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Reseach Article

Re-engineering Real-time Intrusion and Burglary Detection using Fuzzy Technique

by Isah Mohammed M., Charles Ikerionwu, Chinenye C. Opara
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 16
Year of Publication: 2020
Authors: Isah Mohammed M., Charles Ikerionwu, Chinenye C. Opara
10.5120/ijca2020920079

Isah Mohammed M., Charles Ikerionwu, Chinenye C. Opara . Re-engineering Real-time Intrusion and Burglary Detection using Fuzzy Technique. International Journal of Computer Applications. 176, 16 ( Apr 2020), 8-17. DOI=10.5120/ijca2020920079

@article{ 10.5120/ijca2020920079,
author = { Isah Mohammed M., Charles Ikerionwu, Chinenye C. Opara },
title = { Re-engineering Real-time Intrusion and Burglary Detection using Fuzzy Technique },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2020 },
volume = { 176 },
number = { 16 },
month = { Apr },
year = { 2020 },
issn = { 0975-8887 },
pages = { 8-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number16/31283-2020920079/ },
doi = { 10.5120/ijca2020920079 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:42:40.797961+05:30
%A Isah Mohammed M.
%A Charles Ikerionwu
%A Chinenye C. Opara
%T Re-engineering Real-time Intrusion and Burglary Detection using Fuzzy Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 16
%P 8-17
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The alarming rate of burglary and theft across the country, which has drawn societal security concerns, increased individual and government spending in protection of lives and properties, necessitated the urgent need to design and implement an automated building intrusion and theft detection system. In this paper, a burglary and theft detection system using Fuzzy Logic and Short Message Service (SMS) system that will detect intruders and report this crime on a real-time was realized. The design approach combines the acquisition of vibration signal obtained from the burgles/intruder(s) by microcontroller-based accelerometer, intrusion detection logic built on the Fuzzy Inference System installed and configured on a cloud infrastructure with an alerting system which communicates on a real time basis to the appropriate authorities of an intrusion/burglary. This phenomenal innovation and breakthrough in intrusion detection systems will bring about the detection and prosecution of intruders/burglars and thieves in the society – thus reducing the level of crime.

References
  1. Ahn, S. W., Jung, H. S., Lee, Y. W., and Yoo, C. 2009. Network condition adaptive real-time streaming of an intelligent ubiquitous middleware for u-City. In Proceedings of the 4th International Conference on Ubiquitous Information Technologies & Applications.
  2. Anon (2001) Contractors Equipment Losses: Knowledge of Hazards Can Reduce Risk. “Insurance Journal”. Retrieved 19 February 2009 from http://www.insurancejournal.com/magazines/southcentral/2001/02/19/features/22326.htm
  3. Chaudhary, T., Tiwari, H., and Kumar, U., 2019. “Fuzzy Logic Based Intrusion Detection Systems in Mobile Ad Hoc” International Journal of Information Technology, at Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi (INDIA)
  4. Coole, M., Woodward, A. and Valli, C., 2012. Understanding the Vulnerabilities in Wi-Fi and the Impact on its Use in CCTV Systems.
  5. Costin, A., 2016, October. Security of cctv and video surveillance systems: Threats, vulnerabilities, attacks, and mitigations. In Proceedings of the 6th international workshop on trustworthy embedded devices
  6. Curtin, L., Tilley N., Owen M. and. Pease K, 2001. Developing Crime Reduction Plans: Some Examples from the Reducing Burglary Initiative. Crime Reduction Research Series, Paper7. London: Home Office. First Publisher, 1-84082-632-0.
  7. Eseosa, O. and Promise, E., 2014. GSM based intelligent home security system for intrusion detection. International Journal of Engineering and Technology
  8. Fitzgerald, J. and Poynton S., 2011. The Changing Nature of Objects Stolen in Household Burglaries. NSW Bureau of Crime Statistics and Research. Issue paper no. 62.
  9. Jordal, R.L., 1989. Integrated smoke and intrusion alarm system. U.S. Patent 4,862,14
  10. Khanna, V. and Cheema, R.K., 2013. Fire detection mechanism using fuzzy logic. International Journal of Computer Applications
  11. Nancy, G., Samantha, S., Allison, M., and Joshua A., 2011. Surveillance Systems for Crime Control and Prevention: A Practical Guide for Law Enforcement and Their Municipal Partners. The Urban Institute, 978-1-935676-35-5
  12. Obermaier, J. and Hutle, M., 2016, May. Analyzing the security and privacy of cloud-based video surveillance systems. In Proceedings of the 2nd ACM international workshop on IoT privacy, trust, and security
  13. Omorogiuwa, E. and Elechi, P., 2015. Economic Effects of Technical and Non-Technical Losses in Nigeria Power Transmission System. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), Vol. 10 No.2, pp. 89-100, 2015.
  14. One Square Metre (2019) “Small & Large Building” –https://www.onesquaremetres.com/small-large-building/
  15. Zurich, 1999. Suggestions for Use of Video Surveillance Cameras “Clear thinking on fuzzy logic “L.A. Bernardinis (Machine Design, April 1993) Fuzzy set by Ivars Perterson (Science News , Vol. 144, July 24, 1993, pp. 55).
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy Inference System Burglary Detection system Intrusion detection system Theft detection system Short Message Service (SMS) system