Remote Offshore Oil and Gas Platform SCADA System Fault Tree Design and Minimal Cut Sets Analysis
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.775-781, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.775781
Abstract
Safety of the remote oil and gas production platform is vital. Supervisory Control and Data Acquisition System (SCADA) system ensures safe operations at remote platform by remote monitoring and control from main process complex. SCADA system at remote platform comprises of remote radio, field router, and remote telemetry unit (RTU). A frame work in designing fault tree for SCADA system at remote offshore oil and gas production platform presented in this research work. It is presented here to analyze the risk to SCADA system as it is available on corporate LAN. Appearing on internet exposed the SCADA system cyber security threats. Analysis of designed fault tree carried out by applying minimal cut sets (MCS) theorem. Fault tree analysis (FTA) is a failure analysis in which an undesired state of a system is analyzed using Boolean logic to combine a series of lower-level events. FTA is an effective technique to support probabilistic risk assessment; it can also be used as a valuable design tool. Minimal Cut Set is a set such that if any basic event is removed from it, the top event will not necessarily occur if all the remaining events in the cut set occur. MCS analysis performed to identify vulnerable faulty sub systems and their components. This analysis guides us to take appropriate action in advance to mitigate the any eventuality. Present analysis contributes directly in safety analysis. It is essential for human safety and preventing oil spill thus, contributing in environment protection.
Key-Words / Index Term
ICS, SCADA System, DCS, CIs, RTU, TDMA, MTU, Remote Offshore Platform, Fault Tree Analysis, Minimal Cut Sets (MCS)
References
[1]. Helge Janicke, Andrew Nicholson, Stuart Webber and Antonio Cau. “Runtime monitoring for industrial control systems”, Electronics 2015, Vol: 4, pp. 995-1017, 2015.
[2]. Suman Sharma, Yogesh Verma, Amit Nadda, "Information Security: Cyber Security Challenges", International Journal of Scientific Research in Computer Science and Engineering, Vol.7, Issue.1, pp.10-15, 2019
[3]. Aditya Bagri, Richa Netto and Dhruvil Jhaveri. “Article: Supervisory Control and Data Acquisition”. International Journal of computer Applications. Vol: 102. No: 10, pp. 1-5, 2014.
[4] Campos M, Teixeira H, Liporace F, Gomes M. “Challenges and problems with advanced control and optimization technologies”, IFAC Proceedings Volume 42, No. 11, pp. 1-8, 2009.
[5] H.A.Watson. “Launch control safety study”. Bell Telephone Laboratories, Murray Hill, NJ, USA, 1961.
[6]. C. A. Ericson. Fault tree analysis–a history”. In: Proc. 17th International System Safety Conference, Orlando, Florida, USA, pp. 1–9, 1999.
[7]. Mohammad Sadegh Javadi, Azim Nobakht, Ali Meskarbashee. “Fault Tree Analysis Approach in Reliability Assessment of Power System”, International Journal of Multidisciplinary Science and Engineering, Vol. 2, No. 6, pp. 46-50, 2011.
[8]. Yang Y and Jung I. “Boolean Algebra Application in Simplifying Fault Tree Analysis”. International Journal of Safety Science, Vol.1, No.1, pp. 12-19, 2017
[9]. C.C. Fong, C.H. Grigg. “Bulk power system reliability performance assessment”. Reliability Engineering Systems, Saf. 46: pp. 25–3, 1994.
[10]. A. Yadav, V.K. Harit, "Fault Identification in Sub-Station by Using Neuro-Fuzzy Technique", International Journal of Scientific Research in Computer Science and Engineering, Vol.4, Issue.6, pp.1-7, 2016
[11]. H. Haroonabadi, M.R. Haghifam: Generation reliability evaluation in power markets using Monte Carlo simulation and neural networks, in: 15th International Conf. on Intelligent Systems, Applications to Power Systems, Curitiba, 2009.
[12]. Ahmed Ali Baig, Risza Ruzli, and Azizul B. Buang, “Reliability Analysis Using Fault Tree Analysis: A Review”. International Journal of Chemical Engineering and Applications, Vol. 4, No. 3, June 2013.
[13]. Ning Cai, Jidongwang, and XinghuoYu: “SCADA system security: Complexity, History and new developments”. The IEEE International Conference on Industrial Informatics (INDIN 2008), DCC, Daejeon, Korea July 13-16, 2008.
[14]. C.L. T Borges, D.M. Falcao, J.C.O. Mello, A.C.G. Melo: “Composite reliability evaluation by sequential Monte Carlo simulation on parallel and distributed processing environments”, IEEE Transactions on Power Systems. Vol. 16, No.2, pp. 203– 209, 2001.
[15]. Pawel Skrobanek, “Minimal Cut Sets with Time Dependent Analysis”. Automatyka /Automatics, Vol 17. No.2, pp. 219-228, 2013.
[16] SINTEF, “OREDA - Offshore Reliability Data, 3rd Edition”, SINTEF Industrial Management, Trondheim, Norway. 1997.
Citation
M.V. V. Siva Prasad, P.S. Avadhani, "Remote Offshore Oil and Gas Platform SCADA System Fault Tree Design and Minimal Cut Sets Analysis," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.775-781, 2019.
Application of Genetic Algorithms: Task Scheduling in Cloud Computing
Survey Paper | Journal Paper
Vol.7 , Issue.6 , pp.782-787, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.782787
Abstract
Cloud computing implies to the delivery of information technology (IT) services which functions by retrieving the resources from the Internet; implementing various web-based tools and applications, in opposition to directly connecting to a server. In a nutshell, cloud computing works on the purpose of taking all the efforts involved in processing large quantities of data from the device carried around and moving that work to huge computer clusters far away in a virtual space. The internet becomes the virtual information space “THE CLOUD”, and all the data, work and applications are available from any device which when connected to the internet, anywhere in the world accesses it. Cloud computing is the provisioning of business computing model and providing multifarious facilities over the internet. Data that are looked over by third parties or other person at various remote locations can be assessed by individuals and various other business organizations through Cloud Computing applications. A cloud environment is categorized into computing clouds and data clouds.Task scheduling is considered to be the core feature and plays an important role in maintaining the quality of service in the cloud computing environment. The application of genetic algorithm in cloud computing task scheduler environment is a topic gaining popularity in the recent years. But, achieving an efficient task scheduling methodology is a major attribute for harnessing the potential of cloud computing applications in an effective manner. The objective of this paper is to discuss the application of heuristic algorithms; the use of GAs to minimize the total scheduling time and execution cost of tasks improves task completion time and maximize resource utilization in cloud computing framework by a task scheduler genetic algorithm.
Key-Words / Index Term
Cloud Computing; Genetic Algorithm; Selection Operation; Crossover Operation; Task Scheduling; Mutation Operation; Fitness Function
References
[1] S. H. Jang, T. Y. Kim, J. K. Kim, and J. S. Lee, "The study of genetic algorithm-based task scheduling for cloud computing," International Journal of Control and Automation, Vol. 5,pp. 157-162,2012.
[2] T. Goyal and A. Agrawal, "Host Scheduling Algorithm Using Genetic Algorithm In Cloud Computing Environment," International Journal of Research in Engineering & Technology (IJRET), Vol-1, 2013.
[3] B. Furht, "Armando Escalante Handbook of Cloud Computing," ISBN 978-1-4419-6523-3, Springer 2010.
[4] F. Etro, "Introducing Cloud Computing," in London Conference on Cloud Computing For the Public Sector, pp. 01-20,2010.
[5] R. Kaur and S. Kinger, "Enhanced Genetic Algorithm based Task Scheduling in Cloud Computing," International Journal of Computer Applications, Vol. 101, 2014.
[6] J. W. Ge and Y. S. Yuan, "Research of cloud computing task scheduling algorithm based on improved genetic algorithm," in Applied Mechanics and Materials, pp. 2426-2429, 2013.
[7] V. Vignesh, K. Sendhil Kumar, and N. Jaisankar, "Resource management and scheduling in cloud environment," International Journal of Scientific and Research Publications, Vol. 3, p. 1, 2013.
[8] Z. Zheng, R. Wang, H. Zhong, and X. Zhang, "An approach for cloud resource scheduling based on Parallel Genetic Algorithm," in Computer Research and Development (ICCRD), 2011, 3rd International Conference on, pp. 444-447, 2011.
[9] S. Singh and M. Kalra, "Scheduling of Independent Tasks in Cloud Computing Using Modified Genetic Algorithm," Computational Intelligence and Communication Networks (CICN), 2014 International Conference on, pp. 565-569, 2014.
[10] R. Buyya, R. Ranjan, and R. N. Calheiros, "Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities," in High Performance Computing & Simulation, 2009. HPCS`09. International Conference on, pp. 1-11, 2009.
[11] B. Kruekaew and W. Kimpan, "Virtual Machine Scheduling Management on Cloud Computing Using Artificial Bee Colony," in Proceedings of the International Multi-Conference of Engineers and Computer Scientists, 2014.
[12] M. Mitchell, An introduction to genetic algorithms: MIT press, 1998.
[13] R. N. Calheiros, R. Ranjan, C. A. De Rose, and R. Buyya, "Cloudsim : A novel framework for modelling and simulation of cloud computing infrastructures and services," 2009, arXiv preprint arXiv: 0903.2525, 2009.
[14] R. Sahal and F. A. Omara, "Effective virtual machine configuration for cloud environment," in Informatics and Systems (INFOS), 2014 9th International Conference on, pp.-15-20, 2014.
[15] D. M.Abdelkader, F.Omara," Dynamic task scheduling algorithm with load balancing for heterogeneous computing," Journal of system Egyptian Informatics, Vol.13, pp.135–145, 2012.
[16] International Journal of Scientific Research in Computer Sciences and Engineering (ISSN: 2320-7639)
[17] International Journal of Scientific Research in Network Security and Communication (ISSN: 2321-3256)
Citation
Srishti Garg, P. K. Chaurasia, "Application of Genetic Algorithms: Task Scheduling in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.782-787, 2019.
Evaluation to Perform a Scattered for Detecting Selfish Nodes in MANET using Collabrative Watchdog Algorithm
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.788-792, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.788792
Abstract
A mobile ad hoc network (MANET) is a self-organized system comprised by multiple mobile wireless nodes. The node misbehavior due to selfish reasons can significantly diminish the performance of MANET. A selfish node attempts to use the resources only for its own purpose and it hesitates to share the resources with their neighbors. So, it is very important to detect the selfish nodes to improve the performance of MANET. Initially, an architectural model of a MANET is constructed and the communication between the mobile is originated. The packet drop can happen in MANET due to the selfish node or network congestion. In this paper, a distributed global trust is presented to improvise the detection of selfish node in the network in MANET and then This paper studies the impact of selfish nodes concentration on the quality of service in MANETs. The main reason for using trust and reputation in this analysis is to accelerate the detection of misbehaving nodes. This study has been carried out in order to analyze the detection of selfish nodes on essential network functions such as routing and packet dropping. The simulation study demonstrate the proposed method enhances the selfish node detection ratio , packet delivery ratio(PDR), and average packet drop ratio, Quality of service.
Key-Words / Index Term
Mobile ad hoc network (MANET); Selfish node; Route discovery; Route request (RREQ); Packet delivery ratio (PDR); Trust management, Reputation system, Quality of service
References
[1] Jae-Ho C, Kyu-Sun S, SangKeun L, Kun-Lung W: Handling selfishness in replica allocation over a mobile ad hoc network. IEEE Transactions on Mobile Computing 2012, 11: 278-291.
[2] Ryu BG, Choi JH, Lee S: Impact of node distance on selfish replica allocation in a mobile ad-hoc network. Ad Hoc Netw. 2013, 11: 2187-2202. 10.1016/j.adhoc.2013.05.001
[3] Sedghi H, Pakravan MR, Aref MR: A misbehavior-tolerant multipath routing protocol for wireless ad hoc networks. Int J Res Wireless Syst 2013, 2(2):6-15.
[4] Mejia M, Peña N, Muñoz JL, Esparza O, Alzate MA: A game theoretic trust model for on-line distributed evolution of cooperation in MANETs. J. Netw. Comput. Appl. 2011, 34: 39-51. 10.1016/j.jnca.2010.09.007
[5] Singh R, Singh P, Duhan M: An effective implementation of security based algorithmic approach in mobile adhoc networks. Hum Centric Comput Inf Sci 2014, 4: 1-14. 06/19 2014 10.1186/2192-1962-4-1
[6] Hernández-Orallo E, Olmos MS, Cano J-C, Calafate C, Manzoni P: A fast model for evaluating the detection of selfish nodes using a collaborative approach in MANETs. Wirel. Pers. Commun. 2014, 74: 1099-1116. 02/01 2014 10.1007/s11277-013-1346-y
[7] Manoj V, Raghavendiran N, Aaqib M, Vijayan R: Trust based certificate authority for detection of malicious nodes in MANET. In Global Trends in Computing and Communication Systems. vol. 269. Edited by: Krishna PV. Springer, Berlin; 2012:392-401.
[8] Jawhar I, Trabelsi Z, Al-Jaroodi J: Towards more reliable and secure source routing in mobile ad hoc and sensor networks. Telecommun. Syst. 2014, 55: 81-91. 10.1007/s11235-013-9753-7
[9] Rodriguez-Mayol A, Gozalvez J: Reputation based selfishness prevention techniques for mobile ad-hoc networks. Telecommun. Syst. 2013, 1-15.
[10] Afghah F, Razi A, Abedi A: Stochastic game theoretical model for packet forwarding in relay networks. Telecommun. Syst. 2013, 52: 1877-1893. 10.1007/s11235-011-9471-y
[11] Hernandez-Orallo E, Serrat MD, Cano JC, Calafate CT, Manzoni P: Improving selfish node detection in MANETs using a collaborative watchdog. Commun Letters IEEE 2012, 16: 642-645.
[12] Padiya S, Pandit R, Patel S: Survey of innovated techniques to detect selfish nodes in MANET. IJCNWMC 2013, 3(1):221-230.
[13] Roy DB: R Chaki, MADSN: mobile agent based detection of selfish node in MANET. Int J Wireless Mobile Networks (IJWMN) 2011, 3(4):225-235. 10.5121/ijwmn.2011.3416
[14] E. Hernandez-Orallo, M. D. S. Olmos, J.-C. Cano, C. T. Calafate, and P. Manzoni, “A fast model for evaluating the detection of selfish nodes using a collaborative approach in manets," Wireless Personal Communications,Springer, vol. 74, no. 3, pp. 1099-1116, 2014.
[15] S. Gayathry and R. Gaur, “Handling sel_shness in manetsa survey," 2014.
[16] D.Anitha, Dr.M.Punithavalli.” A Collaborative Selfish Replica with Watchdog and Pathrater in MANETS”. IJCSMC, Vol. 2, Issue. 3, March 2013, pg.112 – 119.
[17] Ramasamy Murugan, Arumugam Shanmugam.” A Timer Based Acknowledgement Scheme for Node Misbehavior Detection and Isolation in MANET”. International Journal of Network Security, Vol.15, No.4, PP.241-247, July 2013.
[18] M. D. Serrat-Olmos, E. Hern_andez-Orallo, J.-C. Cano, C. T. Calafate, and P. Manzoni. ”Collaborative watchdog to improve the detection speed of black holes in manets," 2012.
[19] Reshma Lill Mathew, Prof. P. Petchimuthu.” Detecting Selfish Nodes in MANETs Using Collaborative Watchdogs”.IJARCSSE, Volume 3, Issue 3, March 2013.
[20] The network simulator - ns2. http://www.isi.edu/ nsnam/ns/
Citation
R. Manikandan, R. Mangayarkarasi, "Evaluation to Perform a Scattered for Detecting Selfish Nodes in MANET using Collabrative Watchdog Algorithm," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.788-792, 2019.
A Review: IoT Based Camera Surveillance System
Review Paper | Journal Paper
Vol.7 , Issue.6 , pp.793-800, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.793800
Abstract
IOT based Security systems are developed for keeping money safe. In this research objective is to provide more security to the physical wallet with reduced storage cost. The proposed model is capable to solve issues related to expenses and performance. Research is supposed to provide security at remote location without requirement of human attention with help of graphical processing. This research would establishment of cloud environment to host application. Implementation of frame capturing module works from two different dimensions to too boost the security. The size of captured frame sample would be reduced in order to save the storage space. Applying Edge detection mechanism would allow fetching only comparable information make system fast.
Key-Words / Index Term
IOT, Edge Detection mechanism, camera surveillance
References
[1]Muthukrishnan.R1 and M.Radha2 “Edge Detection Techniques For Image Segmentation” International Journal of Computer Science & Information Technology, Volume 3, No 6, 2011.
[2]Suryakant ,N. Kushwaha, “Edge Detection using Fuzzy Logic in Matlab,” Department of Computer Science and Engineering, NIT Jalandhar Volume 2, Issue 4, pp. 38–40, 2012.
[3]J.Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things ( IoT ): A vision , architectural elements , and future directions,” Future. Generation Compuer Sysem, Volume 29, no. 7, pp. 1645–1660, 2013.
[4]S.Saluja, A. K. Singh, and S. Agrawal, “A Study of Edge-Detection Methods,” International Journal of Advanced Research in Computer and Communication Engineering Volume 2, Issue 1,2013.
[5] Chirag M. Shah,et al, “Smart Security Solutions based on Internet of Things ( IoT ),” International Journal of Current Engineering and Technology, Volume 4, pp. 3401–3404, 2014.
[6]Indrajeet Kumar1,Jyoti Rawat2, Dr. H.S. Bhadauria3, “A CONVENTIONAL STUDY OF EDGE DETECTION TECHNIQUE IN DIGITAL IMAGE PROCESSING,” International Journal of Computer Science and Mobile Computing, Volume 3, Issue. 4, pg.328 – 334, 2014.
[7]A. R. Biswas and R. Giaffreda, “IoT and Cloud Convergence : Opportunities and Challenges,” IEEE pp. 375–376, 978-1-4799-3459-1/14/$31.00 ©2014.
[8] J. E. E. Syst and V. Mutneja, “Electrical & Electronic Systems Methods of Image Edge Detection : A Review,”Journal of Electrical & Electronic Systems volume 4, no. 2, Issue 2,2015.
[9]K. Lam and C. Chi, “Identity in the Internet-of-Things ( IoT ): New Challenges and Opportunities,”School of Computer Science and Engineering,Volume 1,2016.
[10]M. A. Iqbal, O. G. Olaleye, and A. Bayoumi, “A Review on Internet of Things (Iot): Security and Privacy Requirements and the Solution Approaches,” Global Journal of Computer Science and Technology: E Network, Web & Security, Volume 16 Issue 7, 2016.
[11]A. Tiwari and H. Maurya, “Challenges and Ongoing Researches for IOT (Internet of Things): A Review,” Volume 5, no. 2, pp. 57–60, 2017.
[12]Mahdi H. Miraz, Maaruf Ali, “A Review on Internet of Things (IoT), Internet of Everything (IoE) and Internet of Nano Things (IoNT) ” , Department of Computer Science and Software Engineering pp. 219–224, 2017.
[13]K. A. H. Ahmed ElShafee, “Design and Implementation of a WiFi Based Home Automation System,”International Journal of Computer Electronc Automation Control Inf. Eng.. Volume 6,2017.
[14]W. Zhou, Y. Jia, A. Peng, Y. Zhang, and P. Liu, “The Effect of IoT New Features on Security and Privacy : New Threats , Existing Solutions , and Challenges Yet to Be Solved,”IEEE Internet Things , vol. PP, no. c, p. 1, 2018.
[15]S. Schefer-wenzl, “NFV Enabled IoT Architecture for an Operating Room Environment,” 2018 IEEE 4th World Forum Internet Things, pp. 98–102, 2018.
[16]E. P. Yadav, “IoT : Challenges and Issues in Indian Perspective,” 3rd Int. Conf. Internet Things Smart Innovative Usages, pp. 1–5, 2018.
[17]Akanksha Bali, Mohita Raina, Simran Gupta “STUDY OF VARIOUS APPLICATIONS OF INTERNET OF THINGS ( IoT ),” International Journal of Computer Engineering & Technology , Volume 9, Issue 2,2018.
[18]T. Haikun, L. Xinsheng, L. Haitao, and Y. Xiao- guang, “Research and Application of the IOT Gateway Based on the Real-Time Specification” Volume 14, no. 3, pp. 129–141. 2018
[19]R. K. Kodali and S. Yerroju, “Energy Efficient Home Automation Using IoT,” 2018 International Conference in Computer Internet Things,2018.
[20]M. N. Ali, “Literature Review on Home Automation system for physically disabled Peoples”, 2018.
[21]K. Ito, T. Miura, N. Fukuda, and A. Hiroike, “Home Automation Platform Using Interaction-Based Sensing,” IEEE International Conference, 2019.
[22]I. P. Rai and A. A. E. S. P. Uno, “ESP32 Based Smart Surveillance System,” 2nd International Conference in Computer Engineering, 2019
Citation
Ritu Rani, Sanjeev Indora, "A Review: IoT Based Camera Surveillance System," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.793-800, 2019.
An Algorithm for Fingerprint Minutiae Extraction
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.801-809, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.801809
Abstract
Human fingerprints are reliable characteristics for personnel identification as it is unique and persistence. Fingerprint biometric authentication is one of the challenging pattern Recognition problems. A Fingerprint pattern contains ridges, valleys and minutiae. Minutiae extraction is an important post-processing step of biometric fingerprint recognition system. The minutiae are key points and the main features of a fingerprint, with which you can compare one print with another. Generally minutiae extraction is carried out after different preprocessing stage like image enhancement and image thinning so image also contains large number of false minutia which can decrease the performance of the fingerprint recognition system. A novel algorithm of fingerprint minutia extraction is proposed in this paper: The algorithm work on the thinned binary image of the fingerprint, in order to eliminate the false minutiae.The implementation of research work is done in .Net platform using custom fingerprint database of 100 images of 25 users
Key-Words / Index Term
Biometric, Fingerprint Recognition, Minutiae Extraction, Fingerprint Thinning, Fingerprint Enhancement
References
[1]Lavanya, B. N., Raja, K. B., Venugopal, K. R., & Patnaik, L. M. (2009, December). Minutiae extraction in fingerprint using gabor filter enhancement. In 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies (pp. 54-56). IEEE.
[2]Ali, M. M., Mahale, V. H., Yannawar, P., & Gaikwad, A. T. (2016, February). Fingerprint recognition for person identification and verification based on minutiae matching. In 2016 IEEE 6th International Conference on Advanced Computing (IACC) (pp. 332-339). IEEE.
[3]Chugh, T., Arora, S. S., Jain, A. K., & Paulter, N. G. (2017, September). Benchmarking fingerprint minutiae extractors. In 2017 International Conference of the Biometrics Special Interest Group (BIOSIG) (pp. 1-8). IEEE.
[4]Darlow, L. N., & Rosman, B. (2017, October). Fingerprint minutiae extraction using deep learning. In 2017 IEEE International Joint Conference on Biometrics (IJCB) (pp. 22-30). IEEE.
[5] Jain, A. K., Hong, L., Pankanti, S., & Bolle, R. (1997). An identity-authentication system using fingerprints. Proceedings of the IEEE, 85(9), 1365-1388.
[6] D. Thakkar. 2017, Minutiae Based Extraction in Fingerprint Recognition by available on https://www.bayometric.com/minutiae-based-extraction-fingerprint-recognition/ Accessed.
[7] Gowthami, A. T., & Mamatha, H. R. (2015). Fingerprint recognition using zone based linear binary patterns. Procedia Computer Science, 58, 552-557.
[8] Afsar, F. A., Arif, M., & Hussain, M. (2004, December). Fingerprint identification and verification system using minutiae matching. In National Conference on Emerging Technologies (Vol. 2, pp. 141-146).
[9] Coetzee, L., & Botha, E. C. (1993). Fingerprint recognition in low quality images. Pattern recognition, 26(10), 1441-1460.
[10] Ratha, N. K., Karu, K., Chen, S., & Jain, A. K. (1996). A real-time matching system for large fingerprint databases. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(8), 799-813.
[11] P. Peer, P. (2010). Fingerprint-based verification system a research prototype. In IWSSIP 2010-17th International Conference on Systems, Signals and Image Processing (pp. 150-153).
[12] Farina, A., Kovacs-Vajna, Z. M., & Leone, A. (1999). Fingerprint minutiae extraction from skeletonized binary images. Pattern recognition, 32(5), 877-889.
[13] Hoi Le, H. (2009). Online fingerprint identification with a fast and distortion tolerant hashing.
[14] Kaur, M., Singh, M., Girdhar, A., & Sandhu, P. S. (2008). Fingerprint verification system using minutiae extraction technique. World Academy of Science, Engineering and Technology, 46, 497-502.
[15] Shunshan, Li, Wei Min, Tang Haiying, Zhuang Tiange, and Michael H. Buonocore. "Image enhancement method for fingerprint recognition system." In 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005. 2005.
[16]Jain, A., Chen, Y., & Demirkus, M. (2006, August). Pores and ridges: Fingerprint matching using level 3 features. In 18th International Conference on Pattern Recognition (ICPR`06) (Vol. 4, pp. 477-480). IEEE.
[17] Vatsa, M., Singh, R., Noore, A., & Singh, S. K. (2009). Combining pores and ridges with minutiae for improved fingerprint verification. Signal Processing, 89(12), 2676-2685.
[18] Maltoni, D., Maio, D., Jain, A. K., & Prabhakar, S. (2009). Handbook of fingerprint recognition. Springer Science & Business Media.
[19]Kaur, M., Singh, M., Girdhar, A., & Sandhu, P. S. (2008). Fingerprint verification system using minutiae extraction technique. World Academy of Science, Engineering and Technology, 46, 497-502.
[20] Manvjeet Kaur, Mukhwinder Singh, Akshay Girdhar, and Parvinder S. Sandhu, Fingerprint Verification System using Minutiae Extraction Technique, World Academy of Science, Engineering and Technology, Vol.46, 2008, pp 499.
[21] Marius Tico, Pauli Kuosmanen, An Algorithm for Fingerprint Image Postprocessing, Computer Society IEEE. 0-7803-6541-3/00, 2000. pp 1739.
[22]Marius Tico, Pauli Kuosmanen, An Algorithm for Fingerprint Image Postprocessing, Computer Society IEEE. 0-7803-6541-3/00, 2000. pp 1736.
[23] Marius Tico, Pauli Kuosmanen, An Algorithm for Fingerprint Image Postprocessing, Computer Society IEEE. 0-7803-6541-3/00, 2000. pp 1737 – pp 1738.
[24] R.Patel D.Hiran J.Patel(2019). Fingerprint Image Thinning by applying Zhang – Suen Algorithm on Enhanced Fingerprint Image, International Journal of Computer Sciences and Engineering (ISSN: 2320-7639), Vol-7 Issue-4 May 2019.
[25]S.Suri, “Biometric based on fingerprint” International Journal of Computer Sciences and Engineering (ISSN: 2320-7639), Vol-6 Issue-5 June 2018.
Citation
Ronak B Patel, Dilendra Hiran, Jayesh M Patel, "An Algorithm for Fingerprint Minutiae Extraction," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.801-809, 2019.
Major Domains of Internet of Things (IOTS) Based Applications and Associated Challenges
Review Paper | Journal Paper
Vol.7 , Issue.6 , pp.810-818, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.810818
Abstract
In recent years Internet of Things (IoTs) concept has expanded in massive impetus due to very good Internet infrastructure everywhere. IoT has the ability to creating a network of physical things that use embedded technologies in order to sense, converse, cooperate, and team up with other things. IoT sets up sophisticated connectivity among physical things in order to make automation in specific areas. Several applications have been developed in all domains, based on IoT concepts, to collaborate with other physical things in order to achieve atomization in that area. This paper will focus on major applications of Internet of Things (IoTs) on various application domains. Internet of Things (IoTs) process is very complex in order to team up with other physical objects and deals with many challenges. This paper will also discuss with challenges of IoTs in various application domains.
Key-Words / Index Term
Internet of Things (IoTs), Embedded Technologies, Data Analytics, Controllers, Connectivity
References
[1] Angelo P. Castellani,Nicola Bui,Paolo Casari,Michele Rossi, Zach Shelby, Michele Zorzi (2010), Architecture and Protocols for the Internet of Things: A Case Study, IEEE, pages-678-683.
[2] BRICKELL , E., C AMENISCH , J., AND C HEN , L.(2004), Direct anonymous attestation, In Proceedings of the 11th ACM conference on Computer and communications security, ACM, pp. 132–145.
[3] Carretero, J. & García, J. D.(2013), The Internet of Things: connecting the world. Personal Ubiquitous Computing .
[4] D. Uckelmann, M. Harrison, F. Michahelles (2011), An Architectural Approach Towards the Future Internet of Things, Architecting the Internet of Things, Springer-Verlag Berlin Heidelberg .
[5] Daniele Miorandi, , , Sabrina Sicari, , Francesco De Pellegrini, ,Imrich Chlamtac(2012), Internet of things: Vision, applications and research challenges, Ad Hoc Networks, Volume 10, Issue 7, Pages 1497–1516.
[6] Hasan Omar AlSakran (2015), Intelligent Traffic Information System Based on Integration of Internet of Things and Agent Technology, International Journal of Advanced Computer Science and Applications,Vol. 6, No.2.
[7] Jayavardhana Gubbi, Rajkumar Buyya, Slaven Marusic, M. Palaniswami(2013), Internet of Things (IoT) : A vision, architectural elements,and future directions, Elsevier, Future Generation Computer Systems 29, 1645-1660.
[8] Jeong-Yong Byun, Aziz Nasridinov (2014), Internet of Things for Smart Crime Detection, Contemporary Engineering Sciences, Vol. 7, no. 15, 749 – 754.
[9] Lei Li, Jing Chen (2011), System Security Solutions of RFID System of Internet of Things Sensing Layer. J. Net Security Technologies and Application, (6): 34-36.
[10]Liang Shen, Yan Zhang ,JianGu (2012),Development Trend of IPv6-based Information Security Products in Network Layer of IoT. C. In: 27th National Computer Security Academic Communication. (8) :38-40.
[11] Lianos, M. and Douglas, M. (2000), Dangerization and the End of Deviance: The Institutional Environment. British Journal of Criminology, 40, 261-278.
[12] Luigi Atzori, Antonio Iera,Giacomo Morabito(2010), The Internet of Things : A Survey, Elsevier, Computer Networks 54, 2787-2805.
[13] Matthew Gigli, Simon Koo(2011) , Internet of Things: Services and Applications Categorization,Scientific Research an academic publisher , Vol.1 No.2.
[14] Mingchuan Zhang,Haixia Zhao, Ruijuan Zheng, Qingtao Wu and Wangyang Wei, Cognitive Internet of Things:Concepts and Application Example, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 6, No 3, November 2012.
[15] Nan LIN,Weihang SHI (2014), The Research on Internet of Things Application Architecture Based on Web , IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA),pages-184-187.
[16] PFLEEGER, C. P., AND P FLEEGER , S. L (2002), Security in computing . Prentice Hall Professional Technical Reference.
[17] SADEGHI , A.-R., AND S TUBLE , C(2004), Property-based attestation for computing platforms: caring about properties, not mechanisms. In Proceedings of the 2004 workshop on New security paradigms, ACM, pp. 67–77.
[18] SESHADRI , A., P ERRIG , A., V AN D OORN , L., AND K HOSLA , P. Swatt(2004), Software-based attestation for embedded devices. In Security and Privacy, 2004. Proceedings. 2004 IEEE Symposium on , IEEE, pp. 272–282.
[19]S hancan g Li, Kewan g Zhan g (2008),Principle and application of wireless sensor network, China Machine Press .
[20] SIMMONDS , A., S ANDILANDS , P., AND V AN EKERT , L. (2004),An ontology for network security attacks.In Applied Computing . Springer, pp. 317–323.
[21] Vijayakannan Sermakani (2014), Transforming healthcare through Internet of Things, Project Management Practioner’s Conference.
[22] Yang Yang (2012), Research and Design of the teaching platform architecture based on IOT , IJCSNS International Journal of Computer Science and Network Security, VOL.12 No.5, pages- 103-105.
[23] Zhao Xiaorong1, Fan Honghui1, Zhu Hongjin, Fu Zhongjun1,Fu Hanyu(2015), The Design of the Internet of ThingsSolution for Food Supply Chain, 5th International Conference on Education, Management, Information and Medicine
[24] Zhanlin Ji , Ivan Ganchev , Máirtín O’Droma , Li Zhao and Xueji Zhang(2014) , A Cloud-Based Car Parking Middleware for IoT-Based Smart Cities: Design and Implementation, Sensors 2014.
[25]ZHIBO PANG (2013), echnologies and Architectures of the Internet-of-Things (IoT) for Health and Well-being, Royal Institute of Technology, Doctoral Thesis in Electronic and Computer Systems, Stockholm, Sweden.
Citation
Dharmendra Patel1, Pranav Vyas, Atul Patel, "Major Domains of Internet of Things (IOTS) Based Applications and Associated Challenges," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.810-818, 2019.
Survey On Multihop Cluster Head Techniques in MODLEACH
Survey Paper | Journal Paper
Vol.7 , Issue.6 , pp.819-821, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.819821
Abstract
MODLEACH is modified version of LEACH protocol, in this protocol, for every round, new cluster head is elected and hence new cluster formation is required. This paper gives the over view of Enhanced MODLEACH for cluster head selection. The data transfer in clusters among nodes depends upon the approach used, the intra cluster and inter cluster technique increases the network life. So this paper presents the data transfer techniques and clustering in MODLEACH protocol.
Key-Words / Index Term
WSN, LEACH, MODLEACH, life time, cluster heads, Residual energy
References
[1] Pyush shaarma et al, “Enhancing MODLEACH using Multihop Cluster Heads as Forwarder Nodes” ijirs, Volume – 7 Issue -2 February 2018.
[2] Priyanka et al, “Enhanced MODLEACH Using Effective Energy Utilization Technique for Wireless Sensor Network “,International Journal Of Engineering And Computer Science”, Volume 5 Issue 09 September 2016 .
[3] Mr. Santosh.Irappa.Shirol et al, “Advanced-LEACH Protocol of Wireless Sensor Network”, International Journal of Engineering Trends and Technology (IJETT) - Volume4 Issue6- June 2013.
[4] Rajashree.V.Biradar Et Al, “Classification And Comparison Of Routing Protocols In Wireless Sensor Networks”, UbiCC Journal – Volume 4.
[5] Chunyao FU et al, ” An Energy Balanced Algorithm of LEACH Protocol in WSN”, International Journal of Computer Science Issues, Vol. 10, Issue 1, No 1, January 2013.
[6] I.F. Akyildiz, W. Su*, Y. Sankarasubramaniam, E. Cayirci,” Wireless sensor networks: a survey”, Elsevier, Computer Networks 38, 393–422, 2002.
[7] S. Rani and S.H. Ahmed, Multi-hop Routing in Wireless Sensor Networks, Springer Briefs in Electrical and Computer Engineering.
[8] Jing, Yang, Li Zetao, and Lin Yi. "An improved routing algorithm based on LEACH for wireless sensor networks." Control and Decision Conference (CCDC), 25th Chinese. IEEE, 2013.
[9] Beiranvand, Zahra, Ahmad Patooghy, and Mahdi Fazeli. "I-LEACH: An efficient routing algorithm to improve performance & to reduce energy consumption in Wireless Sensor Networks." Information and Knowledge Technology (IKT), 5th Conference on. IEEE, 2013.
[10] Xu, Jia, Ning Jin, Xizhong Lou, Ting Peng, Qian Zhou, and Yanmin Chen. "Improvement of LEACH protocol for WSN.", In Fuzzy Systems and Knowledge Discovery (FSKD), IEEE 9th International Conference on, pp. 2174-2177, 2012.
Citation
Manpreet Saini, Sukhbeer Singh, Neelam Chouhan, "Survey On Multihop Cluster Head Techniques in MODLEACH," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.819-821, 2019.
Smart Drip Using Arduino Microcontroller
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.822-829, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.822829
Abstract
During recent years due to the technological advancements many sophisticated techniques has been evolved for assuring fast recovery of the patients in hospitals. For good patient care in hospitals, assessment and management of patient’s fluid in the drip is the most fundamental thing required. All most in all hospital, an assist/nurse is responsible for monitoring the fluid level continuously. But in the government hospitals due to the unavailability of enough number of nurses, observing this fluid is a great headache to the hospitals. Our smart drip using Arduino microcontroller will overcome the complications like infiltration, hematoma, air embolism, blood backup in tubing, extra vascular Injection, Intra-arterial Injection etc. It will detect the emptying of drip bag with the help of Ultrasonic sensor. To overcome this critical situation, we develop a smart drip using arduino with automatic alerting and indicating system is proposed where Ultrasonic sensor is used as a level sensor. Whenever the fluid becomes low, it will send an alert message to the nurse rooms and also nurses can monitor the LIVE level graph in their computer. This technology reduces the work of the nurse rather than keep on looking of an IV Fluid system. one of the best advantages of our project is that the ease interface with users that functionally can be managed by means of an alert message.
Key-Words / Index Term
Arduino Microcontroller, Ultrasonic Sensor, Drip
References
[1] R.Vasuki, Dennis, HemPriya Changer, “An portable monitoring device of measuring drips rate by using an Intravenous (IV) set”, International Journal of Biotechnology Trends and Technology Vol. 1, Issue 3, No.4 2011.
[2] C.C.Gavimath, Krishnamurthy Bhat, C.C.Chayalakshmi, R.S.Hooli, B.E.Ravishankera “Design and Development of versatile saline flow rate measuring system and GSM based remote monitoring device”, International Journal Of Pharmaceutical Applications ISSN 0976-2639.
[3] R.Aravind, Syed Mustak Ahmed “Design of family health monitoring system using wireless communication”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 9, September 2013 [4] V.Ramya, B.Palaniappan, Anuradha Kumari “Embedded patient monitoring system” International Journal of Embedded Systems and Applications (IJESA) Vol.1, No.2,
December 2011
[5] D.Janani, J.Prathibanandhi, P.Meenakshi Vidya, K.S.Sujatha “Wireless Saline Bottle Level Indicator for Hospitals”, Compo soft an International Journal of Advanced computer Technology.
[6] Nakajima K., Osa A., Maekawa T. and Mike H. [1997]. “Evaluation of Body Motion by Optical Flow Analysis”, Japan Journal of Applied Physics, 36(5A), Part 1, 2929- 2937. [7] Cyber-Physical Medical and Medication Systems by Albert M. K. Cheng, 2008.
[8] Zhou Xiao, Li Jiaming, Pu Junjia, Yang Zhi, “The Design and implement of Mobile Remote Medical Ward System.” 2010.
[9] Nivedita Daimiwal, DipaliRamdasi, RevathiShriram, AsmitaWakankar, “Wireless Transfusion Supervision and Analysis Using Embedded System”.
[10] . Hung, Orlando R., Peter H. Gregson, and David C. Roach. "Fluid monitoring device." U.S. Patent No. 7,327,273. 5 Feb. 2008.
Citation
Amal Ajayan, V Sheeja Kumari, Fathima Abdul Rahim, Sooraj S, "Smart Drip Using Arduino Microcontroller," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.822-829, 2019.
Providing Privacy in Profile Based Personalized Web Search
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.830-836, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.830836
Abstract
Web search engines (e.g. Google, Yahoo, Microsoft Live Search, Bing, etc.) are mostly used to search certain information from a large amount of data in a very few amount of time. Aforementioned engines are built for all kind of people and not for any particular client that is, it gives generalized result for input query and not user specific result, to address this problem personalized web search is best way to increase the accuracy of web search in terms of giving user specific results. However, effective personalized web search requires gathering and aggregating user information (e.g. user name, contact no, etc), which often raises serious concerns of privacy infringement for many users. In fact, these privacy concerns have become one of the major reasons for deploying personalized web search applications and how to do privacy-preserving personalization is a great challenge. In this proposed system, we propose and try to resist adversaries with broader background knowledge, such as richer relationship among topics. Richer relationship means we generalize the user profile results by using the background knowledge which is going to store in history. Through this we are able to hide the user search results. By using this new mechanism, we can achieve the better privacy and improve better search quality results.
Key-Words / Index Term
Data security, public server, SSM, PWS
References
[1] Ms. Suvarna A Veer, Rajani S. Sajjan Computer Science & Engineering Department, VVPIET, Solapur, India “Providing Privacy in Domain Specific Search with SSM and Cosine Similarity” www.jetir.org Volume 5, Issue 12 JETIR December2018,
[2] Mrs. Sharvari V. Malthankar , Prof. Shilpa Kolte PG Student, “Client side Privacy Protection Using Personalized Web Search” Elsevier Science direct 7th International Conference on Communication, Computing and Virtualization 2016
[3] S. Manek fmanek3@gmail.com Aishwarya J. Reddy Vaibhavu panchal Vijaya Pinjarkar Department of Information Technology K.J.Somaiya Institute of Engineering and Information Technology, Sion. Mumbai, Maharashtra, India vkhirodkar@somaiya.edu “Hybrid Crawling for Time-Based Personalized Web Search Ranking Foram” 978-1-5090-5686-6/17/$31.00 ©2017 IEEE
[4] Pratibha Rathod pratima.rathod15@gmail.com Smita Desmukh Information Technology, deshmukhsmita17@yahoo.com “A Personalized Mobile Search Engine based on User Preference” IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI-2017)
[5] Lidan Shou, He Bai, Ke Chen, and Gang Chen,“Supporting PrivacyProtection in Personalized Web Search”,IEEE Transactions on Knowledge and Data engineering,vol.26,no.2,february 2014
[6] Sachin S. Kale1, Dattatray N. Udmale1, Anjali B. Navale1, Prerana S. Wagh1, Prof. Rahinj P.L2 B.E “Supporting Privacy Protection in Personalized Web Search, India International Journal of Innovative Research in Computer and Communication Engineering 2017
[7] Brahmaji Katragadda, 2Sk.Meera “Supporting Privacy Protection in Personalized Web Search” Journal of Science and Technology (JST) Volume 2, Issue 7, July 2017
[8] Anoj Kumar anoj.kr@hotmail.com Mohd. Ashraf ashraf.saifee@gmail.com “Personalized Web Search Engine using Dynamic User Profile and Clustering Techniques” 978- 9-3 805-4416-8/15/$31. 00 c2 01 5 IEEE
[9] K R Remesh Babua,Philip Samuelb, “Concept Networks for Personalized Web Search Using Genetic Algorithm” International Conference on Information and Communication Technologies 2016
[10] Kamlesh Makvana, Pinal Shah, Parth Shah, kamleshmakvana.it@charusat.ac.in, parthshah.ce@charusat.ac.in pinalshah.it@charusat.ac.in “A Novel Approach to Personalize Web Search through User Profiling and Query Reformulation” 978-1-4799-4674-7/14/$31.00©2014 IEEE
[11] V.Ramya, S.Gowthami “ENHANCE PRIVACY SEARCH IN WEB SEARCH ENGINE USING GREEDY ALGORITHM” International Journal of Scientific Research Engineering & Technology (IJSRET), ISSN 2278 – 0882 Volume 3, Issue 8, November 2014
[12] Zhan Su, Byung-Ryul Ahn, Ki-yol Eom, Min-koo Kang, Jin-Pyung Kim, Moon-Kyun Kim Department of Artificial Intelligence, University of Sungkyunkwan Cheoncheon dong, Jangan-gu, Suwon, Korea “Plagiarism Detection Using the Levenshtein Distance and Smith-Waterman Algorithm” The 3rd Intetnational Conference on Innovative Computing Information and Control (ICICIC`08) 978-0-7695-3161-8/08 $25.00 © 2008 IEEE
[13] Alfirna Rizqi Lahitani1, Adhistya Erna Permanasari, Noor Akhmad Setiawan Department of Electrical Engineering and Information Technology, Faculty of Engineering Universitas Gadjah Mada “Cosine Similarity to Determine Similarity Measure: Study Case in Online Essay Assessment” ACM 2011
[14] ZHENGHUA XU1 , OANA TIFREA-MARCIUSKA2 , THOMAS LUKASIEWICZ1 ,MARIA VANINA MARTINEZ3 , GERARDO I. SIMARI3 , and CHENG CHEN “Lightweight Tag-Aware Personalized Recommendation on the Social Web Using Ontological Similarity” 4 2169-3536 (c) 2018 IEEE
[15] Yayuan Tang 1;2 , Hao Wang 3 , Kehua Guo 2;4 , Yizhe Xiao 2 , Tao Chi “Relevant Feedback Based Accurate and IntelligentRetrieval on Capturing User Intention for Personalized Websites” 2169-3536 (c) 2018 IEEE
[16] Mohammad Mustaneer Rahman, and Nor Aniza Abdullah, “A Personalised Group-Based Recommendation Approach for Web Search in E-Learning” IEEE 2169-3536 (c) 2018 IEEE.
[17] Puxuan Yu Wuhan University Wuhan, China pxyuwhu@gmail.com Wasi Uddin Ahmad wasiahmad@ucla.edu “Hide-n-Seek: An Intent-aware Privacy Protection Plugin for Personalized Web Search” 18, July 8-12, 2018, Ann Arbor, MI, USA Italy. 2016 ACM. ISBN 978-1-4503-4069-4/16/07
[18] Gerard Deepak, B. N. Shwetha, C. N. Pushpa, J. Thriveni & K. R. Venugopal “A hybridized semantic trust-based framework for personalized web page recommendation” International Journal of Computers and Applications ISSN: 1206-212X (Print) 1925-7074
[19] Najneen Tamboli, Sathish Kumar “Review on Privacy Preservation in Personalized Web Search” International Journal of Innovative Research in Computer and Communication Engineering (An ISO 3297: 2007 Certified Organization) Vol. 3, Issue 11, November 2015
[20] Avi Arampatzis, George Drosatos and Pavlos S. Efraimidis, “A Versatile Tool for Privacy -Enhanced Web Searc” Xant hi 67 100, Greece Springer- Verlag Berlin Heidelberg 2013
[21] B. SekharBabu, P. Lakshmi Prasanna, D. Rajeswara Rao, J. LakshmiAnusha, A. Pratyusha and A. Ravi Chand, “PROFILE BASED PERSONALIZED WEB SEARCH USING GREEDY ALGORITHMS” MAY 2016 ISSN 1819-6608 ARPN Journal of Engineering and Applied Sciences
[22] M. Spertta and S. Gach, “Personalizing Search Based on User Search Histories,” Proc. IEEE/WIC/ACM Int’l Conf. Web Intelligence (WI), 2005.
[23] Hina Ansari Mahakal Institute of Technology, Ujjain “Issues and Challenges in Measuring Security Threats During Personalized Web Search” , Volume-3, Issue-6 ISSN: 2320-7639, IJSRCSE, 2015
Citation
Rajani S. Sajjan, Suvarna A. Veer, "Providing Privacy in Profile Based Personalized Web Search," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.830-836, 2019.
A Survey on Various Approaches of Automatic Optical Inspection for PCB Defect Detection
Survey Paper | Journal Paper
Vol.7 , Issue.6 , pp.837-841, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.837841
Abstract
The Printed circuit board (PCB) is one of the crucial components of the electronics industry. An automated visual inspection system is required to provide a fast and quantitative assessment of PCB, since manual defect detection system is not efficient and time-consuming. Machine vision technology is an alternative to manual inspections and measurements with the help of high-resolution digital camera and image processing. This paper presents the various possible defects in PCB that can affect the working of electronic gadgets. Major defects are classified mainly under Fatal and Potential that can be detected mainly by any of the three approaches as Referential, Non-referential, and, Hybrid to find out defects present in PCB. After a comparative study of these methods, we have tried to find out the significantly fast and accurate method.
Key-Words / Index Term
PCB, Automated Visual inspection, Machine Vision, Image processing, Referential, Non-referential, Hybrid approach
References
[1] M. Kumar, N. Kumar, M. Kumar, Ajay Kumar Vishwakarma, “A Novel Approach of Standard Data Base Generation for Defect Detection in Bare PCB”, in the IEEEinternational conference on ICCCA, 2015, pp. 11-15, 2015.
[2] M. Kumar, M. Kumar, G. Kumar, “PCB Image Enhancement using Machine Vision for Effective Defect Detection”, international Journal of Advanced Engineering Research and Science (IJAERS) Vol-1, Issue-3, pp.50-53, Aug- 2014.
[3] A. eohong, Z.B. Ibrahim, S. Ramli, “Computer machine vision inspection on Printed Circuit Board flux defects”, American Journal of Engineering and Applied Sciences, Science Publication, Vol-6, Issue-3, pp.263-273, 2013.
[4] Y. hanlin, W. jun., “Automatic detection method of Circuit Boards defect based on partition enhanced matching”, Information Technology Journal, Vol-11, pp.2256-2260, 2013.
[5] T.J. Mateo Sanguino and M.S. Rodriguez, “Computer-Aided System for Defect Inspection in the PCB Manufacturing Process”, In the 16th IEEE International Conference on Intelligent Engineering Systems, pp. 151-156. 2012.
[6] Z. Li, Q. Yang, “System design for PCB defects detecion based on AOI technology”, In IEEE, International Congress on Image and Signal Processing, Vol-4, pp.1988-1992, 2011.
[7] F. Guo, S. Guan,” Research of the Machine Vision Based PCB Defect Inspection System”, In IEEE International Conference on Intelligence Science and Information Engineering, pp. 472-475, 2011.
[8] S. Guan, F. Guo, “A New Image Enhancement Algorithm for PCB Defect Detection”, In IEEE International Conference on Intelligence Science and Information Engineering, pp.454-456 2011.
[9] Z. Ibrahim, N.K. Khalid, I. Ibrahim, M.S. Zainal Abidin, M.M. Mokji, S. A. Rahman Syed Abu Bakar,” A noise elimination procedure for Printed Circuit Board inspection system” In the 2nd IEEE Asia International Conference on Modelling & Simulation, pp. 332-33, 2008.
[10] S. Mashohor, J.R. Evans, A.T. Erdogan “Automatic Hybrid Genetic Algorithm Based Printed Circuit Board Inspection” In the IEEE NASA/ESA Conference on Adaptive Hardware and Systems, pp. 390-400, 2006.
[11] Z. Ibrahim , S.A.R Al-Attas, O. Ono, and M.M. Mokji, “A noise elimination procedure for Wavelet-Based Printed Circuit Board inspection system”, Asian Control Conference, pp. 875-880, 2004
[12] J.J. Hong, K.J. Park, K.G. Kim “Parallel Processing Machine Vision System for Bare PCB Inspection”, In IECON`98, Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society, Vol. 3, pp. 1346-1350, 1998.
[13] M. Moganti., F. Ercal, S. Tsunekaw,“Automatic PCB inspection algorithms: A Survey”, Computer vision and image understanding, Vol.63, pp. 287–313, 1996.
[14] T.S. Newman, A.K. Jain,“A Survey of Automated Visual inspection”, Computer vision and image understanding, Vol. 61, pp. 231-262,1995.
[15] Y. Hara., N. Akiyana, and K. Kaasaki , “Automatic inspection system for Printed Circuit Boards”, IEEE Transactions on pattern analysis and Machine intelligence, Vol. 6, pp. 623-630, 1983.
[16] F.R. Leta, F.F. Feliciano, F.P. Martins “Computer vision system for Printed Circuit Board inspection”, ABCM Symposium Series in Mechatronics, Volume 3, pp. 623-632, 2008.
Citation
Mukesh Kumar, Manjesh kumar, "A Survey on Various Approaches of Automatic Optical Inspection for PCB Defect Detection," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.837-841, 2019.