.v1i1.67.
Full textAbstract:
Wireless Sensor Networks (WSNs) are commonly used in various pervasive applications. Wireless communication is the fastest growing segment of the communication industry that has captured attention of the media and imagination of the public. The purpose of this study is to develop a Genetic algorithm that provides a proper deployment of sensors in order to optimize the coverage problem. The genetic algorithm optimizes the operational modes of sensors nodes for transmitting signals. In this paper we will present the optimum method for the mobile sensors nodes placement, so that transmission of signals and the field coverage can be improved. One of the critical issues of today’s world is to ensure that the quality of services requirement is at an acceptable level and genetic algorithm give the best solution for the above discussed problem. The algorithm has been implemented in MATLAB using its genetic algorithm tool box along with the custom code.
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Khan, Fozia Hanif, Rehan Shams, M. Umair, and M. Waseem. "Deployment of Sensors to Optimize the Network Coverage Using Genetic Algorithm." Sir Syed University Research Journal of Engineering & Technology 2, no. 1 (December 20, 2012): 4. http://dx.doi.org/10.33317/ssurj.v2i1.67.
Full textAbstract:
Wireless Sensor Networks (WSNs) are commonly used in various pervasive applications. Wireless communication is the fastest growing segment of the communication industry that has captured attention of the media and imagination of the public. The purpose of this study is to develop a Genetic algorithm that provides a proper deployment of sensors in order to optimize the coverage problem. The genetic algorithm optimizes the operational modes of sensors nodes for transmitting signals. In this paper we will present the optimum method for the mobile sensors nodes placement, so that transmission of signals and the field coverage can be improved. One of the critical issues of today’s world is to ensure that the quality of services requirement is at an acceptable level and genetic algorithm give the best solution for the above discussed problem. The algorithm has been implemented in MATLAB using its genetic algorithm tool box along with the custom code.
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da Silva, Tonny José Araújo, Edna Maria Bonfim-Silva, Adriano Bicioni Pacheco, Thiago Franco Duarte, Helon Hébano de Freitas Sousa, and Jefferson Vieira José. "Evaluation of Various Soil Moisture Sensors in Four Different Soil Types." Applied Engineering in Agriculture 34, no. 6 (2018): 963–71. http://dx.doi.org/10.13031/aea.12712.
Full textAbstract:
Abstract.Accurate measurements of soil moisture content can contribute to resource conservation in irrigated systems. The objective of this study was to evaluate various soil moisture sensors (a porous cup tensiometer, Diviner 2000, PR2, XH300, PM100, and ML3; the mention of model names does not constitute an implied endorsement) used in four different soil types. The experiment was conducted inside a greenhouse using a specially constructed box that contained the soil samples. The soil samples were first saturated and subsequently drained before starting the measurements. The soil moisture content was determined by the oven-drying method. Using the standard deviation of the sensor readings, regression analyses were performed, resulting in calibration equations and coefficient of determination (R2) values for each sensor and soil type combination. The porous cup tensiometer, Diviner 2000, PR2, and ML3 measurements resulted in excellent R2 values that exceeded 0.95 for the four soils. However, measurements with the XH300 and PM100 sensors resulted in R2 values of 0.37 to 0.86 and 0.61 to 0.94, respectively, limiting their scientific applicability for the studied soils. Therefore, the porous cup tensiometer, Diviner 2000, PR2, and ML3 estimated the soil moisture content with greater confidence than did the other sensors and with an error of less than 5%. Keywords: Calibration, Tensiometer, Volumetric water content.
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Mas`udia, Putri Elfa, Bima Eka Samudra, Begum Nabiila, Lis Diana Mustafa, and Mochammad Sarosa. "Smart Food Box untuk penunggu pasien di rumah sakit." JURNAL ELTEK 18, no. 2 (October 30, 2020): 38. http://dx.doi.org/10.33795/eltek.v18i2.257.
Full textAbstract:
Saat ini banyak etalase tempat penyimpanan makanan yang diletakkan di rumah sakit maupun di masjid/mushola dengan tujuan berbagi makanan. Tempat penyimpanan makanan (food box) dapat diisi oleh siapapun (sukarelawan) dan dapat digunakan oleh siapapun. Permasalahan yang sering terjadi adalah tempat penyimpanan makanan ini seringkali dalam keadaan kosong, hal ini dikarenakan sukarelawan kesulitan dalam mendapatkan informasi stok makanan yang tersedia didalam box. Selain itu sukarelawan kesulitan dalam hal pemesanan makanan ke warung dan pendistribusian makanan. Maka dari itu, pada penelitian ini dirancang alat Smart Food Box yang dapat memonitoring ketersediaan stok makanan dalam box yang dapat diakses melalui smartphone. Studi kasus yang diambil adalah untuk penunggu pasien di rumah sakit. Smart Food Box pada penelitian ini menggunakan sensor ultrasonik untuk mengetahui level ketinggian dan sensor Load cell sebagai pendeteksi nilai berat dalam box tersebut. Untuk monitoring jarak jauh menggunakan mikrokontroller Arduino ESP 32 berbasis IoT (Internet of Things). Selain itu akan dibuat suatu aplikasi yang dapat dipergunakan oleh sukarelawan dalam pemesanan makanan ke warung terdekat dan pendistribusisan makanan akan diantar langsung oleh pihak warung ke Smart Food Box yang berada di rumah sakit. Dari hasil pengujian Smart Food Box didapatkan bahwa aplikasi berjalan sesuai tujuan, yaitu perubahan nilai yang dibaca oleh sensor dapat ditampilkan dengan baik di aplikasi sesuai dengan jumlah makanan yang dimasukkan maupun diambil dari Smart Food Box.
A food box is a box that can be used to share food with others. Volunteers usually fill the box with food, and other people who need food can get the food without any fees. The food box usually could be found at the mosque, hospital, and any other public facilities. But, the lack of information on food stock provided to the volunteers, sometimes makes the volunteers do not have enough information on when they must refill the box. This research aims to provide a Smart Food Box prototype that can monitor the food stock in the box automatically. Further, food stock information is accessible through smartphones. For the case study, the Smart Food Box is placed at a hospital. This Smart Food Box uses an ultrasonic sensor to get the height level of food inside the box and the load cell sensor to detect the weight of the food inside. And IoT (Internet of Things) based on Arduino ESP 32 microcontroller is used to monitor the box remotely. A mobile application is also developed for volunteers to order food directly to the food shop. The ordered food will be directly sent by the food shop to the Smart Food Box. The Smart Food Box has been tested and it shows good performance. The sensors can gather information on food stock, and the mobile application can show the information to the volunteers accurately.