Journal articles: 'Automatic identification sensor'

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Álvarez-Bazo, Fernando, Santos Sánchez-Cambronero, David Vallejo, Carlos Glez-Morcillo, Ana Rivas, and Inmaculada Gallego. "A Low-Cost Automatic Vehicle Identification Sensor for Traffic Networks Analysis." Sensors 20, no. 19 (September 29, 2020): 5589. http://dx.doi.org/10.3390/s20195589.

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In recent years, different techniques to address the problem of observability in traffic networks have been proposed in multiple research projects, being the technique based on the installation of automatic vehicle identification sensors (AVI), one of the most successful in terms of theoretical results, but complex in terms of its practical application to real studies. Indeed, a very limited number of studies consider the possibility of installing a series of non-definitive plate scanning sensors in the elements of a network, which allow technicians to obtain a better conclusions when they deal with traffic network analysis such as urbans mobility plans that involve the estimation of traffic flows for different scenarios. With these antecedents, the contributions of this paper are (1) an architecture to deploy low-cost sensors network able to be temporarily installed on the city streets as an alternative of rubber hoses commonly used in the elaboration of urban mobility plans; (2) a design of the low-cost, low energy sensor itself, and (3) a sensor location model able to establish the best set of links of a network given both the study objectives and of the sensor needs of installation. A case of study with the installation of as set of proposed devices is presented, to demonstrate its viability.

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Kushwaha, Ruchi, Rohit Shambharkar, Suyash Gupta, and Monika Malik. "Integration of Block chain Model for Energy Efficient WSN for IOT Application." International Journal for Research in Applied Science and Engineering Technology 11, no. 2 (February 28, 2023): 34–37. http://dx.doi.org/10.22214/ijraset.2023.48942.

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Abstract: Wireless Sensor Networks (WSNs) play a key role in the Internet of Sensor Things (IoST).IoST helps collect data from environments and is used in energy trading, monitoring, smart grids, and more. Connect to the Internet and automate your surveillance system without third-party involvement. An IoST network consists of Sensor nodes that perform environmental monitoring. Wireless Sensor Networks (WSN) and the Internet of Things (I.o.T) have gained popularity in recent years as the underlying infrastructure for connected devices and sensors in a variety of sectors. The data generated by these sensors are used in smart cities, agriculture, transportation systems, healthcare systems, toll collection systems, automatic identification of road data, automatic identification of vehicle license plates, and more. It has become a proposed blockchain mechanism. The main problems and challenges of WSN are effectively reduced by using the LEACH protocol with efficient cluster head selection.

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Giurgiutiu, Victor, and Andrei N. Zagrai. "Embedded Self-Sensing Piezoelectric Active Sensors for On-Line Structural Identification." Journal of Vibration and Acoustics 124, no. 1 (July 1, 2001): 116–25. http://dx.doi.org/10.1115/1.1421056.

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The benefits and limitations of using embedded piezoelectric active sensors for structural identification at ultrasonic frequency are highlighted. An analytical model based on structural vibration theory and theory of piezoelectricity was developed and used to predict the electro-mechanical (E/M) impedance response, as it would be measured at the piezoelectric active sensor’s terminals. The model considers one-dimension structures and accounts for both axial and flexural vibrations. Experiments were conducted on simple specimens in support of the theoretical investigation, and on realistic turbine blade specimen to illustrate the method’s potential. It was shown that E/M impedance spectrum recorded by the piezoelectric active sensor accurately represents the mechanical response of a structure. It was further proved that the response of the structure is not modified by the presence of the sensor, thus validating the latter’s noninvasive characteristics. It is shown that such sensors, of negligible mass, can be permanently applied to the structure creating a nonintrusive sensor array adequate for on-line automatic structural identification and health monitoring. The sensor calibration procedure is outlined. Numerical estimation of the noninvasive properties of the proposed active sensors in comparison with conventional sensors is presented. Self-diagnostics capabilities of the proposed sensors were also investigated and methods for automatic self-test implementation are discussed. The paper underlines that the use of piezoelectric wafer active sensors is not only advantageous, but, in certain situations, may be the sole investigative option, as in the case of precision machinery, small but critical turbine-engine parts, and computer industry components.

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Liu, Li Min. "Internet of Things and RFID Technology." Applied Mechanics and Materials 336-338 (July 2013): 2512–15. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.2512.

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The internet of things is a foundation for connecting things, sensors, actuators, and other smart technologies, thus enabling person-to-object and object-to-object communications. Its applications are concerned to emergency response, intelligent shopping, smart product management, smart meters, home automation, waste management, sustainable urban environment, continuous care and so on. As automatic identification sensor, RFID is a foundational component for the internet of things. In this paper, internet of things, RFID and technical analysis for IoT and RFID are discussed.

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Zhou, Guang-Dong, Mei-Xi Xie, Ting-Hua Yi, and Hong-Nan Li. "Optimal wireless sensor network configuration for structural monitoring using automatic-learning firefly algorithm." Advances in Structural Engineering 22, no. 4 (October 4, 2018): 907–18. http://dx.doi.org/10.1177/1369433218797074.

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Wireless sensor networks are becoming attractive data communication patterns in structural health monitoring systems. Designing and applying effective wireless sensor network–based structural health monitoring systems for large-scale civil infrastructure require a great number of wireless sensors and the optimal wireless sensor networks configuration becomes critical for such spatially separated large structures. In this article, optimal wireless sensor network configuration for structural health monitoring is treated as a discrete optimization problem, where parameter identification and network performance are simultaneously addressed. To solve this rather complicated optimization problem, a novel swarm intelligence algorithm called the automatic-learning firefly algorithm is proposed by integrating the original firefly algorithm with the Lévy flight and the automatic-learning mechanism. In the proposed algorithm, the Lévy flight is adopted to maximize the searching capability in unknown solution space and avoid premature convergence and the automatic-learning mechanism is designed to drive fireflies to move toward better locations at high speed. Numerical experiments are performed on a long-span bridge to demonstrate the effectiveness of the proposed automatic-learning firefly algorithm. Results indicate that automatic-learning firefly algorithm can find satisfactory wireless sensor network configurations, which facilitate easy discrimination of identified mode vectors and long wireless sensor network lifetime, and the innovations in automatic-learning firefly algorithm make it superior to the simple discrete firefly algorithm as to solution quality and convergence speed.

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Beligni, Alessio, Claudio Sbarufatti, Andrea Gilioli, Francesco Cadini, and Marco Giglio. "Robust Identification of Strain Waves due to Low-Velocity Impact with Different Impactor Stiffness." Sensors 19, no. 6 (March 14, 2019): 1283. http://dx.doi.org/10.3390/s19061283.

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Low-velocity impacts represent a major concern for aeronautical structures, sometimes producing barely detectable damage that could severely hamper the aircraft safety, even with regards to metallic structures. For this reason, the development of an automated impact monitoring system is desired. From a passive monitoring perspective, any impact generates a strain wave that can be acquired using sensor networks; signal processing techniques allow for extracting features useful for impact identification, possibly in an automatic way. However, impact wave characteristics are related to the impactor stiffness; this presents a problem for the evaluation of an impact-related feature and for the development of an automatic approach to impact identification. This work discusses the problem of reducing the influence of the impactor stiffness on one of the features typically characterizing the impact event, i.e., the time of arrival (TOA). Two passive sensor networks composed of accelerometers and piezoelectric sensors are installed on two metallic specimens, consisting of an aluminum skin and a sandwich panel, with aluminum skins and NOMEXTM honeycomb core. The effect of different impactor stiffnesses is investigated by resorting to an impact hammer, equipped with different tips. Subsequently, a method for data processing is defined to obtain a feature insensitive to the impactor stiffness, and this method is applied to multiple impact signals for feature uncertainty evaluation.

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Zheng, Jun Hui, and Bing Li. "Fire Seat Intelligent Identification System." Applied Mechanics and Materials 536-537 (April 2014): 421–25. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.421.

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Current fire alarm system can only send fire alarms but failed to report accurately ignition point. So a fire seat intelligent identification system was designed based on wireless sensor networks. The system collects data from wireless sensors using ZigBee wireless communication technology, and carries on cluster analysis on the data set using the improved fuzzy kernel clustering algorithm, and gets accurate clustering results. Finally the ignition source location information is reported to the fire alarm control center. The experimental results show that, compared with other methods, this system realizes real-time monitoring and automatic identification of fire seats, which has virtues of high sensitivity and accuracy and high-speed data transfer.

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Zheng, Fu. "Design of Auto Route Identified Vehicle Model Based on MC9S12XS128." Applied Mechanics and Materials 187 (June 2012): 146–50. http://dx.doi.org/10.4028/www.scientific.net/amm.187.146.

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A vehicle based on automatic route identification technology by using modulated infrared photoelectric sensors was introduced. Circuits for path detecting , motor drive, speed sensor and servo drive were designed. And the controlling strategy was introduced. At last, the assembled model car could run along the black line stably and fast.

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Beiderman, Yevgeny, Mark Kunin, Eli Kolberg, Ilan Halachmi, Binyamin Abramov, Rafael Amsalem, and Zeev Zalevsky. "Automatic solution for detection, identification and biomedical monitoring of a cow using remote sensing for optimised treatment of cattle." Journal of Agricultural Engineering 45, no. 4 (December 21, 2014): 153. http://dx.doi.org/10.4081/jae.2014.418.

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In this paper we show how a novel photonic remote sensing system assembled on a robotic platform can extract vital biomedical parameters from cattle including their heart beating, breathing and chewing activity. The sensor is based upon a camera and a laser using selfinterference phenomena. The whole system intends to provide an automatic solution for detection, identification and biomedical monitoring of a cow. The detection algorithm is based upon image processing involving probability map construction. The identification algorithms involve well known image pattern recognition techniques. The sensor is used on top of an automated robotic platform in order to support animal decision making. Field tests and computer simulated results are presented.

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Li, Dongya, Wei Wang, and De Zhao. "A Practical and Sustainable Approach to Determining the Deployment Priorities of Automatic Vehicle Identification Sensors." Sustainability 14, no. 15 (August 2, 2022): 9474. http://dx.doi.org/10.3390/su14159474.

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Monitoring vehicles’ paths is important for the management and governance of smart sustainable cities, where traffic sensors play a significant role. As a typical sensor, an automatic vehicle identification (AVI) sensor can observe the whereabouts and movements of vehicles. In this article, we introduced an indicator called the deployment score to present the deployment priorities of AVIs for a better reconstruction of vehicles’ paths. The deployment score was obtained based on a programming method for maximizing the accuracy of a recurring vehicle’s path and minimizing the number of AVI sensors. The calculation process is data-driven, where a random-work method was developed to simulate massive path data (tracks of vehicles) according to travel characteristics extracted from finite GPS data. Then, for each simulated path, a path-level bi-level programming model (P-BPM) was constructed to find the optimal layout of the AVI sensors. The solutions of the P-BPM proved to be approximate Pareto optima from a data-driven perspective. Furthermore, the PageRank method was presented to integrate the solutions; thus, the deployment score was obtained. The proposed method was validated in Chengdu City, whose results demonstrated the remarkable value of our approach.

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Shiraishi, M., and H. Sumiya. "Plant Identification From Leaves Using Quasi-Sensor Fusion." Journal of Manufacturing Science and Engineering 118, no. 3 (August 1, 1996): 382–87. http://dx.doi.org/10.1115/1.2831041.

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The method described here identifies plants by using a machine vision technique. This method achieves effective image detection independent of surrounding conditions, dimensionless image detection in each growth stage, and determination of the critical factor for discriminating individual plants. These are the fundamental factors for successful automatic thinning, cropping, weeding, and harvesting using intelligent agricultural robots. Color, aspect ratio, size, radius permutation in leaf profiles, complexity, and curvature are used to classify each plant. Effective discrimination is obtained by using a quasi-sensor fusion combined with a total occurrence range for decision making.

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Mitterer, Tobias, Harald Gietler, Lisa-Marie Faller, and Hubert Zangl. "Artificial Landmarks for Autonomous Vehicles Based on Magnetic Sensors." Proceedings 2, no. 13 (November 20, 2018): 856. http://dx.doi.org/10.3390/proceedings2130856.

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We propose to use an integration process based on Transducer Electronic Data Sheets applied to a magnetic sensor system for the realization of artificial landmarks. Magnetic sensors provide an advantageous alternative in surroundings where GPS and optical sensors do not work. These landmarks can be used by passing autonomous vehicles, e.g., drones, for re-orientation and re-calibration. To facilitate the usage of these landmarks also by any vehicle, known or unknown, a standardized process for automatic connection and identification of the landmarks is suggested. During this process, all necessary information such as protocols, calibration data etc. is made known to the vehicle passing by. Based on the provided information, the vehicle itself can decide whether and how to use the provided sensory information.

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Terada, Kenji, Jun'ichi Yamaguchi, and Masato Nakajima. "An Automatic Identification of Human Faces using Fiber Grating Vision Sensor." IEEJ Transactions on Electronics, Information and Systems 113, no. 12 (1993): 1072–78. http://dx.doi.org/10.1541/ieejeiss1987.113.12_1072.

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Fachri Muhamad and Desy Kristyawati. "RANCANG BANGUN SISTEM KEAMANAN PINTU RUMAH MENGGUNAKAN SENSOR RFID (RADIO FREQUENCY IDENTIFICATION) DAN TOUCH SENSOR BERBASIS ARDUINO UNO." Jurnal Ilmiah Teknik 1, no. 3 (September 29, 2022): 75–83. http://dx.doi.org/10.56127/juit.v1i3.354.

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The current door lock system still uses conventional keys, making it less efficient for homes with many doors because there are too many keys to carry, besides conventional locks are easily opened by thieves. So that a more practical and efficient key is needed, from this statement the idea of making an automatic door unlock device with an RFID (Radio Frequency Identification) Sensor and a Touch Sensor by using an electronic ID card as a key to unlock the door is needed. RFID sensors and touch sensors are supporting components so that the device can be controlled. Solenoid door lock can open the door and unlock the door for 5 seconds via commands previously sent from the RFID sensor and touch sensor. And after that the door closed and locked. Based on the test results, it can be concluded that the simulation of the door safety device can operate properly, according to the design made. RFID reader is used to read the tag code on the electronic ID card. The solenoid can unlock the door if the electronic ID card tag code matches that registered with the Arduino lde program, when the door is closed the solenoid will lock the door within 5 seconds.

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Sun, Weiwei, Hu Shao, Ting Wu, Feng Shao, and Emily Zhu Fainman. "Reliable location of automatic vehicle identification sensors to recognize origin-destination demands considering sensor failure." Transportation Research Part C: Emerging Technologies 136 (March 2022): 103551. http://dx.doi.org/10.1016/j.trc.2021.103551.

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Ho, Chao Ching, and Dan Wen Kuo. "IEEE 1451-Based Sensor Interfacing and Data Fusion for Fire Smoke Detection." Key Engineering Materials 613 (May 2014): 219–27. http://dx.doi.org/10.4028/www.scientific.net/kem.613.219.

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The performance of a fire sensor has a significant effect on fire detection. Today’s fire alarm systems, such as smoke and heat sensors, however are generally limited to a close proximity to the fire; and cannot provide additional information about fire circumstances. Thus, it is essential to design a suite of low-cost networked sensors that provide the capability of performing distributed measurement and control in real time. In this work, a wireless sensor system was developed for fire detection. The purpose of this paper is to analyze the integration of traditional fire sensors into intelligent fire management systems by using the smart transducer concept. An automated video processing sensor for fire smoke monitoring applications is integrated into an surveillance network as a case study and supported sensor fusion assessment to improve the resistance to nuisance alarms. The proposed sensor system for fire detection was developed to reconcile issues related to proliferation and interoperability, and the architecture can support a smart transducer interface (IEEE 1451). The proposed embedded system for STIM (smart transducer interface module) and NCAP (network capable application processor) will be implemented with DSP. To realize the self-identification of transducers and plug-and-play connections, a transducer electronic data sheet (TEDS) is also stored inside the DSP. The acquired sensor data are pre-processed and applied to discriminate nuisance sources. The IEEE 1451 standard has been integrated into an automatic video-based fire smoke detection system. The proposed architecture has been tested on an experimental setup with the purpose of monitoring fire incidents successfully.

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Kim, Hankil, Jaehyun Park, and Hoekyung Jung. "Automatic control system based on iot data identification." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 3 (September 1, 2020): 1525. http://dx.doi.org/10.11591/ijeecs.v19.i3.pp1525-1532.

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Recently, as the Internet of Things (IoT) technology has developed, researches are rigorously conducted to construct smart environments such as smart home, smart grid, and industrial IoT. However, currently existing systems consists of a series of events, and even if an existing task is running, unnecessary work still occurs as both works happen simultaneously. In this paper, we propose an automatic work control system to solve this problem. The proposed system transmits the data measured by the sensor to the server and identifies non - real - time tasks such as real - time work which is related to the dangerous situations, ventilation and temperature control. In addition, priority among the tasks is set in a way that existing tasks are stopped when high priority tasks occur. Accordingly, this can reduce the unnecessary waste of power, and the user is able to receive a proactive service.

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Debattisti, Nicola, Simone Cinquemani, and Federico Zanelli. "Automatic Decentralized Vibration Control System Based on Collaborative Stand-Alone Smart Dampers." Applied Sciences 13, no. 6 (March 7, 2023): 3406. http://dx.doi.org/10.3390/app13063406.

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In many structures, undesired noise and vibrations generated by external sources represent a huge problem in terms of structural damage and comfort. Active vibration absorbers can be used to dynamically suppress vibrations, by increasing the damping of the system. A wireless smart active damper has been developed to perform this task and some automated functionalities have been implemented to perform the identification of the structure on which it is mounted on. The sharing of information between wireless sensors represents one of the most interesting features of this kind of control system. In this work, a procedure to estimate the nondimensional damping and modal amplitude for each wireless sensor location and each vibration mode is studied. Then, the information obtained by each sensor in the identification phase are used to implement a coordinated control strategy, which is based on a modified version of the Efficient Modal Control (EMC). Such control strategy implements the low level Selective Negative Derivative Feedback control law and modulates the control gains of each actuator and controlled mode pair in order to get an effective vibration reduction. The tuning procedure represents the next step of the algorithm, in which the evaluation of the introduced damping and the maximum applicable gains are derived; finally, the proposed solution is validated with experimental results on a simply-supported beam.

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Duan, Dingbo, Guangyu Gao, Chi Harold Liu, and Jian Ma. "Automatic Person Identification in Camera Video by Motion Correlation." Journal of Sensors 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/838751.

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Person identification plays an important role in semantic analysis of video content. This paper presents a novel method to automatically label persons in video sequence captured from fixed camera. Instead of leveraging traditional face recognition approaches, we deal with the task of person identification by fusing information from motion sensor platforms, like smart phones, carried on human bodies and extracted from camera video. More specifically, a sequence of motion features extracted from camera video are compared with each of those collected from accelerometers of smart phones. When strong correlation is detected, identity information transmitted from the corresponding smart phone is used to identify the phone wearer. To test the feasibility and efficiency of the proposed method, extensive experiments are conducted which achieved impressive performance.

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Biddle, Liam, and Saber Fallah. "A Novel Fault Detection, Identification and Prediction Approach for Autonomous Vehicle Controllers Using SVM." Automotive Innovation 4, no. 3 (April 5, 2021): 301–14. http://dx.doi.org/10.1007/s42154-021-00138-0.

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AbstractFaults that develop in vehicle sensors have the potential to propagate unchecked throughout control systems if undetected. Automatic fault diagnosis and health monitoring algorithms will become necessary as automotive applications become more autonomous. The current fault diagnosis systems are not effective for complex systems such as autonomous cars where the case of simultaneous faults in different sensors is highly possible. Therefore, this paper proposes a novel fault detection, isolation and identification architecture for multi-fault in multi-sensor systems with an efficient computational burden for real-time implementation. Support Vector Machine techniques are used to detect and identify faults in sensors for autonomous vehicle control systems. In addition, to identify degrading performance in a sensor and predict the time at which a fault will occur, a novel predictive algorithm is proposed. The effectiveness and accuracy of the architecture in detecting and identifying multiple faults as well as the accuracy of the proposed predictive fault detection algorithm are verified through a MATLAB/IPG CarMaker co-simulation platform. The results present detection and identification accuracies of 94.94% and 97.01%, respectively, as well as a prediction accuracy of 75.35%.

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Kamble, Divya Balaso. "Review Paper on Microcontroller Based Object Sorting." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 31, 2021): 3287–88. http://dx.doi.org/10.22214/ijraset.2021.36872.

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Sorting of products is a very difficult industrial process. Continuous manual sorting creates consistency issues. This paper describes a working prototype designed for automatic sorting of objects based on the metal detector KY-036 sensor was used to detect the colour of the product and the PIC16F628A microcontroller was used to control the overall process. The identification of the colour is based on the frequency analysis of the output of TCS230 sensor. One conveyor belts were used, it controlled by separate DC motors. The belt is for placing the product to be analysed by the colour sensor, having separated compartments, in order to separate the products. The experimental results promise that the prototype will fulfil the needs for higher production and precise quality in the field of automation.

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Kelemen, Michal. "EXPERIMENTAL IDENTIFICATION OF SENSITIVITY OF TILT SENSOR." TECHNICAL SCIENCES AND TECHNOLOGIES, no. 4(18) (2019): 114–20. http://dx.doi.org/10.25140/2411-5363-2019-4(18)-114-120.

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Urgency of the research. Robots and vehicles which locomote on high slope ground has tendency to overturning and they lost stability during the locomotion. The problem also occurs in area of automotive industry. Target setting. All vehicles moving on the rough and inclined ground has a problem with stability. Emergency system for warning before dangerous tilt angle can be mounted inside the vehicles and robots as prevention of side overturning. Actual scientific researches and issues analysis. The problem is to find the reliable sensor for detection of dangerous tilt angle. Task is to identify the sensor properties as sensitivity, zero shift and also uncertainty of measurement. Before using it is necessary to identify sensor properties. Uninvestigated parts of general matters defining. The questions of the filtering of data acquisition by tilt angle sensor are uninvestigated, because the next research will be focused to this topic. The research objective. Sine bar is used for verification and testing of tilt sensor. Sine bar angle is adjusted using the parallel length gauge blocks. Sensor reacts to the changed tilt angle proportionally with pulse width on output pulse width signal. Indication of sensed data is made via using the microcontroller and LCD display. Also all calculations are executed inside the microcontroller. The statement of basic materials. The tilt sensor can be mounted inside the problematic vehicles to detect dangerous tilt angle and also automatic system for change the center of gravity position can be designed. The system will compensate the dangerous tilt angle. Conclusions. Evaluated uncertainties are related to overall sensing system and not only for sensor. Only sensor alone cannot be tested, because the sensor has no indication module. Expanded uncertainty of the system for measurement of tilt has been obtained and it is value should be taken into account before the sensor using.

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Baniasad, M., R. Martin, X. Crevoisier, C. Pichonnaz, F. Becce, and K. Aminian. "Automatic identification of the IMU sensor location on body segment during gait." Gait & Posture 97 (September 2022): S345—S346. http://dx.doi.org/10.1016/j.gaitpost.2022.07.205.

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TERADA, Kenji, Jun'ichi YAMAGUCHI, and Masato NAKAJIMA. "An Automatic System for Identification of Human Faces Using 3-D Sensor." Transactions of the Society of Instrument and Control Engineers 32, no. 1 (1996): 122–29. http://dx.doi.org/10.9746/sicetr1965.32.122.

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Weenk, Dirk, Bert-Jan F. van Beijnum, Chris TM Baten, Hermie J. Hermens, and Peter H. Veltink. "Automatic identification of inertial sensor placement on human body segments during walking." Journal of NeuroEngineering and Rehabilitation 10, no. 1 (2013): 31. http://dx.doi.org/10.1186/1743-0003-10-31.

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Venugopal, Chitra, and Bhuvaneswari Thangavel. "Automatic Vehicle Fueling System using PLC Controlled Robotic Arm." F1000Research 11 (September 6, 2022): 1006. http://dx.doi.org/10.12688/f1000research.73674.1.

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The objective of this research is to design and develop a robotic arm for an automatic fuelling system using a PLC LogixPro simulation. The system includes the “FASS” concept, which is Fast, Accurate, Safe and Simple, to allow car users to have an efficient fuel filling system. The design concept consists of three processes – identification of the vehicle, payment, and filling with the fuel. The first process identifies the presence of the car by the in-floor weight sensors. The weight sensor identifies the car, locks it in position, and activates the payment system. The second process activates the payment system. After payment is completed, the fuel cap will be opened to enable the system to start filling the fuel. If the payment doesn’t go through the car will be released, manual operation will be initialized, and the entire system will be reset. A timer is included in the payment section to process the payment. In the third process, the filling arm is extended to the car, the fuel cap is opened, the fuel pump is inserted into the tank, and fuel is directed into the tank. Once the tank is full, filling is stopped, the pump is ejected, the fuel cap is closed, and the arm returned back to its position. Thus, an automatic vehicle fuelling system is created to overcome the problems of poor safety and longer waiting time during peak hours. The fuel cap is activated and deactivated by pressure and the sensor filler is stopped by a level sensor. The pump insert is activated and deactivated by a photosensor.

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Zheng, Gang Feng, Jia Wei Zha, Hai Zeng Liu, and Ling Li. "Research on a Coal Gangue Identification Device." Applied Mechanics and Materials 325-326 (June 2013): 699–702. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.699.

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The paper designed a coal gangue identification device. It firstly proposed to use the guide groove to guide, grayscale sensor to recognize and the corresponding mechanical actuators to realize automatic separation of coal and waste rocks. Compared with other separation device, it firstly put forward solutions to realize the linear arrangement of materials, and solve the problem of removing the soft sundry after hand sorting. It has advantages of simple structure, reliable operation and so on.

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Yadav, Shivani. "Automatic Rain Sensing Wiper using Arduino." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 5434–38. http://dx.doi.org/10.22214/ijraset.2021.36065.

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Now a days the technology will enhanced to focusing on autonomous vehicle on different implementation. In all likelihood major of accidents occur due to the disturbance of driver. Sometime many cases the deficiency of proper vision accountable for road accident during heavy rain falls. The usual wiper system requires driver’s attention to switch on the wiper system during rainfall. Whereas in traffic condition, driver should not be unfocused by manual adjustment of switching the wiper system which may lead to accident. In this framework we proposed a weather recognized method to construction an automatic rain sensing wiper on the wind screen during rain so as to avoid frenzy of driver. In this project we used Arduino along with a rain sensor, an LCD 16x2 module, and a servo motor. the rainfalls is measured via water rain sensor is present in automatic wiper system to collect information via sensor the wiper will start rotating then dispatch to Arduino. our method exhibited good identification ability of raindrops and encouraging results for rainfall discernment . In order to keep away from condemning situation this automatic wiper system provides changeable wiping speed formed on precipitation intensity. The state of the art in this paper was not only money-making but also highly dispatch and more accurate and economically inexpensive which can be implemented in all low and middle intensity vehicles.

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Kim, Kwang-Il, and Keon Lee. "Deep Learning-Based Caution Area Traffic Prediction with Automatic Identification System Sensor Data." Sensors 18, no. 9 (September 19, 2018): 3172. http://dx.doi.org/10.3390/s18093172.

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In a crowded harbor water area, it is a major concern to control ship traffic for assuring safety and maximizing the efficiency of port operations. Vessel Traffic Service (VTS) operators pay much attention to caution areas like ship route intersections or traffic congestion area in which there are some risks of ship collision. They want to control the traffic of the caution area at a proper level to lessen risk. Inertial ship movement makes swift changes in direction and speed difficult. It is hence important to predict future traffic of the caution area earlier on so as to get enough time for control actions on ship movements. In the harbor area, VTS stations collect a large volume of Automatic Identification Service (AIS) sensor data, which contain information about ship movement and ship attributes. This paper proposes a new deep neural network model called Ship Traffic Extraction Network (STENet) to predict the medium-term traffic and long-term traffic of the caution area. The STENet model is trained with AIS sensor data. The STENet model is organized into a hierarchical architecture in which the outputs of the movement and contextual feature extraction modules are concatenated and fed into a prediction module. The movement module extracts the features of overall ship movements with a convolutional neural network. The contextual modules consist of five separated fully-connected neural networks, each of which receives an associated attribute. The separation of feature extraction modules at the front phase helps extract the effective features by preventing unrelated attributes from crosstalking. To evaluate the performance of the proposed model, the developed model is applied to a real AIS sensor dataset, which has been collected over two years at a Korean port called Yeosu. In the experiments, four methods have been compared including two new methods: STENet and VGGNet-based models. For the real AIS sensor dataset, the proposed model has shown 50.65% relative performance improvement on average for the medium-term predictions and 57.65% improvement on average for the long-term predictions over the benchmark method, i.e., the SVR-based method.

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Chen, Yin-Lin, Wen-Jyi Hwang, Tsung-Ming Tai, and Po-Sheng Cheng. "Sensor-Based Hand Gesture Detection and Recognition by Key Intervals." Applied Sciences 12, no. 15 (July 23, 2022): 7410. http://dx.doi.org/10.3390/app12157410.

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This study aims to present a novel neural network architecture for sensor-based gesture detection and recognition. The algorithm is able to detect and classify accurately a sequence of hand gestures from the sensory data produced by accelerometers and gyroscopes. Each hand gesture in the sequence is regarded as an object with a pair of key intervals. The detection and classification of each gesture are equivalent to the identification and matching of the corresponding key intervals. A simple automatic labelling is proposed for the identification of key intervals without manual inspection of sensory data. This could facilitate the collection and annotation of training data. To attain superior generalization and regularization, a multitask learning algorithm for the simultaneous training for gesture detection and classification is proposed. A prototype system based on smart phones for remote control of home appliances was implemented for the performance evaluation. Experimental results reveal that the proposed algorithm provides an effective alternative for applications where accurate detection and classification of hand gestures by simple networks are desired.

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Aarthi Mai A S and Rajeswari N. "IoT BASED AUTOMATIC STREET LIGHT CONTROL AND FAULT DETECTION." international journal of engineering technology and management sciences 6, no. 5 (September 28, 2022): 858–63. http://dx.doi.org/10.46647/ijetms.2022.v06i05.133.

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The IoT (Internet of Things) is a booming technology that mainly concentrates on the interconnection of devices or components to one another and the people. As the time being, many of these connections are changing as Device to Device from Human to Device. Finding the faulty street light automatically is become a vital milestone by using this technology. The primary goal of the paper is to provide control and identification of the damaged street light automatically. Street light fault detector system informs to the concerned area electricity board substation when the street light is not functioning. Because of no proper street light, most of the thefts and accidents are happening. To avoid that sensors can be included in the light pole which sends the signal to the substation if the light is not functioning properly. Sensor sends the information like Area, Street, and Pole ID Number to the electricity substation. Lineman can easily identify the location from the substation and necessary measures can be taken immediately. Sensors added to identify whether the problem is with the solar light panel/ bulb or any difficulty in electricity distribution system. This approach helps for the lineman to work and fix it.

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Terada, Kenji, Junichi Yamaguchi, and Masato Nakajima. "An Automatic System for Identification of Human Faces Using Fiber Grating Vision Sensor." Journal of Robotics and Mechatronics 5, no. 2 (April 20, 1993): 106–11. http://dx.doi.org/10.20965/jrm.1993.p0106.

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In this paper, the authors describe an automatic system for the identification of human faces. In this system, the fiber grating vision sensor which has been developed by the authors is employed for the 3-D shape of the faces. To identify human faces, a multi-layered neural network is used in which the inputs are two component values of normal vector at data spot on the surface of human faces. The experiments using the developed system is performed to demonstrate the efficacy of this system and the experimental results are shown.

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Wu, Jianqing, Hao Xu, Yuan Tian, Yongsheng Zhang, Junxuan Zhao, and Bin Lv. "An automatic lane identification method for the roadside light detection and ranging sensor." Journal of Intelligent Transportation Systems 24, no. 5 (January 29, 2020): 467–79. http://dx.doi.org/10.1080/15472450.2020.1718500.

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Hsieh, Chia-Yeh, Hsiang-Yun Huang, Kai-Chun Liu, Chien-Pin Liu, Chia-Tai Chan, and Steen Jun-Ping Hsu. "Multiphase Identification Algorithm for Fall Recording Systems Using a Single Wearable Inertial Sensor." Sensors 21, no. 9 (May 10, 2021): 3302. http://dx.doi.org/10.3390/s21093302.

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Fall-related information can help clinical professionals make diagnoses and plan fall prevention strategies. The information includes various characteristics of different fall phases, such as falling time and landing responses. To provide the information of different phases, this pilot study proposes an automatic multiphase identification algorithm for phase-aware fall recording systems. Seven young adults are recruited to perform the fall experiment. One inertial sensor is worn on the waist to collect the data of body movement, and a total of 525 trials are collected. The proposed multiphase identification algorithm combines machine learning techniques and fragment modification algorithm to identify pre-fall, free-fall, impact, resting and recovery phases in a fall process. Five machine learning techniques, including support vector machine, k-nearest neighbor (kNN), naïve Bayesian, decision tree and adaptive boosting, are applied to identify five phases. Fragment modification algorithm uses the rules to detect the fragment whose results are different from the neighbors. The proposed multiphase identification algorithm using the kNN technique achieves the best performance in 82.17% sensitivity, 85.74% precision, 73.51% Jaccard coefficient, and 90.28% accuracy. The results show that the proposed algorithm has the potential to provide automatic fine-grained fall information for clinical measurement and assessment.

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Wu, Jianqing, Hao Xu, Bin Lv, Rui Yue, and Yang Li. "Automatic Ground Points Identification Method for Roadside LiDAR Data." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 6 (May 8, 2019): 140–52. http://dx.doi.org/10.1177/0361198119843869.

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Roadside light detection and ranging (LiDAR) provides a solution to fill the data gap under mixed traffic situations. The real-time high-resolution micro traffic data (HRMTD) of all road users from the roadside LiDAR sensor provides a new opportunity to serve the connected-vehicle system during the transition period from unconnected vehicles to connected vehicles. Ground surface identification is the basic data processing step for HRMTD collection. The current ground points identification algorithms based on airborne and mobile LiDAR do not work for roadside LiDAR. A novel algorithm is developed in this paper to identify and exclude ground points based on the features of LiDAR, terrain, and point density in the space. The scan feature of different beams is used to search ground points. The whole procedure can be divided into four major parts: points clustering in each beam, slope-based filtering, shape-based filtering, and ground points matrix extraction. The proposed algorithm was evaluated using the real-world LiDAR data collected at different scenarios. The results showed that this algorithm can be used for ground points exclusion under different situations (differing terrain types, weather situations, and traffic volumes) with high accuracy. This algorithm was compared with previously developed algorithms. The overall performance of the proposed algorithm is superior. The low computational load guarantees this method may be applied for real-time data processing.

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Kowalska-Styczeń, Agnieszka, Roman Peleshchak, Vasyl Lytvyn, Ivan Peleshchak, Andrii Dyriv, and Vitalii Danylyk. "Automatic Identification of Sound Source Position Coordinates Using a Sound Metric System of Sensors Linked with an Internet Connection." Symmetry 14, no. 11 (November 7, 2022): 2338. http://dx.doi.org/10.3390/sym14112338.

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In this article, we deal with the problem of increasing the accuracy of the automatic determination of the coordinates of the sound source location. We propose a new algorithm for the identification of the sound source’s position coordinates based on a system of three equations of the second order describing the dynamics of acoustic wavefront propagation. The implementation of the algorithm is carried out by a distributed automated system, which includes autonomous sensor-receivers located in the field and connected to the server of this system via wireless communication channels. Sensor-receivers are placed at the vertices of a flat, symmetrical figure with 4 axes of symmetry of the second order (square). The proposed algorithm takes into account the change in the phase speed of the sound wave when the temperature, air humidity, wind direction and speed change and allows for the determination of the coordinates of the position of the sound source with an error of no more than 1%. The experiment with real input data was carried out in a simulated environment, which was created on the Node.js platform.

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Giurgiutiu, Victor, and Andrei N. Zagrai. "Characterization of Piezoelectric Wafer Active Sensors." Journal of Intelligent Material Systems and Structures 11, no. 12 (December 2000): 959–76. http://dx.doi.org/10.1106/a1hu-23jd-m5au-engw.

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In the beginning, the classical one-dimensional analysis of piezoelectric active sensors is reviewed. The complete derivation for a free-free sensor is then extended to cover the cases of clamped and elastically constrained sensors. An analytical model based on structural vibration theory and theory of piezoelectricity was developed and used to predict the electromechanical (E/M) impedance response, as it would be measured at the piezoelectric active sensor’s terminals. The model considers one-dimensional structures and accounts for both axial and flexural vibrations. The numerical analysis was performed and supported by experimental results. Experiments were conducted on simple beam specimens to support the theoretical investigation, and on thin gauge aluminum plates to illustrate the method’s potential. It was shown that E/M impedance spectrum recorded by the piezoelectric active sensor accurately represents the mechanical response of a structure. It was further proved that the response of the structure is not modified by the presence of the sensor, thus validating the sensor’s non-invasive characteristics. The sensor calibration procedure is outlined and statistical analysis was presented. It was found that PZT active sensors have stable and repeatable characteristics not only in as-received condition, but also while mounted on 1-D or 2-D host structure. It is shown that such sensors, of negligible mass, can be permanently applied to the structure creating a non-intrusive sensor array adequate for on-line automatic structural identification and health monitoring.

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Sun, Rong Xia, Lei Gao, Jian Kang, Pan Pan Huang, Yi Tian, and Xiao Feng Chen. "Automatic On-Line Detection and Sorting System Design and Implementation for Paper-Making Printing." Advanced Materials Research 383-390 (November 2011): 3–5. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.3.

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Transforms the papermaking production line to spurt the code automatic detection separation system is the production of impending rapid requirement. This design using the original paper cutter to cut the paper separating function is bad, choose the trigger for separating door action by photoelectric sensor signal, triggering bad signal detection equipments, and complete code identification papers in the test paper separating bad logo. In printing, the PLC control high-speed counter acquisition traction, printing roll encoder pulse signal range. This system includes color standard sensor signal detection, Siemens S7-200 PLC controller, etc. Also gives the system installation problems and presents the corresponding countermeasures. The paper realize online automatic testing equipments, satisfying the function of separation, stable, zero leakage rate of selected control of the production requirement.

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Alharbe, Nawaf, and Anthony S. Atkins. "A study of the application of automatic healthcare tracking and monitoring system in Saudi Arabia." International Journal of Pervasive Computing and Communications 10, no. 2 (May 27, 2014): 183–95. http://dx.doi.org/10.1108/ijpcc-03-2014-0026.

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Purpose – This paper aims to outline the results of a study of the potential use of sensor technology such as radio frequency identification (RFID) and/or ZigBee technology in providing real-time tracking and tracing of patients and equipment in hospitals. The government of Saudi Arabia has given high priority to providing the best practice in patients’ care. However, the growing requirement of the healthcare industry to obtain real-time information and data from various applications that can improve the performance and accuracy of management systems has not been addressed seriously in Saudi Arabia. Design/methodology/approach – ZigBee and RFID are both emerging technologies and have become important topics in recent years. RFID technology is a non-contact identification technology that does not require direct eyesight to the target object. It is cheap and reliable, but its coverage zone is limited. ZigBee is another communication technology, which has a larger coverage and can also be used as an automatic identification technology with the benefits of lower power consumption. Findings – This paper proposes a smart hospital management system that can be used to detect, locate and monitor patients and track assets and equipment using modern sensor technologies in a real-time environment for e-health systems in Saudi Arabia. Originality/value – A novel management information system/knowledge management system framework based on sensor technologies for supporting and speeding up development of healthcare systems.

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Wu, Jianqing, Hao Xu, Yuan Sun, Jianying Zheng, and Rui Yue. "Automatic Background Filtering Method for Roadside LiDAR Data." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 45 (June 17, 2018): 106–14. http://dx.doi.org/10.1177/0361198118775841.

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The high-resolution micro traffic data (HRMTD) of all roadway users is important for serving the connected-vehicle system in mixed traffic situations. The roadside LiDAR sensor gives a solution to providing HRMTD from real-time 3D point clouds of its scanned objects. Background filtering is the preprocessing step to obtain the HRMTD of different roadway users from roadside LiDAR data. It can significantly reduce the data processing time and improve the vehicle/pedestrian identification accuracy. An algorithm is proposed in this paper, based on the spatial distribution of laser points, which filters both static and moving background efficiently. Various thresholds of point density are applied in this algorithm to exclude background at different distances from the roadside sensor. The case study shows that the algorithm can filter background LiDAR points in different situations (different road geometries, different traffic demands, day/night time, different speed limits). Vehicle and pedestrian shape can be retained well after background filtering. The low computational load guarantees this method can be applied for real-time data processing such as vehicle monitoring and pedestrian tracking.

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Han, Chan Woo, Sung Wook Lee, and Eun Seok Jin. "Tracking of ARPA Radar Signals Based on UK–PDAF and Fusion with AIS Data." Journal of Ocean Engineering and Technology 37, no. 1 (February 27, 2023): 38–48. http://dx.doi.org/10.26748/ksoe.2022.046.

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To maintain the existing systems of ships and introduce autonomous operation technology, it is necessary to improve situational awareness through the sensor fusion of the automatic identification system (AIS) and automatic radar plotting aid (ARPA), which are installed sensors. This study proposes an algorithm for determining whether AIS and ARPA signals are sent to the same ship in real time. To minimize the number of errors caused by the time series and abnormal phenomena of heterogeneous signals, a tracking method based on the combination of the unscented Kalman filter and probabilistic data association filter is performed on ARPA radar signals, and a position prediction method is applied to AIS signals. Especially, the proposed algorithm determines whether the signal is for the same vessel by comparing motion-related components among data of heterogeneous signals to which the corresponding method is applied. Finally, a measurement test is conducted on a training ship. In this process, the proposed algorithm is validated using the AIS and ARPA signal data received by the voyage data recorder for the same ship. In addition, the proposed algorithm is verified by comparing the test results with those obtained from raw data. Therefore, it is recommended to use a sensor fusion algorithm that considers the characteristics of sensors to improve the situational awareness accuracy of existing ship systems.

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Song, Qiang. "Automated Visual Inspection of Surface Defects on Hot-Rolled Plate." Advanced Materials Research 201-203 (February 2011): 1619–22. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.1619.

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This paper is concerned with the problem of automatic inspection of hot-rolled plate surface using machine vision. An automated visual inspection (AVI) system has been developed to take images of external hot-rolled plate surfaces and the detailed characteristics of the sensor system which include the illumination and digital camera are described. An intelligent surface defect detection paradigm based on morphology is proposed to detect structural defects on plate surfaces. The proposed method has been implemented and tested on a number of hot-rolled plate surfaces. The results suggest that the method can provide an accurate identification to the defects and can be developed into a commercial visual inspection system.

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Quqa, Said, Luca Landi, and Pier Paolo Diotallevi. "Automatic identification of dense damage-sensitive features in civil infrastructure using sparse sensor networks." Automation in Construction 128 (August 2021): 103740. http://dx.doi.org/10.1016/j.autcon.2021.103740.

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Rantelino, Alan Prasetyo, R. Rizal Isnanto, and Eko Didik Widianto. "Sistem Pembukaan Kunci Otomatis Menggunakan Identifikasi Pola Ketukan." Jurnal Teknologi dan Sistem Komputer 2, no. 4 (November 3, 2014): 281. http://dx.doi.org/10.14710/jtsiskom.2.4.2014.281-287.

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During this time automatic unlocking still use the physical tools as the authentication method, which potentially damaged or lost. Authentication method of automatic unlocking system does not use technology which allows unique information to be stored without the need for physical tools and where everyone can use it. Therefore, research needs to be done to develop an automatic unlocking system using knocking pattern identification as the authentication method. System consists of hardware and software. Hardware consist of sensor which are buzzer, ATTiny85 as microcontroller and solenoid lock as actuator. Software is coded using C language with Arduino IDE which is compatible with AVR microcontroler. The system can read the knocking pattern from buzzer then identify it as true or false knock. From the test results, system can identify knocking pattern based on number of knocks, time beetween knocks and soft or loud of knocks. The system identifies the knocking patterns by analyzing its pattern compared with the true knock saved in system memory. Knocking pattern identification can be an alternative of authentication system for automatic unlocking system.

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Tong, Lukai. "A Intelligent Campus Based on the Internet of Things------Campus Intelligent Drainage System." Urban Transportation & Construction 6, no. 4 (January 29, 2021): 66. http://dx.doi.org/10.18686/utc.v6i4.97.

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Nowadays, the Internet of Things is being used in various fields. Drainage is placed at the top of the priority in campus life. However, the current campus drainage system cannot meet people’s yearning for a better life, so the system needs to be optimized. The optimized drainage system is divided into four parts. Sensor part, communication part, cloud control part, water storage/drainage part, identification part. RFID and AI technology are used for identification, temperature, humidity and pressure sensors are used for perception, cloud computing technology is used for cloud control, WIFI technology is used for communication and water storage and drainage control has three modes: remote control, automatic closed-loop control and manual control. Drainage network with circular pipe network drainage system, to achieve intelligent, accurate goals.

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Balestra, Noah, Gaurav Sharma, Linda M. Riek, and Ania Busza. "Automatic Identification of Upper Extremity Rehabilitation Exercise Type and Dose Using Body-Worn Sensors and Machine Learning: A Pilot Study." Digital Biomarkers 5, no. 2 (July 2, 2021): 158–66. http://dx.doi.org/10.1159/000516619.

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Background: Prior studies suggest that participation in rehabilitation exercises improves motor function poststroke; however, studies on optimal exercise dose and timing have been limited by the technical challenge of quantifying exercise activities over multiple days. Objectives: The objectives of this study were to assess the feasibility of using body-worn sensors to track rehabilitation exercises in the inpatient setting and investigate which recording parameters and data analysis strategies are sufficient for accurately identifying and counting exercise repetitions. Methods: MC10 BioStampRC® sensors were used to measure accelerometer and gyroscope data from upper extremities of healthy controls (n = 13) and individuals with upper extremity weakness due to recent stroke (n = 13) while the subjects performed 3 preselected arm exercises. Sensor data were then labeled by exercise type and this labeled data set was used to train a machine learning classification algorithm for identifying exercise type. The machine learning algorithm and a peak-finding algorithm were used to count exercise repetitions in non-labeled data sets. Results: We achieved a repetition counting accuracy of 95.6% overall, and 95.0% in patients with upper extremity weakness due to stroke when using both accelerometer and gyroscope data. Accuracy was decreased when using fewer sensors or using accelerometer data alone. Conclusions: Our exploratory study suggests that body-worn sensor systems are technically feasible, well tolerated in subjects with recent stroke, and may ultimately be useful for developing a system to measure total exercise “dose” in poststroke patients during clinical rehabilitation or clinical trials.

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Wang, Qiang, and Josh Davis. "Airport Pavement Groove Identification and Analysis at NAPTF." Advanced Materials Research 723 (August 2013): 1003–10. http://dx.doi.org/10.4028/www.scientific.net/amr.723.1003.

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Transverse grooves in an airport pavement allow water to be ejected from beneath the tires of an aircraft moving at high speed. It has been found that the grooves can efficiently reduce the hydroplaning potential of a pavement during wet weather. The Federal Aviation Administration (FAA) maintains a standard specification for groove configuration immediately after construction and during service. The National Airport Pavement Test Facility (NAPTF) performed a long period of real scale tests to investigate the performance of the current FAA standard square grooves and proposed trapezoidal grooves. This paper includes the comparison of trapezoidal and rectangular grooves under aircraft tire loading with service life. These two groove patterns were constructed on the flexible and rigid pavement respectively. In the automatic device measurement, a laser sensor from a truss profiler constantly detected the distance between the grooved surface and an initial standard line as the aircraft tires repeatedly passed through the grooved areas. An automatic groove identification program was also developed to evaluate the groove configurations. Our test results demonstrate that the trapezoidal grooves maintain a longer life shape configuration than rectangular grooves, especially for asphalt pavements.

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Beck, Moritz, Georg Maier, Merle Flitter, Robin Gruna, Thomas Längle, Michael Heizmann, and Jürgen Beyerer. "An Extended Modular Processing Pipeline for Event-Based Vision in Automatic Visual Inspection." Sensors 21, no. 18 (September 13, 2021): 6143. http://dx.doi.org/10.3390/s21186143.

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Dynamic Vision Sensors differ from conventional cameras in that only intensity changes of individual pixels are perceived and transmitted as an asynchronous stream instead of an entire frame. The technology promises, among other things, high temporal resolution and low latencies and data rates. While such sensors currently enjoy much scientific attention, there are only little publications on practical applications. One field of application that has hardly been considered so far, yet potentially fits well with the sensor principle due to its special properties, is automatic visual inspection. In this paper, we evaluate current state-of-the-art processing algorithms in this new application domain. We further propose an algorithmic approach for the identification of ideal time windows within an event stream for object classification. For the evaluation of our method, we acquire two novel datasets that contain typical visual inspection scenarios, i.e., the inspection of objects on a conveyor belt and during free fall. The success of our algorithmic extension for data processing is demonstrated on the basis of these new datasets by showing that classification accuracy of current algorithms is highly increased. By making our new datasets publicly available, we intend to stimulate further research on application of Dynamic Vision Sensors in machine vision applications.

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Choi, Jeonghun, and Seung Jun Lee. "A Sensor Fault-Tolerant Accident Diagnosis System." Sensors 20, no. 20 (October 15, 2020): 5839. http://dx.doi.org/10.3390/s20205839.

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Emergency situations in nuclear power plants are accompanied by an automatic reactor shutdown, which gives a big task burden to the plant operators under highly stressful conditions. Diagnosis of the occurred accident is an essential sequence for optimum mitigations; however, it is also a critical source of error because the results of accident identification determine the task flow connected to all subsequent tasks. To support accident identification in nuclear power plants, recurrent neural network (RNN)-based approaches have recently shown outstanding performances. Despite the achievements though, the robustness of RNN models is not promising because wrong inputs have been shown to degrade the performance of RNNs to a greater extent than other methods in some applications. In this research, an accident diagnosis system that is tolerant to sensor faults is developed based on an existing RNN model and tested with anticipated sensor errors. To find the optimum strategy to mitigate sensor error, Missforest, selected from among various imputation methods, and gated recurrent unit with decay (GRUD), developed for multivariate time series imputation based on the RNN model, are compared to examine the extent that they recover the diagnosis accuracies within a given threshold.

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Prabowo, Y. A., R. I. Imaduddin, W. S. Pambudi, R. A. Firmansyah, and A. Fahruzi. "Identification of automatic guided vehicle (agv) based on magnetic guided sensor for industrial material transfer." IOP Conference Series: Materials Science and Engineering 1010 (January 16, 2021): 012028. http://dx.doi.org/10.1088/1757-899x/1010/1/012028.

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Journal articles on the topic 'Automatic identification sensor'

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