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international journal of computer techniques(ijct)

Paper Title : Android App for Women Safety: A Survey

ISSN : 2394-2231
Year of Publication : 2022

10.29126/23942231/IJCT-v9i1p2
Authors: Dr Kamalraj R, Tandra Debnath

MLA Style: Android App for Women Safety: A Survey " Dr Kamalraj R, Tandra Debnath " Volume 9 - Issue 1 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

APA Style: Android App for Women Safety: A Survey " Dr Kamalraj R, Tandra Debnath " Volume 9 - Issue 1 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

Abstract
The use of advanced cells outfitted with GPS route unit have expanded quickly from 3% to over 20% in the beyond five years. Henceforth, an advanced cell can be utilized effectively for individual wellbeing or different other security purposes particularly for ladies. This application can be initiated by a solitary snap when the client feels she is at serious risk. This application sends the client's area to the enrolled contacts for at regular intervals as message. In this way, it behaves like a sentinel following behind the individual till the client feels she is protected. This paper presents examination a special element of this application to send the message to the enrolled contacts ceaselessly till they are squeezing 'HELP' button. Nonstop area following data through SMS assists with finding the area of the casualty rapidly and can be safeguarded securely. This application expects to guarantee ladies wellbeing. This is accomplished by tending to the conditions that compromise the security of ladies in the present day and age. This application guarantees ladies are not placed into such circumstances through different highlights presented by our framework.

Reference
1. https://www.kdnuggets.com/2019/04/predict-age-gender-usingconvolutional-neural-network- opencv.html 2. https://levelup.gitconnected.com/a-small-gui-application-basedon-computer-vision-and- python-imaging-libraries-using-opencve07b3f8c06c1 3. https://medium.com/ai-in-plain-english/an-approach-towardsbuilding-a-gui-based-and-voice- controlled-security-lockmechanism-based-on-f06b47d0426e 4. https://docs.python.org/3/ 5. https://opencv.org/ 6. https://wiki.python.org/moin/TkInter 7. https://learnopencv.com/read-write-and-display-a-video-usingopencv-cpp-python/ 8. https://link.springer.com/article/10.1007/s10610-017-9341-6 9. https://www.sinch.com/ 10.S. T. PLC, “Video Surveillance Storage: How Much Is Enough?,” [Online]. Available: https://www.seagate.com/in/en/solutions/surveillance/how-much-videosurveillance-storage- is-enough/. 11. T. &. G. E. .. 8. 2.-2. 1. Moeslund, “A Survey of Computer VisionBased Human Motion Capture.,” Computer Vision and Image Understanding, pp. 231-268. 12. M. M. M. Zoltán Balogh, “Motion Detection and Face Recognition using Raspberry Pi, as a Part of, the Internet of Things,” Acta Polytechnica Hungarica, vol. 16, no. 3, 2019. 13. M. Piccardi, “Background subtraction techniques: a review,” IEEE International Conference on Systems, Man and Cybernetics , 2004 . 14. SAĞLAM, “Adaptive Camera Tamper Detection For Video Surveillance,” etd.lib.metu.edu.tr, p. 54, 2009. 15. S. a. A. Temizel, “Real-time Adaptive Camera Tamper Detection for Video Surveillance,” Advanced Video and Signal Based Surveillance, 2009 . 16. . I. R. Molano, D. Betancourt, G. Gomez, “Internet of things: A prototype architecture using a raspberry Pi,” Lecture Notes in Business Information Processing, Vol. 224, 2015, pp. 618-631 17. N. Sulman, T. Sanocki, D. Goldg of and R. Kasturi, How effective is human video surveillance performance? 19th International Conference on Pattern Recognition, Tampa, FL, 2008, pp.1- 3R. 18. Y. Mano, B. S. Faiçal, L. H. V. Nakamura, P. H. Gomes, G. L. Libralon, R. I. Meneguete, J. Ueyama, “Exploiting IoT technologies for enhancing health smart homes through patient identification and emotion recognition, ”Computer Communications, 89-90, 2016, pp. 178- 190,doi:10.1016/j.comcom.2016.03.010 19. P. Viola & M. J. Jones, “Robust real-time face detection,” International Journal of Computer Vision, 57(2), 2004, pp. 137- 154,doi:10.1023/B:VISI.0000013087.49260.fb 20. Chaudhary, R. Klette, J. L. Raheja, X. Jin, “Introduction to the specialissue on computer vision in road safety and intelligent traffic,” Eurasip Journal on Image and Video Processing, 2017(1), 2017,doi:10.1186/s13640-017-0166-5

Keywords
— Women Security, Smart Phone, Android, Registered Contacts, GPS location

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