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Journal articles on the topic 'Sensor-based IT system'

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Published: 4 June 2021
Last updated: 6 February 2022

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1

D, Charansai. "Sensor based Human Assistance System." International Journal of Psychosocial Rehabilitation 24, no. 5 (May 25, 2020): 7087–92. http://dx.doi.org/10.37200/ijpr/v24i5/pr2020717.

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2

Aye Maung Maung, Nyein, and Makoto Kawai. "Wireless Sensor Network Based Mobile Tracking System." International Journal of Computer and Communication Engineering 5, no. 1 (2016): 31–40. http://dx.doi.org/10.17706/ijcce.2016.5.1.31-40.

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3

Pragnya, K. Ranjitha, and J. Krishna Chaitanya. "Wireless Sensor Network based Healthcare Monitoring System for Homely Elders." International Journal of Advances in Engineering & Technology 6, no. 5 (November 1, 2013): 2078–83. http://dx.doi.org/10.7323/ijaet/v6_iss5_14.

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4

S ,, Madhusudhan, Channakeshava K.R ,, and Dr T. Rangaswamy. "Content-Based Image Retrieval System for Optical Fiber Sensor Information Processing." International Journal of Engineering Research 3, no. 6 (June 1, 2014): 398–401. http://dx.doi.org/10.17950/ijer/v3s6/607.

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5

., Mali S. P., Jadhav Priyanka H. ., Mane Shalaka K. ., and Ghodake Shital T. . "SENSOR BASED ACCIDENT MAPPING SYSTEM." International Journal of Engineering Applied Sciences and Technology 3, no. 10 (February 28, 2019): 44–46. http://dx.doi.org/10.33564/ijeast.2019.v03i10.009.

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6

Nithya, M., N. Pooranam, R. Deepalakshmi, M. Aruna Rani, and S. Anandha Swarna. "Sensor Based Accident Prevention System." Journal of Computational and Theoretical Nanoscience 17, no. 4 (April 1, 2020): 1720–24. http://dx.doi.org/10.1166/jctn.2020.8431.

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In the developing countries accident is the major cause of death. The top 10 dangerous roads in the world are mountain roads and curve roads. In the mountain roads there will be tight curves and the roads will be narrow. In these kinds of situations the driver of a vehicle cannot see vehicles coming from opposite side. Thousands of people lose their lives each year because of this problem. The mountain roads might lead to a cliff. The solution for this problem is alerting the driver about the vehicle coming from opposite side in the hair-pin bends. That can be performed by placing the ultrasonic sensor on the road in one side before the road curve and then will keep the LED light after that curve, thus the vehicle which comes from the one end of the curve, the sensors which is present in that curve will sense and makes the LED light glows along with that buzzer sound and also vehicle speed is displayed at the opposite side. By looking at the LED light on signal driver can become alert and can slow down the speed of the vehicle. Thus it saves more lives.
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Fan, Bingfei, Tao Liu, Qingguo Li, and Yoshio Inoue. "Quantitative Analysis of Human Daily Activities Based on a Wireless Sensor System." Abstracts of the international conference on advanced mechatronics : toward evolutionary fusion of IT and mechatronics : ICAM 2015.6 (2015): 357–58. http://dx.doi.org/10.1299/jsmeicam.2015.6.357.

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8

Kim, Hansoo. "VRSMS: VR-based Sensor Management System." Journal of the HCI Society of Korea 3, no. 2 (November 30, 2008): 1. http://dx.doi.org/10.17210/jhsk.2008.11.3.2.1.

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9

AJAYI, Olusola Olajide, Taiwo Gabriel OMOMULE, and Sekinat Bolanle ADEKILE. "Sensor-based mobile pigeonhole alert system." International Journal of Biosensors & Bioelectronics 6, no. 1 (January 31, 2020): 4–12. http://dx.doi.org/10.15406/ijbsbe.2020.06.00180.

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10

Zhang, Dengpan, and H. L. Zhu. "Sensor Array Based Distributed Instrument System." International Journal of Online Engineering (iJOE) 10, no. 3 (April 28, 2014): 31. http://dx.doi.org/10.3991/ijoe.v10i3.3546.

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11

Khan, Mohammad Monirujjaman. "Sensor-Based Gas Leakage Detector System." Engineering Proceedings 2, no. 1 (November 14, 2020): 28. http://dx.doi.org/10.3390/ecsa-7-08278.

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Liquefied Petroleum Gas (LPG) is a main source of fuel, especially in urban areas because it is clean compared to firewood and charcoal. Gas leakage is a major problem in the industrial sector, residential premises, etc. Nowadays, home security has become a major issue because of increasing gas leakage. Gas leakage is a source of great anxiety with ateliers, residential areas and vehicles like Compressed Natural Gas (CNG), buses, and cars which are run on gaspower. One of the preventive methods to stop accidents associated with the gas leakage is to install a gas leakage detection kit at vulnerable places. The aim of this paper is to propose and discuss a design of a gas leakage detection system that can automatically detect, alert and control gas leakage. This proposed system also includes an alerting system for the users. The system is based on a sensor that easily detects a gas leakage.
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12

Lee, Sooyong. "Gradient based Stereo Temperature Sensor System." Journal of Korea Robotics Society 14, no. 4 (November 30, 2019): 258–63. http://dx.doi.org/10.7746/jkros.2019.14.4.258.

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13

Nagai, Masahiko, Apichon Witayangkurn, Kiyoshi Honda, and Ryosuke Shibasaki. "UAV-Based Sensor Web Monitoring System." International Journal of Navigation and Observation 2012 (March 7, 2012): 1–7. http://dx.doi.org/10.1155/2012/858792.

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An unmanned aerial vehicle- (UAV-) based monitoring system is developed as an intermediate system between aerial survey and ground survey. All the measurement tools are mounted on the UAV to acquire detailed information from low altitudes which is different from a satellite or a plane. The monitoring is carried out from the sky, but the spatial and temporal resolutions are freely selected near the ground. In this study, the data is easily acquired with safety and mobility by the utilization of a sensor web. A sensor web is a type of sensor network which is well suited for environmental monitoring. Sensor nodes are spatially distributed and wirelessly communicate with each other. In this study, the UAV-based system is considered as a mobile sensor node. This study proposes a combination of UAV-based monitoring with a ubiquitous sensor network.
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14

Tzafestas, S. G. "Integrated sensor-based intelligent robot system." IEEE Control Systems Magazine 8, no. 2 (April 1988): 61–72. http://dx.doi.org/10.1109/37.1876.

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15

AJAYI, Olusola Olajide, Taiwo Gabriel OMOMULE, and Sekinat Bolanle ADEKILE. "Sensor-based mobile pigeonhole alert system." International Journal of Biosensors & Bioelectronics 6, no. 1 (January 31, 2020): 4–12. http://dx.doi.org/10.15406/ijbsbe.2020.06.00180.

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16

Srijith, Biyyala. "Arduino based Distance Measurement Sensor using Ultrasonic Sensor." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 20, 2021): 1789–99. http://dx.doi.org/10.22214/ijraset.2021.35346.

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The project we designed is used to develop a distance measurement system using ultrasonic waves and interfaced with Arduino UNO. We know that the human audible range is from 20hz to 20khz. We can use these frequency range waves through ultrasonic sensor HC-SR04. The main advantages of this sensor are when this sensor is interfaced with Arduino which is a control system and a sensing system, a proper calculation of the distance measurement can be done by using different types of new techniques. As huge amounts are spent on hundreds of inflexible circuit boards, the Arduino board will allow the business to bring many more unique devices. These distance measurement systems are mostly used as range meters and as proximity detectors in the different types of industries. The hardware part of the ultrasonic sensor is interfaced with the Arduino Uno board. This type of measuring distance is an efficient way to measure even small distances accurately. The distance of an object from the sensor is measured by using an ultrasonic sensor. After knowing the speed of the sound wave the distance of an object can be calculated.
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17

A, Ravishankar, and Pandian R. "Embedded System Based Sensor Failiure Detection and Industrial Environment Controll Over Wireless Network." International Journal of Engineering Research 3, no. 12 (December 1, 2014): 716–19. http://dx.doi.org/10.17950/ijer/v3s12/1202.

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18

Bovhyra, R. V., V. M. Zhyrovetskyy, D. I. Popovych, S. S. Savka, and A. S. Serednytskij. "Development and Creation of Gas-Sensor System Based on Low Dimensional Metal Oxides." Science and innovation 12, no. 6 (November 30, 2016): 57–62. http://dx.doi.org/10.15407/scine12.06.057.

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19

Wang, Dejun, and Shiyao Song. "Robust Model-Based Sensor Fault Monitoring System for Nonlinear Systems in Sensor Networks." Sensors 14, no. 10 (October 15, 2014): 19138–61. http://dx.doi.org/10.3390/s141019138.

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20

Shiraishi, N., M. Kimura, H. Okada, and Y. Ando. "Polymer-based VOC Sensor Module for Wireless Sensor Network System." Procedia Engineering 87 (2014): 600–603. http://dx.doi.org/10.1016/j.proeng.2014.11.560.

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21

Liu, Ya, Jian Hua Mao, and Xue Feng Liu. "Smart Community Security System Based on Sensor Web." Applied Mechanics and Materials 571-572 (June 2014): 1037–41. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.1037.

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The traditional smart security systems have poor extensity, delayed alarm systems, and cannot be controlled through the remote network. To solve the shortcomings, this article proposed a smart security system based on Sensor Web. The system used Sensor Observation Service to achieve the data transmission and storage in real time. Users can send requests to Sensor Observation Service to get home environment information in real time via Internet. The system also implemented Sensor Event Service, so that users can get home security alarm information in real time by subscribing the events they are interested in.
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22

TSUJITA, Wataru, Kenji KATAOKA, Seiya NAGASHIMA, Kazuhiro TAHARA, Kazunori ARIJI, and Atsushi IWAMOTO. "1B11 DEVELOPMENT OF CONTACTLESS SPEED SENSOR BASED ON THE MICROWAVE RADAR TECHNOLOGY(Vehicles-System)." Proceedings of International Symposium on Seed-up and Service Technology for Railway and Maglev Systems : STECH 2015 (2015): _1B11–1_—_1B11–7_. http://dx.doi.org/10.1299/jsmestech.2015._1b11-1_.

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23

Shimojima, K., T. Fukuda, F. Arai, H. Matsuura, A. Takeishi, and T. Ooka. "Sensor Integration System Based on Fuzzy Inference with Vision System and LED Displacement Sensor." IFAC Proceedings Volumes 26, no. 2 (July 1993): 761–64. http://dx.doi.org/10.1016/s1474-6670(17)48833-1.

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24

Kim, Kwangsoo, Yangho Kim, and Sooyeong Kwak. "Vision Sensor Based Fuzzy System for Intelligent Vehicles." Sensors 19, no. 4 (February 19, 2019): 855. http://dx.doi.org/10.3390/s19040855.

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Those in the automotive industry and many researchers have become interested in the development of pedestrian protection systems in recent years. In particular, vision-based methods for predicting pedestrian intentions are now being actively studied to improve the performance of pedestrian protection systems. In this paper, we propose a vision-based system that can detect pedestrians using an on-dash camera in the car, and can then analyze their movements to determine the probability of collision. Information about pedestrians, including position, distance, movement direction, and magnitude are extracted using computer vision technologies and, using this information, a fuzzy rule-based system makes a judgement on the pedestrian’s risk level. To verify the function of the proposed system, we built several test datasets, collected by ourselves, in high-density regions where vehicles and pedestrians mix closely. The true positive rate of the experimental results was about 86%, which shows the validity of the proposed system.
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25

Sungthan, Soumya. "Multiple Sensor based Smart Women Safety System." International Journal for Research in Applied Science and Engineering Technology 8, no. 7 (July 31, 2020): 714–17. http://dx.doi.org/10.22214/ijraset.2020.30329.

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26

Patel, Shubham. "Design for Sensor based Waste Segregator System." International Journal for Research in Applied Science and Engineering Technology 8, no. 12 (December 31, 2020): 207–14. http://dx.doi.org/10.22214/ijraset.2020.32445.

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27

Kitagaki, Kosei, Takashi Suehiro, Tsukasa Ogasawara, and Yun-Hui Liu. "Sensor Based Parallel Processing Manipulation System: TAKUMI." Journal of the Robotics Society of Japan 15, no. 3 (1997): 363–72. http://dx.doi.org/10.7210/jrsj.15.363.

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28

He, Hong, C. Q. Mao, H. Y. Pan, and Yu Li. "Vehicle Detection System Based on Magnetoresistive Sensor." Applied Mechanics and Materials 743 (March 2015): 277–80. http://dx.doi.org/10.4028/www.scientific.net/amm.743.277.

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According to the vehicle after geomagnetic disturbances cause of this phenomenon, in-depth theoretical study of the anisotropic magnetoresistance AMR sensors, using triaxial anisotropic magnetoresistive sensor HMC5883L design a vehicle detection system. The system consists of a sensor module, wireless communication module. Sensor nodes through wireless communication module connected with the host computer, to achieve the detection of vehicle information.
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29

Xie, Baofeng, Rong Ge, and Qinyou Hu. "Ship Navigation System Based on Wireless Sensor." International Journal of Online Engineering (iJOE) 14, no. 06 (June 22, 2018): 98. http://dx.doi.org/10.3991/ijoe.v14i06.8701.

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<p class="0abstract"><span lang="EN-US">T</span><span lang="EN-US">o study the application of wireless sensor in the ship dynamic positioning system, the distributed fusion function model and structure model of wireless sensor network were set up.</span><span lang="EN-US">Using the DJC model-based SVM prediction algorithm, the quadratic optimal performance index in ship dynamic positioning MPC control was solved</span><span lang="EN-US"> and t</span><span lang="EN-US">he optimal control thrust was obtained.</span><span lang="EN-US">According to the classic cluster routing protocol, a data fusion structure based on residual energy and dormancy scheduling mechanism was proposed. The results showed that the proposed routing protocol based on the residual energy and sleep scheduling mechanism data fusion structure was superior to the Leach protocol. It improved the real-time performance of data transmission. Thus, the network data fusion structure achieves the goal of energy balance. The energy consumption is reduced to a certain extent</span><span lang="EN-US"> and t</span><span lang="EN-US">he design is reasonable.</span></p>
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30

B.T, Associate Prof Salokhe, and Miss Shilpa G. Gadekar. "Wireless Sensor Network Based Irrigation Management System." IJARCCE 4, no. 4 (April 30, 2015): 590–92. http://dx.doi.org/10.17148/ijarcce.2015.44136.

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31

Um, Dae-Jin, Jung-In Choi, and Ingyu Lee. "Development of Sensor Based Energy Management System." Journal of the Korean Institute of Illuminating and Electrical Installation Engineers 28, no. 10 (October 31, 2014): 69–74. http://dx.doi.org/10.5207/jieie.2014.28.10.069.

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32

Uhl, Tadeusz, Artur Hanc, Krzysztof Tworkowski, and Łukasz Sekiewicz. "Wireless Sensor Network Based Bridge Monitoring System." Key Engineering Materials 347 (September 2007): 499–504. http://dx.doi.org/10.4028/www.scientific.net/kem.347.499.

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This paper presented idea and implementation of efficient, reliable wireless bridge monitoring system. The system using Wireless Sensor Network to collect the related environment parameters (vibrations, temperature, humidity) and transmitting data to the main server. The system eliminates stand-alone laboratory benchtop equipment sets and cable-based, hard-wired sensor networking. Modern MEMS technology for vibrations measurement and integrated humidity/temperature sensors application for structural monitoring is presented. Data collected by the wireless monitoring system is compared to data from a traditional wired monitoring system. Both – traditional and wireless collected data that can be used to accurately identify modal frequencies and mode shapes of the bridge. Case study of the system on bridge located over Vistula river in Krakow is shown.
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33

Caputo, D., M. Ceccarelli, G. de Cesare, R. Intrieri, C. Manetti, A. Nascetti, and R. Scipinotti. "Chromatography system based on amorphous silicon sensor." Journal of Non-Crystalline Solids 354, no. 19-25 (May 2008): 2615–18. http://dx.doi.org/10.1016/j.jnoncrysol.2007.09.114.

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34

Kamenova, N., P. Venkov, A. Benhammadi, and S. Monchaud. "Sensor based detection system for mobile robot." IFAC Proceedings Volumes 33, no. 20 (July 2000): 515–19. http://dx.doi.org/10.1016/s1474-6670(17)38102-8.

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35

Mayer, Michael, and Jaromir Ruzicka. "Flow Injection Based Renewable Electrochemical Sensor System." Analytical Chemistry 68, no. 21 (January 1996): 3808–14. http://dx.doi.org/10.1021/ac960524a.

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36

Young, Sheng-Joue, and Wei-Lun Tang. "Wireless Zinc Oxide Based pH Sensor System." Journal of The Electrochemical Society 166, no. 9 (2019): B3047—B3050. http://dx.doi.org/10.1149/2.0071909jes.

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37

Hines, Jacqueline H., and Leland P. Solie. "Passive saw-based hydrogen sensor and system." Journal of the Acoustical Society of America 123, no. 5 (2008): 2466. http://dx.doi.org/10.1121/1.2921157.

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38

SMITH, ROBERT, ANDREW STEVENS, ANDY FROST, and PENNY PROBERT. "Developing a sensor-based underwater navigation system." International Journal of Systems Science 29, no. 10 (October 1998): 1145–55. http://dx.doi.org/10.1080/00207729808929604.

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39

Chodavarapu, Vamsy P., Daniil O. Shubin, Rachel M. Bukowski, Albert H. Titus, Alexander N. Cartwright, and Frank V. Bright. "CMOS-Based Phase Fluorometric Oxygen Sensor System." IEEE Transactions on Circuits and Systems I: Regular Papers 54, no. 1 (January 2007): 111–18. http://dx.doi.org/10.1109/tcsi.2006.888680.

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40

Jung, In-Yong, Ki-Hyun Kim, Byong-John Han, and Chang-Sung Jeong. "Hadoop-Based Distributed Sensor Node Management System." International Journal of Distributed Sensor Networks 10, no. 3 (January 2014): 601868. http://dx.doi.org/10.1155/2014/601868.

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41

Dzulkefli, Nik Nur Shaaadah Nik, Suziyani Rohafauzi, Afiza Nur Jaafar, Rina Abdullah, Rosmawati Shafie, Muhammad Shahmir Selamat, Nazrul Syafi Azman, and Muhammad Zakwan Zakaria Muhammad. "Density Based Traffic System via IR Sensor." Journal of Physics: Conference Series 1529 (April 2020): 022061. http://dx.doi.org/10.1088/1742-6596/1529/2/022061.

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42

Hoh, S. M., P. Thorpe, K. Johnston, and K. F. Martin. "Sensor Based Machine Tool Condition Monitoring System." IFAC Proceedings Volumes 21, no. 15 (September 1988): 103–10. http://dx.doi.org/10.1016/s1474-6670(17)54684-4.

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43

Fukuda, Toshio, Koji Shimojima, Fumihito Arai, and Hideo Matsuura. "Sensor Integration System based on Fuzzy Inference." IEEJ Transactions on Electronics, Information and Systems 114, no. 1 (1994): 81–86. http://dx.doi.org/10.1541/ieejeiss1987.114.1_81.

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44

., M. Babita Devi. "WIRELESS SENSOR MODULE BASED HOME AUTOMATION SYSTEM." International Journal of Research in Engineering and Technology 05, no. 08 (August 25, 2016): 297–301. http://dx.doi.org/10.15623/ijret.2016.0508050.

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45

Sivaraman, R., Shriram K. Vasudevan, Akash Kannegulla, and A. Salivahana Reddy. "Sensor Based Smart Traffic Regulatory/Control System." Information Technology Journal 12, no. 9 (April 15, 2013): 1863–67. http://dx.doi.org/10.3923/itj.2013.1863.1867.

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46

Kim, Dong-Ok, Min-Suk Gye, and Hoe-Kyung Jung. "The Acceleration Sensor based Personalized Fitness System." International Journal of Multimedia and Ubiquitous Engineering 10, no. 1 (January 31, 2015): 317–28. http://dx.doi.org/10.14257/ijmue.2015.10.1.30.

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47

Yoannan, Shinu N. "Security System Based on Ultrasonic Sensor Technology." IOSR Journal of Electronics and Communication Engineering 7, no. 6 (2013): 27–30. http://dx.doi.org/10.9790/2834-0762730.

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48

Ong, Jin B., Osama K. Eyada, and Abu S. Masud. "A knowledge-based system for sensor selection." Computers & Industrial Engineering 17, no. 1-4 (January 1989): 85–89. http://dx.doi.org/10.1016/0360-8352(89)90041-7.

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Ong, Jin B., Abu S. M. Masud, and Osama K. Eyada. "Senses: A knowledge-based sensor selection system." Computers & Industrial Engineering 22, no. 1 (January 1992): 1–8. http://dx.doi.org/10.1016/0360-8352(92)90028-i.

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50

Seok, Kwang-Ho, Junho Ko, Chul-Won Park, Chul-Hwan Kim, and Yoon Sang Kim. "Distributed Sensor Network-Based Virtual FDR System." International Journal of Distributed Sensor Networks 9, no. 11 (January 2013): 398480. http://dx.doi.org/10.1155/2013/398480.

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