Search results for: ultrasonic sensors

Authors: Mohamed E. Harb, Enas Moustafa, Shaker Ebrahim, Moataz Soliman

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In this paper pressure detectors were synthesized and characterized using hybrid perovskite/PVDF composites as an active layer. Methylammonium lead iodide (MAPbI₃) was synthesized from methylammonium iodide (MAI) (CH₃NH₃I) and lead iodide (PbI₂). Composites of perovskite/PVDF using different weight ratio were prepared as the active material. PVDF with weights percentages of 6%, 8%, and 10% was used. All prepared materials were investigated by x-ray diffraction (XRD), Fourier transforms infrared spectrum (FTIR) and scanning electron microscopy (SEM). A Versastat 4 Potentiostat Galvanostat instrument was used to perform the current-voltage characteristics of the fabricated sensors. The pressure sensors exhibited a voltage increase with applying different forces. Also, the current-voltage characteristics (CV) showed different effects with applying forces. So, the results showed a good pressure sensing performance.

Keywords: perovskite semiconductor, hybrid perovskite, PVDF, Pressure sensing

Procedia PDF Downloads 205

Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

Procedia PDF Downloads 266

Authors: Miroslav Popelka, Jakub Nožička

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In this paper we deal with using Lego Mindstorms in simulation of robotic systems with respect to cost reduction. Lego Mindstorms kit contains broad variety of hardware components which are required to simulate, program and test the robotics systems in practice. Algorithm programming went in development environment supplied together with Lego kit as in programming language C# as well. Algorithm following the line, which we dealt with in this paper, uses theoretical findings from area of controlling circuits. PID controller has been chosen as controlling circuit whose individual components were experimentally adjusted for optimal motion of robot tracking the line. Data which are determined to process by algorithm are collected by sensors which scan the interface between black and white surfaces followed by robot. Based on discovered facts Lego Mindstorms can be considered for low-cost and capable kit to simulate real robotics systems.

Keywords: LEGO Mindstorms, PID controller, low-cost robotics systems, line follower, sensors, programming language C#, EV3 Home Edition Software

Procedia PDF Downloads 373

Authors: Mauro Callejas-Cuervo, Andrea C. Alarcon-Aldana, Andres F. Ruiz-Olaya, Juan C. Alvarez

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Motion capture (MC) is the construction of a precise and accurate digital representation of a real motion. Systems have been used in the last years in a wide range of applications, from films special effects and animation, interactive entertainment, medicine, to high competitive sport where a maximum performance and low injury risk during training and competition is seeking. This paper presents an inertial and magnetic sensor based technological platform, intended for particular amplitude monitoring and telerehabilitation processes considering an efficient cost/technical considerations compromise. Our platform particularities offer high social impact possibilities by making telerehabilitation accessible to large population sectors in marginal socio-economic sector, especially in underdeveloped countries that in opposition to developed countries specialist are scarce, and high technology is not available or inexistent. This platform integrates high-resolution low-cost inertial and magnetic sensors with adequate user interfaces and communication protocols to perform a web or other communication networks available diagnosis service. The amplitude information is generated by sensors then transferred to a computing device with adequate interfaces to make it accessible to inexperienced personnel, providing a high social value. Amplitude measurements of the platform virtual system presented a good fit to its respective reference system. Analyzing the robotic arm results (estimation error RMSE 1=2.12° and estimation error RMSE 2=2.28°), it can be observed that during arm motion in any sense, the estimation error is negligible; in fact, error appears only during sense inversion what can easily be explained by the nature of inertial sensors and its relation to acceleration. Inertial sensors present a time constant delay which acts as a first order filter attenuating signals at large acceleration values as is the case for a change of sense in motion. It can be seen a damped response of platform virtual in other images where error analysis show that at maximum amplitude an underestimation of amplitude is present whereas at minimum amplitude estimations an overestimation of amplitude is observed. This work presents and describes the platform virtual as a motion capture system suitable for telerehabilitation with the cost - quality and precision - accessibility relations optimized. These particular characteristics achieved by efficiently using the state of the art of accessible generic technology in sensors and hardware, and adequate software for capture, transmission analysis and visualization, provides the capacity to offer good telerehabilitation services, reaching large more or less marginal populations where technologies and specialists are not available but accessible with basic communication networks.

Keywords: inertial sensors, joint amplitude measurement, MEMS, telerehabilitation

Procedia PDF Downloads 259

Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

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Authors: Pakhil Singh, Rahul Singh, Mohammad Saad Alam, Yasser Rafat

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The battery management system is an essential package/system which ensures optimum performance and safety of a battery by monitoring the key essential parameters of the battery like the voltage, current, temperature, state of charge, state of health during charging and discharging. This can be accomplished using outputs of various sensors employed to serve the purpose. The increasing demand for electricity generation from renewable energy sources requires proper storage and hence a proper monitoring system as well. A battery management system is required in wide applications ranging from renewable energy storage systems, off-grid solar PV applications to electric vehicles. The aim of this paper is to study the parameters used in monitoring various battery operating conditions and proposes the usage of the internet of things (IoT) to implement a reliable battery management system.

Keywords: electric vehicles, internet of things, sensors, state of charge, state of health

Procedia PDF Downloads 194

Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

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Authors: Chenlu Zhang, Wanni Zhang, Florian Schaule

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Indoor environment in office buildings directly affects comfort, productivity, health, and well-being of building occupants. Wireless environmental sensor networks have been deployed in many modern offices to monitor and control the indoor environments. However, indoor environmental variables are not strong enough predictors of comfort and productivity levels of every occupant due to personal differences, both physiologically and psychologically. This study proposes human-centric sensor networks that integrate wireless environmental sensors, body area network sensors and participatory sensing technologies to collect data from both environment and human and support building operations. The sensor networks have been tested in one small-size and one medium-size office rooms with 22 participants for five months. Indoor environmental data (e.g., air temperature and relative humidity), physiological data (e.g., skin temperature and Galvani skin response), and physiological responses (e.g., comfort and self-reported productivity levels) were obtained from each participant and his/her workplace. The data results show that: (1) participants have different physiological and physiological responses in the same environmental conditions; (2) physiological variables are more effective predictors of comfort and productivity levels than environmental variables. These results indicate that the human-centric sensor networks can support human-centric building control and improve comfort and productivity in offices.

Keywords: body area network, comfort and productivity, human-centric sensors, internet of things, participatory sensing

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Authors: Vahid Bairami Rad

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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?

Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno

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Authors: Shiuh-Jer Huang, Su-Shean Chen, Sheam-Chyun Lin

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Two-wheel inverted pendulum robot (TWIPR) is designed with two-hub DC motors for human riding and motion control evaluation. In order to measure the tilt angle and angular velocity of the inverted pendulum robot, accelerometer and gyroscope sensors are chosen. The mobile robot’s moving position and velocity were estimated based on DC motor built in hall sensors. The control kernel of this electric mobile robot is designed with embedded Arduino Nano microprocessor. A handle bar was designed to work as steering mechanism. The intelligent model-free fuzzy sliding mode control (FSMC) was employed as the main control algorithm for this mobile robot motion monitoring with different control purpose adjustment. The intelligent controllers were designed for balance control, and moving speed control purposes of this robot under different operation conditions and the control performance were evaluated based on experimental results.

Keywords: balance control, speed control, intelligent controller, two wheel inverted pendulum

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Authors: Mohamed Hafid, Marcel Lacroix

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This study presents an inverse analysis for predicting the thermal conductivities and the heat flux of a high-temperature metallurgical reactor simultaneously. Once these thermal parameters are predicted, the time-varying thickness of the protective phase-change bank that covers the inside surface of the brick walls of a metallurgical reactor can be calculated. The enthalpy method is used to solve the melting/solidification process of the protective bank. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined with the Broyden method (BM). A statistical analysis for the thermal parameter estimation is carried out. The effect of the position of the temperature sensors, total number of measurements and measurement noise on the accuracy of inverse predictions is investigated. Recommendations are made concerning the location of temperature sensors.

Keywords: inverse heat transfer, phase change, metallurgical reactor, Levenberg–Marquardt method, Broyden method, bank thickness

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Authors: Milan Uhríčik, Andrea Soviarová, Zuzana Dresslerová, Peter Palček, Alan Vaško

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The article is focused on the analysis changes dependence on the temperature on the magnesium alloy with 5,48% Al, 0,813% Zn and 0,398% Mn by internal friction. Internal friction is a property of the material is measured on the ultrasonic resonant aparature at a frequency about f = 20470 Hz. The measured temperature range was from 30 °C up to 420 °C. Precisely measurement of the internal friction can be monitored ongoing structural changes and various mechanisms that prevent these changes.

Keywords: internal friction, magnesium alloy, temperature, resonant frequency

Procedia PDF Downloads 699

Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively new concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification by means of a global navigation satellite system (GNSS), cellular connectivity by means of 3G/long-term evolution (LTE) modem, connectivity to on-board diagnostics (OBD), and connectivity to analog and digital sensors by means of a novel design of expansion board. Specifically, the later provides eight analog plus three digital sensor channels, as well as one on-board temperature / relative humidity sensor. The specific device offers a number of adaptability features based on appropriate zero-ohm resistor placement and appropriate value selection for limited number of passive components. For example, although in the standard configuration four voltage analog channels with constant voltage sources for the power supply of the corresponding sensors are available, up to two of these voltage channels can be converted to provide power to the connected sensors by means of corresponding constant current source circuits, whereas all parameters of analog sensor power supply and matching circuits are fully configurable offering the advantage of covering a wide variety of industrial sensors. Note that a key feature of the proposed sensor node, ensuring the reliable operation of the connected sensors, is the appropriate supply of external power to the connected sensors and their proper matching to the IoT sensor node. In standard mode, the IoT sensor node communicates to the data center through 3G/LTE, transmitting all digital/digitized sensor data, IoT device identity, and position. Moreover, the proposed IoT sensor node offers WiFi connectivity to mobile devices (smartphones, tablets) equipped with an appropriate application for the manual registration of vehicle- and driver-specific information, and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware. It is programmed with a high-level language (Python) on top of a modern operating system (Linux). Acknowledgment: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK- 01359, IntelligentLogger).

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

Procedia PDF Downloads 153

Authors: M. A. Izzati, R. Rosazley, A. W. Fareezal, M. Z. Shazana, I. Rushdan, M. Jani

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Ultrasonic probe were using to produce nanofibrillated cellulose (NFC) kenaf core. NFC kenaf core and graphene was mixed using in-situ method with the 5V voltage for 24 hours. The resulting NFC graphene paper was characterized by field emission scanning electron microscopy (FESEM), fourier transformed infrared (FTIR) spectra and thermogavimetric analysis (TGA). The properties of NFC kenaf core graphene paper are compared with properties of pure NFC kenaf core paper.

Keywords: NFC, kenaf core, graphene, in-situ method

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

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Authors: Tomas Vampola, Michael Valášek

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On the basis of simulation-generated failure states of structural elements of a turboprop engine suitable for the busy-jet class of aircraft, an algorithm for early prediction of damage or reduction in functionality of structural elements of the engine is designed and verified with real data obtained at dynamometric testing facilities of aircraft engines. Based on an expanding database of experimentally determined data from temperature and pressure sensors during the operation of turboprop engines, this strategy is constantly modified with the aim of using the minimum number of sensors to detect an inadmissible or deteriorated operating mode of specific structural elements of an aircraft engine. The assembled algorithm for the early prediction of reduced functionality of the aircraft engine significantly contributes to the safety of air traffic and to a large extent, contributes to the economy of operation with positive effects on the reduction of the energy demand of operation and the elimination of adverse effects on the environment.

Keywords: detectability of malfunction, dynamometric testing, prediction of damage, turboprop engine

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Authors: Ursula D. C. Resende, Yan G. Santos, Lucas M. de O. Andrade

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The recent and fast development of the internet, wireless, telecommunication technologies and low-power electronic devices has led to an expressive amount of electromagnetic energy available in the environment and the smart applications technology expansion. These applications have been used in the Internet of Things devices, 4G and 5G solutions. The main feature of this technology is the use of the wireless sensor. Although these sensors are low-power loads, their use imposes huge challenges in terms of an efficient and reliable way for power supply in order to avoid the traditional battery. The radio frequency based energy harvesting technology is especially suitable to wireless power sensors by using a rectenna since it can be completely integrated into the distributed hosting sensors structure, reducing its cost, maintenance and environmental impact. The rectenna is an equipment composed of an antenna and a rectifier circuit. The antenna function is to collect as much radio frequency radiation as possible and transfer it to the rectifier, which is a nonlinear circuit, that converts the very low input radio frequency energy into direct current voltage. In this work, a set of rectennas, mounted on a paper substrate, which can be used for the inner coating of buildings and simultaneously harvest electromagnetic energy from the environment, is proposed. Each proposed individual rectenna is composed of a 2.45 GHz patch antenna and a voltage doubler rectifier circuit, built in the same paper substrate. The antenna contains a rectangular radiator element and a microstrip transmission line that was projected and optimized by using the Computer Simulation Software (CST) in order to obtain values of S11 parameter below -10 dB in 2.45 GHz. In order to increase the amount of harvested power, eight individual rectennas, incorporating metamaterial cells, were connected in parallel forming a system, denominated Electromagnetic Wall (EW). In order to evaluate the EW performance, it was positioned at a variable distance from the internet router, and a 27 kΩ resistive load was fed. The results obtained showed that if more than one rectenna is associated in parallel, enough power level can be achieved in order to feed very low consumption sensors. The 0.12 m2 EW proposed in this work was able to harvest 0.6 mW from the environment. It also observed that the use of metamaterial structures provide an expressive growth in the amount of electromagnetic energy harvested, which was increased from 0. 2mW to 0.6 mW.

Keywords: electromagnetic energy harvesting, metamaterial, rectenna, rectifier circuit

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Authors: A. B. M. Aftabuzzaman, Md. Mahin Hossain, Md. Ifran Sharif Imthi, Md. Razu Ahmed, A. Z. M. Imran

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The goals of the study are to develop a safety system that is combined with a smart helmet to reduce the likelihood of two-wheeler bike accidents and cases of drunk driving. The smart helmet and the limit switch both verify when a biker is wearing a helmet. The presence of alcohol in the rider's breath is detected using alcohol sensors. The bike remains turned off if the rider is not wearing a helmet or if the rider's breath contains alcohol. The bike will not start until the rider is wearing a helmet and there is no alcoholic substance present, indicating that the bike rider has not consumed alcohol. When the rider faces in an accident, instantly the smart helmet hits the ground and respective sensors detect the movement and tilt of the protective helmet and instantly sending the information about the location of accident to the rider's relatives and the crisis contact numbers which are introduced in the smart helmet respective device. So this project finding will ensure safe bike journey and improve safe commercial bike services in Bangladesh.

Keywords: smart helmet, GSM, GPS, bike, biker accident

Procedia PDF Downloads 104

Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf

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Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.

Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer

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Authors: Seyed Mohsen Mousavi, Ali Reza Mahjoub, Bahjat Afshari Razani

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In this work, Fe/ZnO hollow spherical structures with high surface area using the template glucose was prepared by the hydrothermal method using an ultrasonic bath at room temperature was produced and were identified by FT-IR, XRD, FE-SEM and BET. The photocatalytic activity of synthesized spherical Fe/ZnO hollow sphere were studied in the destruction of Congo Red and Methylene Blue as Azo dyes. The results showed that the photocatalytic activity of Fe/ZnO hollow spherical structures is improved compared with ZnO hollow sphere and other morphologys.

Keywords: azo dyes, Fe/ZnO hollow sphere, hollow sphere nanostructures, photocatalyst

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Authors: Aman Johri, Sidhant Sood, Pooja Suresh

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This paper suggests a new and more efficient method of atomization of fuel in a combustor nozzle of a high bypass turbofan engine, using ultrasonic vibrations. Since atomization of fuel just before the fuel spray is injected into the combustion chamber is an important and crucial aspect related to functioning of a propulsion system, the technology suggested by this paper and the experimental analysis on the system components eventually proves to assist in complete and rapid combustion of the fuel in the combustor module of the engine. Current propulsion systems use carburetors, atomization nozzles and apertures in air intake pipes for atomization. The idea of this paper is to deploy new age hybrid technology, namely the Ultrasound Field Effect (UFE) to effectively atomize fuel before it enters the combustion chamber, as a viable and effective method to increase efficiency and improve upon existing designs. The Ultrasound Field Effect is applied axially, on diametrically opposite ends of an atomizer tube that gloves onto the combustor nozzle, where the fuel enters and exits under a pre-defined pressure. The Ultrasound energy vibrates the fuel particles to a breakup frequency. At reaching this frequency, the fuel particles start disintegrating into smaller diameter particles perpendicular to the axis of application of the field from the parent boundary layer of fuel flow over the baseplate. These broken up fuel droplets then undergo swirling effect as per the original nozzle design, with a higher breakup ratio than before. A significant reduction of the size of fuel particles eventually results in an increment in the propulsive efficiency of the engine. Moreover, the Ultrasound atomizer operates within a control frequency such that effects of overheating and induced vibrations are least felt on the overall performance of the engine. The design of an electrical manifold for the multiple-nozzle system over a typical can-annular combustor is developed along with this study, such that the product can be installed and removed easily for maintenance and repairing, can allow for easy access for inspections and transmits least amount of vibrational energy to the surface of the combustor. Since near-field ultrasound is used, the vibrations are easily controlled, thereby successfully reducing vibrations on the outer shell of the combustor. Experimental analysis is carried out on the effect of ultrasonic vibrations on flowing jet turbine fuel using an ultrasound generator probe and results of an effective decrease in droplet size across a constant diameter, away from the boundary layer of flow is noted using visual aid by observing under ultraviolet light. The choice of material for the Ultrasound inducer tube and crystal along with the operating range of temperatures, pressures, and frequencies of the Ultrasound field effect are also studied in this paper, while taking into account the losses incurred due to constant vibrations and thermal loads on the tube surface.

Keywords: atomization, ultrasound field effect, titanium mesh, breakup frequency, parent boundary layer, baseplate, propulsive efficiency, jet turbine fuel, induced vibrations

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Authors: Mohamed Farhat O. Hameed, Yasamin K. A. Alrayk, A. A Shaalan, S. S. A. Obayya

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The surface plasmon resonance (SPR) sensors are widely used due to its high sensitivity with molecular labels free. The commercial SPR sensors depend on the conventional prism-coupled configuration. However, this type of configuration suffers from miniaturization and integration. Therefore, the search for compact, portable and highly sensitive SPR sensors becomes mandatory.In this paper, sensitivity enhancement of a novel photonic crystal fiber biosensoris introduced and studied. The suggested design has microstructure of air holes in the core region surrounded by two large semicircular metallized channels filled with the analyte. The inner surfaces of the two channels are coated by a silver layer followed by a gold layer.The simulation results are obtained using full vectorial finite element methodwith perfect matched layer (PML) boundary conditions. The proposed design depends on bimetallic configuration to enhance the biosensor sensitivity. Additionally, the suggested biosensor can be used for multi-channel/multi-analyte sensing. In this study, the sensor geometrical parameters are studied to maximize the sensitivity for the two polarized modes. The numerical results show that high refractive index sensitivity of 4750 nm/RIU (refractive index unit) and 4300 nm/RIU can be achieved for the quasi (transverse magnetic) TM and quasi (transverse electric) TE modes of the proposed biosensor, respectively. The reportedbiosensor has advantages of integration of microfluidics setup, waveguide and metallic layers into a single structure. As a result, compact biosensor with better integration compared to conventional optical fiber SPR biosensors can be obtained.

Keywords: photonic crystal fibers, gold, silver, surface plasmon, biosensor

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Authors: Ebrahim Farahmand, Ali Mahani

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Wireless sensor networks (WSNs) can facilitate continuous monitoring of patients and increase early detection of emergency conditions and diseases. High density WSNs helps us to accurately monitor a remote environment by intelligently combining the data from the individual nodes. Due to energy capacity limitation of sensors, enhancing the lifetime and the reliability of WSNs are important factors in designing of these networks. The clustering strategies are verified as effective and practical algorithms for reducing energy consumption in WSNs and can tackle WSNs limitations. In this paper, an Energy-efficient weight-based Clustering Protocol (EWCP) is presented. Artificial retina is selected as a case study of WSNs applied in body sensors. Cluster heads’ (CHs) selection is equipped with energy efficient parameters. Moreover, cluster members are selected based on their distance to the selected CHs. Comparing with the other benchmark protocols, the lifetime of EWCP is improved significantly.

Keywords: WSN, healthcare monitoring, weighted based clustering, lifetime

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Authors: A. W. Fareezal, R. Rosazley, M. A. Izzati, M. Z. Shazana, I. Rushdan

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Kenaf cellulose CNT paper production was for lightweight, high strength and excellent flexibility electrical purposes. Aqueous dispersions of kenaf cellulose and varied weight percentage of CNT were combined with the assistance of PEI solution by using ultrasonic probe. The solution was dried using vacuum filter continued with air drying in condition room for 2 days. Circle shape conductive paper was characterized with Fourier transformed infrared (FTIR) spectra, scanning electron microscopy (SEM) and therma gravimetric analysis (TGA).

Keywords: cellulose, CNT paper, PEI solution, electrical conductive paper

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Authors: Miroslav Gutten, Jozef Jurcik, Daniel Korenciak, Milan Sebok, Matej Kuceraa

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This paper deals with the phenomenon of the undesirable detonation combustion in internal combustion engines. A control unit of the engine monitors these detonations using piezoelectric knock sensors. With the control of these sensors the detonations can be objectively measured just outside the car. If this component provides small amplitude of the output voltage it could happen that there would have been in the areas of the engine ignition combustion. The paper deals with the design of a simple device for the detection of this disorder. A construction of the testing device for the knock sensor suitable for diagnostics of knock combustion in internal combustion engines will be presented. The output signal of presented sensor will be described by Bessel functions. Using the first voltage extremes on the characteristics it is possible to create a reference for the evaluation of the polynomial residue. It should be taken into account that the velocity of sound in air is 330 m/s. This sound impinges on the walls of the combustion chamber and is detected by the sensor. The resonant frequency of the clicking of the motor is usually in the range from 5 kHz to 15 kHz. The sensor worked in the field to 37 kHz, which shall be taken into account on an own sensor resonance.

Keywords: diagnostics, knock sensor, measurement, testing device

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Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro

Abstract:

Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.

Keywords: authentication, key-session, security, wireless sensors

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Authors: Evangelia Tsampali, Evangelos Yfantidis, Andreas Ioakim, Maria Stefanidou

Abstract:

The purpose of this paper is the characterization of the effects of crystalline admixtures on concrete. Crystallites, aided by the presence of humidity, form idiomorphic crystals that block cracks and pores resulting in reduced porosity. In this project, two types of crystallines have been employed. The hydrophilic nature of crystalline admixtures helps the components to react with water and cement particles in the concrete to form calcium silicate hydrates and pore-blocking precipitates in the existing micro-cracks and capillaries. The underlying mechanism relies on the formation of calcium silicate hydrates and the resulting deposits of these crystals become integrally bound with the hydrated cement paste. The crystalline admixtures continue to activate throughout the life of the composite material when in the presence of moisture entering the concrete through hairline cracks, sealing additional gaps. The resulting concrete exhibits significantly increased resistance to water penetration under stress. Admixtures of calcium aluminates can also contribute to this healing mechanism in the same manner. However, this contribution is negligible compared to the calcium silicate hydrates due to the abundance of the latter. These crystalline deposits occur throughout the concrete volume and are a permanent part of the concrete mass. High-performance fibre reinforced cementitious composite (HPFRCC) were produced in the laboratory. The specimens were exposed in three healing conditions: water immersion until testing at 15 °C, sea water immersion until testing at 15 °C, and wet/dry cycles (immersion in tap water for 3 days and drying for 4 days). Specimens were pre-cracked at 28 days, and the achieved cracks width were in the range of 0.10–0.50 mm. Furthermore, microstructure observations and Ultrasonic Pulse Velocity tests have been conducted. Based on the outcomes, self-healing related indicators have also been defined. The results show almost perfect healing capability for specimens healed under seawater, better than for specimens healed in water while inadequate for the wet/dry exposure in both of the crystalline types.

Keywords: autogenous self-healing, concrete, crystalline admixtures, ultrasonic pulse velocity test

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Authors: Bongsoo Jeon, Jayoung Kim, Jihong Lee

Abstract:

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor (exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit (IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

Keywords: inertial measurement unit, laser range finder, real-time recognition of the ground shape, proprioceptive sensor

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Authors: Irmak Karaduman, Tugba Corlu, Sezin Galioglu, Burcu Akata, M. Ali Yildirim, Aytunç Ateş, Selim Acar

Abstract:

Breath analysis represents a promising non-invasive, fast and cost-effective alternative to well-established diagnostic and monitoring techniques such as blood analysis, endoscopy, ultrasonic and tomographic monitoring. Portable, non-invasive, and low-cost breath analysis devices are becoming increasingly desirable for monitoring different diseases, especially asthma. Beacuse of this, NO gas sensing at low concentrations has attracted progressive attention for clinical analysis in asthma. Recently, nanomaterials based sensors are considered to be a promising clinical and laboratory diagnostic tool, because its large surface–to–volume ratio, controllable structure, easily tailored chemical and physical properties, which bring high sensitivity, fast dynamic processand even the increasing specificity. Among various nanomaterials, semiconducting metal oxides are extensively studied gas-sensing materials and are potential sensing elements for breathanalyzer due to their high sensitivity, simple design, low cost and good stability.The sensitivities of metal oxide semiconductor gas sensors can be enhanced by adding noble metals. Doping contents, distribution, and size of metallic or metal oxide catalysts are key parameters for enhancing gas selectivity as well as sensitivity. By manufacturing doping MOS structures, it is possible to develop more efficient sensor sensing layers. Zeolites are perhaps the most widely employed group of silicon-based nanoporous solids. Their well-defined pores of sub nanometric size have earned them the name of molecular sieves, meaning that operation in the size exclusion regime is possible by selecting, among over 170 structures available, the zeolite whose pores allow the pass of the desired molecule, while keeping larger molecules outside.In fact it is selective adsorption, rather than molecular sieving, the mechanism that explains most of the successful gas separations achieved with zeolite membranes. In view of their molecular sieving and selective adsorption properties, it is not surprising that zeolites have found use in a number of works dealing with gas sensing devices. In this study, the Cu doped ZnO nanostructure film was produced by SILAR method and investigated the NO gas sensing properties. To obtain the selectivity of the sample, the gases including CO,NH3,H2 and CH4 were detected to compare with NO. The maximum response is obtained at 85 C for 20 ppb NO gas. The sensor shows high response to NO gas. However, acceptable responses are calculated for CO and NH3 gases. Therefore, there are no responses obtain for H2 and CH4 gases. Enhanced to selectivity, Cu doped ZnO nanostructure film was coated with zeolite A thin film. It is found that the sample possess an acceptable response towards NO hardly respond to CO, NH3, H2 and CH4 at room temperature. This difference in the response can be expressed in terms of differences in the molecular structure, the dipole moment, strength of the electrostatic interaction and the dielectric constant. The as-synthesized thin film is considered to be one of the extremely promising candidate materials in electronic nose applications. This work is supported by The Scientific and Technological Research Council of Turkey (TUBİTAK) under Project No, 115M658 and Gazi University Scientific Research Fund under project no 05/2016-21.

Keywords: Cu doped ZnO, electrical characterization, gas sensing, zeolite

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Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

Abstract:

Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

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