DOI QR코드

DOI QR Code

Secure Internet of Things Based Human Detection in Computer Vision

  • Fatima Ashraf (Department of Information Technology, Government College University) ;
  • Sheraz Arshad Malik (Department of Information Technology, Government College University) ;
  • Muhammad Ayub Sabir (Department of Information Technology, Government College University)
  • 투고 : 2024.10.05
  • 발행 : 2024.10.30

초록

Billions of the objects around us are transformed to the IoT device by connecting them with the internet and control in that way of collecting and sharing data. Privacy is required to keep the data save from the security attacks in internet of things. Computer vision is used for monitoring the people. Computer vision algorithms, application and tools are primarily used in IOT for human movement's analysis. Traditional system and algorithms are unable to detect the human in a perfect manner. Use of the thermal camera is degraded the movements of human detection. In this paper we propose a new IoT system that is combined with the latest feature of computer vision to detect the position using computer vision. It is a useful technology that helps to keep an eye on your house and office. It will alert you if anybody enters your home or office and do any harm at your place. For that purpose, the credit card size Raspberry PI card will be used. Histogram of oriented gradient (HOG) algorithm is used to detect the person in the image.

키워드

참고문헌

  1. Ilhan Aydin, N. A. (19 March 2018). A new IoT combined body detection of people by using computer vision for security application. International Conference on Computational Intelligence and Communication Networks (CICN), 20-24. 
  2. Othman, N. A., & Aydin, I. (2017, September). A new IoT combined body detection of people by using computer vision for security application. In Computational Intelligence and Communication Networks (CICN), 2017 9th International Conference on (pp. 108-112). IEEE. 
  3. Sathe, I., Patel, C., Mahajan, P., Telang, T., & Shah, S. (2017). Automatic Locking Door Using Face Recognition. 
  4. K. Sage, S. Y. (1998). Computer vision for security applications. Proceedings IEEE 32nd Annual 1998 International Carnahan Conference on Security Technology (Cat. No.98CH36209), 210 - 215. 
  5. Lakshmi Boppana, S. B. (2016). IoT based smart security and home automation system. IEEE (pp. 1286 - 1289). Noida, India: IEEE. 
  6. M. Zubal, T. L. (2016). IoT gateway and industrial safety with computer vision. 2016 IEEE 14th International Symposium on Applied Machine Intelligence and Informatics (SAMI), 183 - 186. 
  7. Sachchidanand Singh, N. S. (2015). Internet of Things (IoT): Security challenges, business opportunities & reference architecture for E-commerce. 2015 International Conference on Green Computing and Internet of Things (ICGCIoT) (pp. 1577 - 1581). Noida, India: IEEE. 
  8. https://www.learnopencv.com/histogram-of-oriented-gradients/ 
  9. https://www.google.com/search?q=computer+vision+process&hl=st&source=lnms&tbm=isch&sa=X&ved=0ahUKEwj_hOuEkonkAhVKx4UKHQiHCGwQ_AUIESgB&biw=1138&bih=536#imgrc=oA49CHBdmD10ZM:&spf=1566018635398 
  10. Shutao Zhao, B. L. (2005). Research on Remote Meter Automatic Reading Based on Computer Vision. 2005 IEEE/PES Transmission & Distribution Conference & Exposition: Asia and Pacific, 1 - 4. 
  11. Zhang, B. (2010, July). Computer vision vs. human vision. In Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on (pp. 3-3). IEEE. 
  12. Tan, Z., Jamdagni, A., He, X., Nanda, P., Liu, R.P., & Hu, J. (2015). Detection of Denial-of-Service Attacks Based on Computer Vision Techniques. IEEE Transactions on Computers, 2519 - 2533. 
  13. Kodali, R. K., Jain, V., Bose, S., & Boppana, L. (2016, April). IoT based smart security and home automation system. In Computing, Communication and Automation (ICCCA), 2016 International Conference on (pp. 1286-1289). IEEE. 
  14. Tom Loten, R. G. (2008). Embedded computer vision framework on a multimedia processor. 2008 23rd International Conference Image and Vision Computing New Zealand, 1 - 5.