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The expensive, inefficient and unreliable nature of the existing communication systems, makes them inadequate for use in raising security awareness in local areas such as the University of Bamenda campus. With the current sociopolitical crisis in the region, there is a need for a reliable communication system which can be used to improve upon the security of staff and students on campus. This research project proposes a solution which is cost, time and power efficient. This system was analyzed and designed by following an evolutionary prototyping life cycle model which consists of developing a robust prototype in a structured manner which is constantly refined with user feedback to get a better end product. Mathematical analysis of the system components was used to determine the system specifications for the project. This solution has a low power requirement and does not depend on mobile networks. Simulation results showed our system is capable of receiving and transmitting information without any degradation of the signal within a 100m range when supplied with a 9V dc supply.


Communication Frequency Modulation Signal Distance Power

Article Details

How to Cite
Suh Charles Forbacha, & Walters Marlene Bih Mbakwa Anagho. (2021). Design and implementation of a security communication system for a local area: case study the university of bamenda. International Journal of Human Computing Studies, 3(1), 52-73.


  1. Ahmed, M. S., Mohammed, A. S., & Agbo, G. A., (2006) Development of a Simple Sound Activated Burglar Alarm System. Leonardo Journal of Sciences, no. 9, p. 97-102.
  2. Baiying, L., & Man-Wai, M, (2015) Sound-Event Partitioning and Feature Normalization for Robust Sound-Event Detection. Hong Kong Polytechnic University, Hong Kong.
  3. Binu, F., Jacob, F., Richard, T., Yakov, D., Theus, A. & Vijayan, A.. (2011) Multi-Pose Face Recognition And Tracking System, in Complex Adaptive Systems, Chicago.
  4. Chang, C. Y., & Chang, Y.P., (2013) Application of Abnormal Sound Recognition System for Indoor Environment, in Proc. IEEE International Conference on Information, Communication & Signal Processing ICICS, Tainan, Taiwan.
  5. Etienne, C. & Francois, B., (2006) Combining face detection and people tracking in video sequences.
  6. Mykhalo, A., Stefan, R. & Bernt, S., (2008)
  7. People-Tracking-by-Detection and People-Detection-by-Tracking.
  8. Bhavani, K., Dhanara.j, V., Siddesh, N. V., Ragav, V. & Uma, R. S., (2017) Real time Face Detection and Recognition in Video Surveillance, International Research Journal of Engineering and Technology (IRJET), p. 1562-1565, .
  9. FEANTSA (2013) Using Information and Communication Technology in Addressing Homelessnes.
  10. Grezl, F. & Cernocky, J., (2009) Audio Surveillance through Known Event Classification, Radioengineering, vol. 18, no. 4, p. 671-675.
  11. Gupta, D., Bansal, P & Choudhary, K.,(2017) The State of the Art of Feature Extraction Techniques in Speech Recognition. Advances in Intelligent Systems and Computing, vol. 664, p. 195-207.
  12. Jaeseok, Y & Sang, S. L., (2014) Human Movement Detection and Identification Using Pyroelectric Infrared Sensors.
  13. Junho, C. & Lyon, P., (1994) Effects of Modulation Index on Telecommunication.
  14. Manoha, K., (2018) Analog Communication Laboratory Manual.
  15. Michalis, Z. (2013), Multi-camera face detection and recognition applied to people tracking.
  16. Morgan, D. K. (2003) Datasheet on CD4046B Phase-Locked Loop: A Versatile Building Block for Micropower Digital and Analog Applications, TEXAS INSTRUMENTS.
  17. Murungi, M., (2009) Video surveillance system design.
  18. Nizar, Z., Ziad, A. H. & Rada, D., (2008) Real-Time Human Motion Detection and Tracking.
  19. Ntalampiras, S., (2013), Audio surveillance, WIT Transactions on State of the Art in Science and Engineering, vol. 54, p. 191-205.
  20. Oguche, I. A., Agber, J. U. & Tarkaa, S., (2017) Design and Construction of an Audio Surveillance System, Communications on Applied Electronics CAE, vol. 6, no.10, p. 21-27. Ntalampiras, S., Pottammitis, I. & Fakotakis, N (2009) Acoustic Surveillance of Hazardous Situations, in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP, Taipei, Taiwan.
  21. Oltean, G., Grama, L., Ivanciu, L., & Rusu, C. (2015) Alarming Events Detection Based on Audio Signals Recognition, in Proc. IEEE International Conference on Speech Technology and Human Computer Dialogue (SpeD), Bucharest, Romania.
  22. Pavithra, S., Mahanthesh, U. & Stafford, M. (2016) Human Motion Detection and Tracking for Real-Time Security System. International Journal of Advanced Research in Computer and Communication Engineering.
  23. Ramey, K., (2013) Use of Technology in Communication. Available: CDvb4G4YYWoYTwtF&cf=1.
  24. Rouas, J. Louradour, M. & Ambellouis, S., (2006) Audio Events Detection in Public Transport Vehicle, in Proc. IEEE Intelligent Transportation Systems, Toronto, Ont, Canada.
  25. Saha, J. K., Ghuri, M. A., Mamur, M. R., Hosain, T. A., Chowdhury, T. A. & Paul, B., (2016) A Novel Design and Implementation of a Real-time Wireless Video and Audio Transmission Device WSEAS, vol. 4, p. 161-172.
  26. Simon Haykin, M. M., (2007) An Introduction to Analog and Digital Communications, United States of America: John Wiley & Sons, Inc.
  27. Uzkent, B. & Barkana, B. D., (2011) Pitch-Range Based Feature Extraction for Audio Surveillance Systems in Proc. IEEE Eighth International Conference on Information Technology: New Generations, Las Vegas, NV, USA.
  28. Vandit, G., Ayesha. G., & Yash. K., (2018) Human Detection and Tracking for Video Surveillance: A Cognitive Science.