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i-manager's Journal on Electronics Engineering (JELE)

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An Intelligent Base Link Recovery Management and Path Stability in Clustered Randomly Distributed Mobile Ad Hoc Networks
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Volume 9 Issue 1 September - November 2018

Article

An Article on CNC Upgradation

Shradha Sanjay Sandanshiv* , Swapnali Dayanand Shete, Shraddha Shrimant Shinde*, M. M. Narkhede****

- BE Graduate, Department of Electronics and Telecommunication Engineering, Pimpri Chinchwad College of Engineering, Nigdi, Pune,Maharashtra, India.

** Assistant Professor, Pimpri Chinchwad College of Engineering, Nigdi, Pune, Maharashtra, India.

Sandanshiv,S.S., Shete,S.D., Shinde,S.S., & Narkhede,M.M.(2018). A Review Paper On CNC Upgradation. i-manager’s Journal on Electronics Engineering, 9(1), 1-6. https://doi.org/10.26634/jele.9.1.14425

Abstract

This paper deals with the upgradation of CNC machine and its flexibility for modern technologies. In this paper, designing of control panel and its implementation is discussed. Different components are mounted in control panel to protect the system in case of power failure and protect motors against phase down. Almost all the industries use PLCs now-a-days because it is highly compatible, reduces wiring, and makes the design more compact and reliable. This is as up-gradation of CNC machine. Generally, PLCs are programmed in “ladder logic”, which strongly resembles a schematic diagram of relay logic. Different ladder logics are developed for performing different operations. This article can be extended further by emerging it with IIoT, i.e. Industrial Internet of Things, where we can monitor CNC machines from remote place.

References

[1]. Ansar Md, A. H., Alamoodi, M. A. H. S. M., Mahreen, S., Sultana, T., & Rahman Uzair, M. A. (2016). Features and applications of CNC Machines and Systems. International Journal of Science, Engineering and Technology Research (IJSETR), 5(3), 717-726.

[2]. Dhatrak, S. A., & Gond, V. J., (2016). Restructuring control system of top surface grinding machine for improved performance. International Journal of Electrical and Electronics Engineers, 8(2), 321-325.

[3]. Hindalekar, M. A. R., & Patil, M. S. (2015). Up – gradation of conventional control panel with PLC for the total utilization of machine. International Journal on Recent and Innovation Trends in Computing and Communication, 3(2), 461-465.

[4]. Pabla, B. S., & Adithan, M. (2007). CNC Machines. New Age Publishers, NewDelhi.

[5]. Rajput, R., & Sarathe, A. K. (2016). Comparative study of CNC Controllers used in CNC Milling Machine. American Journal of Engineering Research (AJER), 5(4), pp. 54-62.

[6]. Wadhawe, A. S., & Kurtadikar, R. P. (2014). Automation of ash handling system with event logger. International Journal of Computer Trends and Technology (IJCTT), 18(5), 231-237.

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Research Paper

Simulation and Performance Comparison of Variable Speed Multi-Phase PMSM Machines

Khadim Moin Siddiqui* , Amreen Fatma, Mohd Khursheed Siddiqui*

* Associate Professor and Head, Department of Electrical Engineering, Guru Nanak Institute of Engineering & Management, Hoshiarpur,Punjab, India.

Postgraduate, Department of Instrumentation and Control, Integral University, Lucknow, Uttar Pradesh, India.

* Associate Professor, Department of Electrical Engineering, Integral University, Lucknow, Uttar Pradesh, India.

Siddiqui,K.M., Fatma,A.,& Siddiqui,M.K.(2018). Simulation and Performance Comparison of Variable Speed Multi-Phase PMSM Machines. i-manager’s Journal on Electronics Engineering , 9(1), 7-13. https://doi.org/10.26634/jele.9.1.15120

Abstract

In the present time, the multi-phase Permanent Magnet Synchronous Machines (PMSMs) are being popular in the industries with efficient performance. In future, the multi-phase Permanent Magnet (PM) synchronous machines may be used in the variable speed drive applications, especially in renewable energy generation. Therefore, an accurate simulation model is needed for variable speed applications of PMSMs. Therefore, in this paper, an attempt has been made to make variable speed PMSMs simulation models in the latest MATLAB/Simulation environment with effective performance. The three phase and five phase variable speed PMSM machines models have been developed and both the performances have been compared. For performance comparison, three motor parameters have been used; these are stator currents, rotor speed, and electromagnetic torque. In the simulation models, two control loops have been used for efficient performance of the motor. The inner loop is used to control the speed of the motor and outer loop is used to control stator currents. The PI controller has also been used for motor controlling purpose. Finally, the authors state that the five phase variable speed PMSM motor model gives encouraging results as compared to three phase PMSM motor.

References

[1]. Choi, H. Y., Park, S. J., Kong, Y. K., & Bin, J. G. (2009, November). Design of multi-phase permanent magnet motor for ship propulsion. In Electrical Machines and Systems, 2009. ICEMS 2009. International Conference on (pp. 1-4). IEEE.

[2]. Huixian, L., & Shihua, L. (2012). Speed control for PMSM Servo system using predictive functional control and extended state observer. IEEE Trans. Ind. Electron., 59(2), 1171-1183.

[3]. Mani, M. V. (2006). A quick overview on rotatory Brush and Brushless DC Motors (Tech.Rep.) Motion Control Department, Ingenia, Barcelona, Spain.

[4]. Milanesi, F. (2009). Design optimization and control strategies for PM Multiphase Tubular Linear Actuators (Doctoral Dissertation, Alma).

[5]. Nagamani, C., & Somanatham, R. (2016). Design and analysis of traction drive system for hybrid locomotives using 5-phase permanent magnet synchronous motors as traction motors. i-manager's Journal on Electrical Engineering, 10(2), 27-45.

[6]. Pillay, P., & Krishnan, R. (1989). Modeling, simulation, and analysis of permanent-magnet motor drives. I. The permanent-magnet synchronous motor drive. IEEE Transactions on Industry Applications, 25(2), 265-273.

[7]. Pillay, P., & Krishnan, R. (1991). Application characteristics of permanent magnet synchronous and brushless DC motors for servo drives. IEEE Transactions on Industry Applications, 27(5), 986-996.

[8]. Siddiqui, K. M., Sahay, K., & Giri, V. K. (2017a). Modeling and open phase fault analysis in three and five phase permanent magnet synchronous motor machine. i-manager's Journal on Instrumentation & Control Engineering, 5(4), 32-40.

[9]. Siddiqui, K. M., Upadhyay, S. K., Singh, S., Srivastava, R. K., & Babu, R. (2017b). Performance and analysis of PWM Inverter fed 3-Phase PMSM drive. i-manager's Journal on Electronics Engineering, 8(1), 9-18.

[10]. Thakur, E. S. (2016). A review on multiphase Permanent Magnet Synchronous Motor Drive. International Journal of Innovative Research in Computer and Communication Engineering, 4(6), 11275-11282.

[11]. Zhao, Y., & Lipo, T. A. (1996). Modeling and control of a multi-phase induction machine with structural unbalance. IEEE Transactions on Energy Conversion, 11(3), 578-584.

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Research Paper

Atmospheric Radar Signal Processing Using Hybrid Window Functions

G. Chandraiah * , T. Sreenivasulu Reddy**

* Research Scholar, Department of Electronics and Communication Engineering, S.V.U. College of Engineering, S.V. University, Tirupati,Andhra Pradesh, India.

** Professor, Department of Electronics and Communication Engineering, S.V.U. College of Engineering, S.V. University, Tirupati,Andhra Pradesh, India.

Chandraiah,G.,& Reddy,T.S.(2018) Atmospheric Radar Signal Processing Using Hybrid Window Functions. i-manager’s Journal on Electronics Engineering ,9(1), 14-20. https://doi.org/10.26634/jele.9.1.14427

Abstract

The MST radar is situated at National Atmospheric Research Laboratory (NARL), Gadanki, Andhra Pradesh. This radar is used to investigate the atmospheric dynamics in the regions of Mesosphere, Stratosphere, and Troposphere (MST). MST radar was developed with an active phased antenna array consisting of 1024 Yagi-Uda antenna elements and operated by a frequency of 53 MHz. In this article, the authors introduce new hybrid window functions by using a combination of Kaiser and Blackman windows. The new hybrid window functions exhibit low side lobe levels and narrow beam width of main lobe so that the spectral leakage is minimum. The proposed window based algorithms has been applied to MST radar time series data to compute Doppler power spectrum. After computing Doppler spectrum, the wind parameters like Zonal U, Meridional V, and Wind velocity W can be calculated from the Doppler profile. The obtained wind velocity components of the MST radar data is validated through the Global Positioning System (GPS) Radiosonde data.

References

[1]. Anandan, V. K. (2001). Atmospheric Data Processor- Technical and User Reference Manual. Tirupati, India: NMRF, DOS Publication.

[2]. Anandan, V. K., Balamuralidhar, P., Rao, P. B., & Jain, A. R. (1996). A method for adaptive moments estimation technique applied to MST radar echoes. In Proc. Prog. Electromagn. Res. Symp. (pp. 360-365).

[3]. Anandan, V. K., Ramachandra Reddy G., & Rao, P. B. (2001). Spectral analysis of atmospheric signal using higher orders spectral estimation technique. IEEE Trans. Geosci. Remote Sens., 39(9), 1890-1895.

[4]. Anandan, V. K., Pan, C. J., Rajalakshmi, T., & Reddy, G. R. (2004, November). Multitaper spectral analysis of atmospheric radar signals. In Annales Geophysicae 22(11), 3995-4003.

[5]. Eappen, N. I., Reddy, T. S., & Reddy, G. R. (2016). Semiparametric algorithm for processing MST Radar Data. IEEE Transactions on Geoscience and Remote Sensing, 54(5), 2713-2721.

[6]. Hooper, D. A. (1999). Signal and noise level estimation for narrow spectral width returns observed by the Indian MST radar. Radio Science, 34(4), 859-870.

[7]. Rao, V. V. M. J., Rao, D. N., Ratnam, M. V., Mohan, K., & Rao, S. V. S. (2003). Mean vertical velocities measured by Indian MST radar and comparison with indirectly computed values. Journal of Applied Meteorology, 42(4), 541-552.

[8]. Kaiser, J. F. (1974). Nonrecursive digital filter design using the I_o-sinh window function. In Proc. 1974 IEEE International Symposium on Circuits & Systems (pp. 20- 23).

[9]. Muralidhar, P. V., Nataraj, D., Lokesh Raju, V., & Naik, S. K. (2010, July). Implementation of different FIR high pass filters using fractional Kaiser window. In Signal Processing Systems (ICSPS), 2010 2^nd International Conference on (Vol. 2, pp. V2-651). IEEE.

[10]. Rao, D. U. M., Reddy, T. S., & Reddy, G. R. (2014). Atmospheric radar signal processing using principal component analysis. Digital Signal Processing, 32, 79-84.

[11]. Reddy, T. S., & Reddy, G. R. (2010a). MST radar signal processing using cepstral thresholding. IEEE Transactions on Geoscience and Remote Sensing, 48(6), 2704-2710.

[12]. Reddy, T. S., & Reddy, G. R. (2010b). Spectral analysis of atmospheric radar signal using filter banks-polyphase approach. Digital Signal Processing, 20(4), 1061-1071.

[13]. Thatiparthi, S. R., Gudheti, R. R., & Sourirajan, V. (2009). MST radar signal processing using wavelet-based denoising. IEEE Geoscience and Remote Sensing Letters, 6(4), 752-756.

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Research Paper

Design, Implementation and Simulation of Patient Monitoring System using Steady State Visual Evoked Potential Signal based on LABVIEW

Harsha K. M.* , Shalini Shravan**

* BE Graduate, Department of Electronics and Communication Engineering, K.S. School of Engineering and Management, VTU,Bangalore, Karnataka, India.

** Assistant Professor, Department of Electronics and Communication Engineering, K.S. School of Engineering and Management, VTU,Bangalore, Karnataka, India.

Harsha,K.M.,&Shravan,S. (2018). Design, Implementation and Simulation of Patient Monitoring System Using Steady State Visual Evoked Potential Signal Based On LabVIEW.i-manager’s Journal on Electronics Engineering ,9(1),21-26. https://doi.org/10.26634/jele.9.1.14807

Abstract

Paralyzed people find it difficult to communicate their intent to serve outside world. Hence, this work provides a Mind Controlled communication system that uses Brain Computer Interface which can bypass different communication channels like neurons’ electrical activity, muscles, and thoughts to supply direct communication and management between the physical devices and human brain by translating dissimilar patterns of brain activity into instructions followed by the conversion of predefined text on the screen into voice. The proposed system consists of: Amplifier Filter circuits and LabVIEW software for signal processing and acquisition. The main aim of this work is to develop a brain computer interface system called BCI system that allows the paralyzed people to communicate their intention without any difficulty, provided it is more superior which may assist disabled folks in their everyday life. Different messages are put up on the visual stimulation screen and made to flicker at different frequencies. When patient looks at one of the flickering frequency on the screen, the same frequency is generated in the visual cortex of the human brain and the frequency is then determined by signal acquisition system and translates the predefined assigned message to voice.

References

[1]. Bender, T., Kjaer, T. W., Thomsen, C. E., Sorensen, H. B., & Puthusserypady, S. (2013, July). Semi-supervised adaptation in SSVEP-based brain-computer interface using tri-training. In Engineering in Medicine and Biology Society (EMBC), 2013 35^th Annual International Conference of the IEEE (pp. 4279-4282). IEEE.

[2]. Besio, W. G., Cao, H., & Zhou, P. (2008). Application of tripolar concentric electrodes and prefeature selection algorithm for brain–computer interface. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 16(2), 191-194.

[3]. Chan, F. H., Yang, Y. S., Lam, F. K., Zhang, Y. T., & Parker, P. A. (2000). Fuzzy EMG classification for prosthesis control. IEEE Transactions on Rehabilitation Engineering, 8(3), 305- 311.

[4]. Chang, B. C., & Seo, B. H. (2009, February). Development of new brain computer interface based on EEG and EMG. In Robotics and Biomimetics, 2008. ROBIO 2008. IEEE International Conference on (pp. 1665-1670). IEEE..

[5]. Chi, Y. M., & Cauwenberghs, G. (2009, September). Micropower non-contact EEG electrode with active common-mode noise suppression and input capacitance cancellation. In Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE (pp. 4218-4221). IEEE.

[6]. Diez, P. F., Mut, V. A., Perona, E. M. A., & Leber, E. L. (2011). Asynchronous BCI control using high-frequency SSVEP. Journal of Neuroengineering and Rehabilitation, 8(1), 39.

[7]. Dilshad, A., Uddin, V., Naz, U., Parveen, S., Javid, T., & Memon, A. M. (2016). On the development of a novel, Plug and Play SSVEP-EEG based General Purpose Human- Computer Interaction device. Asian Journal of Engineering, Sciences & Technology, 1-5.

[8]. Fukuda, O., Tsuji, T., Kaneko, M., & Otsuka, A. (2003). A human-assisting manipulator teleoperated by EMG signals and arm motions. IEEE Transactions on Robotics and Automation, 19(2), 210-222.

[9]. Hasan, M. K., Mondal, C., Al Mahmud, N., & Ahmad, M. (2015, December). Performance analysis of SSVEP based wireless Brain computer Interface for wet and dry electrode. In Advances in Electrical Engineering (ICAEE), 2015 International Conference on (pp. 64-67). IEEE.

[10]. Hazrati, M. K., Husin, H. M., & Hofmann, U. G. (2013, September). Wireless brain signal recordings based on capacitive electrodes. In Intelligent Signal Processing (WISP), 2013 IEEE 8^th International Symposium on (pp. 8-13). IEEE.

[11]. Jabode, J. S., & Shende, P. M. (2015). Literature review of Brain Computer Interface (BCI) using EEG signal. IJETT, 8(10), 1435-1467.

[12]. Lee, S., Shin, Y., Woo, S., Kin, K., & Lee, H-N. (2013). Dry electrode design and performance evaluation for EEG based BCI systems. 2013 International Winter Workshop on Brain-Computer Interface (BCI) (pp. 52-53). doi: 10.1109/IWW-BCI.2013.6506627

[13]. Lesenfants, D., Habbal, D., Lugo, Z., Lebeau, M., Horki, P., Amico, E., ...& Laureys, S. (2014). An independent SSVEP-based brain–computer interface in locked-in syndrome. Journal of Neural Engineering, 11(3), 035002.

[14]. Malmivuo, J., Ahokas, S., & Välkky, T. (2014, October). High-resolution EEG recording system using smart electrodes. In Electronic Conference (BEC), 2014 14^th Biennial Baltic (pp. 21-24). IEEE.

[15]. Oehler, M., Neumann, P., Becker, M., Curio, G., & Schilling, M. (2008, August). Extraction of SSVEP signals of a capacitive EEG helmet for human machine interface. In Engineering in Medicine and Biology Society, 2008. EMBS 2008 30^th Annual International Conference of the IEEE (pp. 4495-4498). IEEE.

[16]. Ramoser, H., Muller-Gerking, J., & Pfurtscheller, G. (2000). Optimal spatial filtering of single trial EEG during imagined hand movement. IEEE Transactions on Rehabilitation Engineering, 8(4), 441-446.

[17]. Resalat, S. N., & Afdideh, F. (2012, December). Realtime monitoring of military sentinel sleepiness using a novel SSVEP-based BCI system. In Biomedical Engineering and Sciences (IECBES), 2012 IEEE EMBS Conference on (pp. 740-745). IEEE.

[18]. Sullivan, T. J., Deiss, S. R., Jung, T. P., & Cauwenberghs, G. (2008, May). A brain-machine interface using dry-contact, low-noise EEG sensors. In Circuits and Systems, 2008. ISCAS 2008. IEEE International Symposium on (pp. 1986-1989). IEEE.

[19]. Wang, Y. T., Wang, Y., Cheng, C. K., & Jung, T. P. (2012, August). Measuring steady-state visual evoked potentials from non-hair-bearing areas. In Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE (pp. 1806-1809). IEEE.

[20]. Teng, C., Zhang, Y., & Wang, G. (2014). The removal of EMG artifact from EEG signals by the multivariate empirical mode decomposition. 2014 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) (pp. 873-876).

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Research Paper

QoS Control for Wireless Video Communication - A Survey

K. Maheswari* , N. Padmaja**

* Research Scholar, Department of Electronics and Communication Engineering, JNTUA, Anantapur, Andhra Pradesh, India.

** Professor, Sree Vidyanikethan Engineering College (Autonomous), Tirupati, Andhra Pradesh, India.

Maheswari,K., & Padmaja,N. (2018). QoS Control For Wireless Video Communication - A Survey . i-manager’s Journal on Electronics Engineering , 9(1), 27-33. https://doi.org/10.26634/jele.9.1.14810

Abstract

4G mobile phones are able to perform video coding and streaming over wireless networks, but are often constrained by the energy supply and end-to-end delay requirements. Video transmission via wireless channels with good Quality of Service (QoS) is still strenuous problem as it is a difficult task to deliver video content through limited bandwidth and error prone networks. In a real time wireless video communication system, the capture-to-display delay would significantly affect the overall video reception quality. To study, control, and optimize the quality of service parameters in the recent video transmission schemes, the DRDO for the wireless video communication system is extented and a novel control algorithm is proposed by investigating the allocation of capture-to-display delay to different delay components. Causes of end-to-end delay are identified and quantified, where the average end-to-end distortion under the transmission rate and end-to-end delay are considered by a joint selection of both source coding and channel coding parameters. To guarantee the Quality of Service (QoS), different service levels are specified for various stream of traffic in terms of delay, distortion, power, throughput, rate, and packet loss. This survey highlights, the tradeoff between various QoS parameters in the area of wireless video communication systems and quality of the reproduced picture.

References

[1]. Bobarshad, H., van der Schaar, M., Aghvami, A. H., Dilmaghani, R. S., & Shikh-Bahaei, M. R. (2012). Analytical modeling for delay-sensitive video over WLAN. IEEE Transactions on Multimedia, 14(2), 401-414.

[2]. Chen, Q. (2011). Image and video processing for denoising, coding and content protection (Doctoral Dissertation, University of Florida).

[3]. Chen, Q., & Wu, D. (2015). Delay-rate-distortion model for real-time video communication. IEEE Transactions on Circuits and Systems for Video Technology, 25(8), 1376-1394.

[4]. Chen, Z., & Wu, D. (2010). Prediction of transmission distortion for wireless video communication: Algorithm and application. Journal of Visual Communication and Image Representation, 21(8), 948-964.

[5]. Chen, Z., & Wu, D. (2012). Rate-distortion optimized cross-layer rate control in wireless video communication. IEEE Transactions on Circuits and Systems for Video Technology, 22(3), 352-365.

[6]. Gong, C., & Wang, X. (2014). Adaptive transmission for delay-constrained wireless video. IEEE Transactions on Wireless Communications, 13(1), 49-61.

[7]. Guan, Z., Melodia, T., & Yuan, D. (2013). Jointly optimal rate control and relay selection for cooperative wireless video streaming. IEEE/ACM Transactions on Networking, 21(4), 1173-1186.

[8]. He, Z., Cai, J., & Chen, C. W. (2002). Joint source channel rate-distortion analysis for adaptive mode selection and rate control in wireless video coding. IEEE Transactions on Circuits and Systems for Video Technology, 12(6), 511-523.

[9]. Hsu, C. Y., Ortega, A., & Khansari, M. (1999). Rate control for robust video transmission over burst-error wireless channels. IEEE Journal on Selected Areas in Communications, 17(5), 756-773.

[10]. Hsu, C. Y., Ortega, A., & Reibman, A. R. (1997). Joint selection of source and channel rate for VBR video transmission under ATM policing constraints. IEEE Journal on Selected Areas in Communications, 15(6), 1016-1028.

[11]. Kondi, L. P., Ishtiaq, F., & Katsaggelos, A. K. (2002). Joint source-channel coding for motion-compensated DCT-based SNR scalable video. IEEE Transactions on Image Processing, 11(9), 1043-1052.

[12]. Li, C., Wu, D., & Xiong, H. (2014). Delay-Power-Rate- Distortion Model for Wireless Video Communication under delay and energy constraints. IEEE Trans. Circuits Syst. Video Techn., 24(7), 1170-1183.

[13]. Li, C., Xiong, H., & Wu, D. (2015). Delay–rate– distortion optimized rate control for end-to-end video communication over wireless channels. IEEE Transactions on Circuits and Systems for Video Technology, 25(10), 1665-1681.

[14]. Pudlewski, S., Cen, N., Guan, Z., & Melodia, T. (2015). Video transmission over lossy wireless networks: A crosslayer perspective. IEEE Journal of Selected Topics in Signal Processing, 9(1), 6-21.

[15]. Stuhlmuller, K., Farber, N., Link, M., & Girod, B. (2000). Analysis of video transmission over lossy channels. IEEE Journal on Selected Areas in Communications, 18(6), 1012-1032.

[16]. Sühring, K. (2012). H.264/AVC Reference Software JM18.2. Retrieved from http://iphome.hhi.de/suehring/ tml/download

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Research Paper

Automatic Accident Detection and Tracking of Vehicles by Using MEMS

Vulavabeti Raghunath Reddy* , Chandra Mohan Reddy Sivappagari**

* Post Graduate, Department of Electronics and Communication Engineering, JNTUA College of Engineering, Pulivendula,Andhra Pradesh, India.

** Associate Professor, Department of Electronics and Communication Engineering, JNTUA College of Engineering, Pulivendula,Andhra Pradesh, India.

Reddy,V.R.,K.,& Sivappagari,C.M.R. (2018). Automatic Accident Detection and Tracking of Vehicles by Using MEMS. i-manager’s Journal on Electronics Engineering , 9(1), 34-40. https://doi.org/10.26634/jele.9.1.14771

Abstract

The improvement of knowledge and substructure takes through our inhales natural. The arrival of equipment consumes improved the road traffic exposures and the road accident take place regularly which practicalities enormous injury of lifetime and belongings because of the concentrated emergency facilities. Our development resolve deliver an right justification to this problem. An accelerometer can be recycled popular a car apprehension submission so that hazardous motivating can be searched. It container be rummage-sale as a crash or rollover detector of the vehicle over and subsequent an accident, an accidents can be recognized with a help of an accerlometer sensor. The main aim of implemented this project identification of accidents through vibrations the sensor is notice the signals of vehicle moves, the MEMS sensor is pass the signal to the ARM controller to performed action. The signal is send to the GSM module it gives accident location of information to the rescue team or pre-defined numbers after receiving the message rescue or predefined numbers know the accident location. Then takes the immediate action.

References

[1]. Accelerometer. (2018). In Sensorwiki. Retrieved from https://sensorwiki.org/sensors/accelerometer

[2]. Alert Scheme using Mems and GSM for Womens Safety. (2018). In IJETCSE . Retrieved from http://www.ijetcse.com/wp-content/plugins/ijetcse/file/ upload/docx/23CS1856-pdf.pdf

[3]. Goge, A., Goge, T., Thorat, P., & Dixit, R. M. (2017). Intelligent Vehicle Accident Identification by using GPS and GSM. System, 4(5).

[4]. Liquid-Crystal Display. (n.d.). In Wikipedia. Retrieved from https://en.wikipedia.org/wiki/Liquid-crystal_display

[5]. Matthews, V. O., & Adetiba, E. (2011). Vehicle Accident Alert and Locator (VAAL). International Journal of Electrical & Computer Sciences IJECS-IJENS, 11(2), 35- 38.

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[7]. Pooja, S. (2013). Vehicle tracking system using GPS. International Journal of Science and Research (IJSR), India Online ISSN, 2319-7064.

[8]. Ramani, R., Valarmathy, S., SuthanthiraVanitha, N., Selvaraju, S., Thiruppathi, M., & Thangam, R. (2013). Vehicle tracking and locking system based on GSM and GPS. IJ Intelligent Systems and Applications, 9, 86-93.

[9]. Sane, N. H., Patil, D. S., Thakare, S. D., & Rokade, A. V. Real time vehicle accident detection and tracking using GPS and GSM. International Journal on Recent and Innovation Trends in Computing and Communication.

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[11]. Varma, S. K. C., Poornesh Varma, T., & Harsha. (2013). Automatic Vehicle Accident Detection and Messaging system using GPS and GSM Modems. International Journal of Scientific & Engineering Research, 4(8).

[12]. Wei, W., & Hanbo, F. (2011, April). Traffic accident automatic detection and remote alarm device. In Electric Information and Control Engineering (ICEICE), 2011 International Conference on (pp. 910-913). IEEE.

[13]. Zhao, Y. (2000). Mobile phone location determination and its impact on intelligent transportation systems. IEEE Transactions on Intelligent Transportation Systems, 1(1), 55-64.

i-manager's Journal on Electronics Engineering (JELE)

Current Issue Vol. 14 Issue 1

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Volume 9 Issue 1 September - November 2018

An Article on CNC Upgradation

Shradha Sanjay Sandanshiv* , Swapnali Dayanand Shete**, Shraddha Shrimant Shinde***, M. M. Narkhede****

*-*** BE Graduate, Department of Electronics and Telecommunication Engineering, Pimpri Chinchwad College of Engineering, Nigdi, Pune,Maharashtra, India. **** Assistant Professor, Pimpri Chinchwad College of Engineering, Nigdi, Pune, Maharashtra, India.

Sandanshiv,S.S., Shete,S.D., Shinde,S.S., & Narkhede,M.M.(2018). A Review Paper On CNC Upgradation. i-manager’s Journal on Electronics Engineering, 9(1), 1-6. https://doi.org/10.26634/jele.9.1.14425

Abstract

References

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Simulation and Performance Comparison of Variable Speed Multi-Phase PMSM Machines

Khadim Moin Siddiqui* , Amreen Fatma**, Mohd Khursheed Siddiqui***

Siddiqui,K.M., Fatma,A.,& Siddiqui,M.K.(2018). Simulation and Performance Comparison of Variable Speed Multi-Phase PMSM Machines. i-manager’s Journal on Electronics Engineering , 9(1), 7-13. https://doi.org/10.26634/jele.9.1.15120

Abstract

References

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Atmospheric Radar Signal Processing Using Hybrid Window Functions

G. Chandraiah * , T. Sreenivasulu Reddy**

Chandraiah,G.,& Reddy,T.S.(2018) Atmospheric Radar Signal Processing Using Hybrid Window Functions. i-manager’s Journal on Electronics Engineering ,9(1), 14-20. https://doi.org/10.26634/jele.9.1.14427

Abstract

References

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Design, Implementation and Simulation of Patient Monitoring System using Steady State Visual Evoked Potential Signal based on LABVIEW

Harsha K. M.* , Shalini Shravan**

Harsha,K.M.,&Shravan,S. (2018). Design, Implementation and Simulation of Patient Monitoring System Using Steady State Visual Evoked Potential Signal Based On LabVIEW.i-manager’s Journal on Electronics Engineering ,9(1),21-26. https://doi.org/10.26634/jele.9.1.14807

Abstract

References

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QoS Control for Wireless Video Communication - A Survey

K. Maheswari* , N. Padmaja**

* Research Scholar, Department of Electronics and Communication Engineering, JNTUA, Anantapur, Andhra Pradesh, India. ** Professor, Sree Vidyanikethan Engineering College (Autonomous), Tirupati, Andhra Pradesh, India.

Maheswari,K., & Padmaja,N. (2018). QoS Control For Wireless Video Communication - A Survey . i-manager’s Journal on Electronics Engineering , 9(1), 27-33. https://doi.org/10.26634/jele.9.1.14810

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Automatic Accident Detection and Tracking of Vehicles by Using MEMS

Vulavabeti Raghunath Reddy* , Chandra Mohan Reddy Sivappagari**

* Post Graduate, Department of Electronics and Communication Engineering, JNTUA College of Engineering, Pulivendula,Andhra Pradesh, India. ** Associate Professor, Department of Electronics and Communication Engineering, JNTUA College of Engineering, Pulivendula,Andhra Pradesh, India.

Reddy,V.R.,K.,& Sivappagari,C.M.R. (2018). Automatic Accident Detection and Tracking of Vehicles by Using MEMS. i-manager’s Journal on Electronics Engineering , 9(1), 34-40. https://doi.org/10.26634/jele.9.1.14771

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Shradha Sanjay Sandanshiv* , Swapnali Dayanand Shete, Shraddha Shrimant Shinde*, M. M. Narkhede****

- BE Graduate, Department of Electronics and Telecommunication Engineering, Pimpri Chinchwad College of Engineering, Nigdi, Pune,Maharashtra, India.

** Assistant Professor, Pimpri Chinchwad College of Engineering, Nigdi, Pune, Maharashtra, India.

Khadim Moin Siddiqui* , Amreen Fatma, Mohd Khursheed Siddiqui*

* Research Scholar, Department of Electronics and Communication Engineering, JNTUA, Anantapur, Andhra Pradesh, India.

** Professor, Sree Vidyanikethan Engineering College (Autonomous), Tirupati, Andhra Pradesh, India.

* Post Graduate, Department of Electronics and Communication Engineering, JNTUA College of Engineering, Pulivendula,Andhra Pradesh, India.

** Associate Professor, Department of Electronics and Communication Engineering, JNTUA College of Engineering, Pulivendula,Andhra Pradesh, India.