Vision based Office Automation and Security System using Machine Learning and Internet of Things

  • Abstract
  • Keywords
  • References
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  • Abstract

    The paper focuses on two areas, automation and security. Raspberry Pi is the heart of the project and it is fuelled by Machine Learning Algorithms using Open CV and Internet of Things. Face recognition uses Linear Binary Pattern and if an unknown person uses their workstation, a message will be sent to the respective person with the photo of the person who uses the workstation. Face recognition is also being used for uploading attendance and switching ON and OFF appliances automatically. During un-official hours, A Human Detection algorithm is being used to detect the human presence. If an unknown person enters the office, a photo of the person will be taken and sent to the authorities. This technology is a combination of Computer Vision, Machine learning and Internet of things, that serves to be an efficient tool for both automation and security.



  • Keywords

    Facial Recognition; Histogram of Oriented Gradients; Human Detection; Linear Binary Pattern; Raspberry Pi; Support Vector Machine;.

  • References

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      [2] E.Varadharajan,R.Dharani, S.Jeevitha, B.Kavinmathi, S.Hemalatha “Automatic Attendance Management System Face Detection”, International Conference on Green Engineering and Technologies (IC-GET) 2017

      [3] Ishita Gupta, Varsha Patil, Chaitali Kadam, Shreya Dumbre “ Face Detection and Recognition using Raspberry Pi “ IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE) 2016

      [4] Bhaumik Vaidya, Ankit Patel, Anand Panchal “Smart home automation with a unique door monitoring system for old age people using Python, OpenCV, Android and Raspberry pi ” International Conference on Intelligent Computing and Control Systems (ICICCS) 2017

      [5] S.V. Manikanthan , T. Padmapriya “An enhanced distributed evolved node-b architecture in 5G tele-communications network” International Journal of Engineering & Technology (UAE), Vol 7 Issues No (2.8) (2018) 248-254.March2018

      [6] S.V. Manikanthan, T. Padmapriya, Relay Based Architecture For Energy Perceptive For Mobile Adhoc Networks, Advances and Applications in Mathematical Sciences, Volume 17, Issue 1, November 2017, Pages 165-179

      [7] S.V.Manikanthan and T.Padmapriya “Recent Trends In M2m Communications In 4g Networks And Evolution Towards 5g”, International Journal of Pure and Applied Mathematics, ISSN NO:1314-3395, Vol-115, Issue -8, Sep 2017.




Article ID: 11996
DOI: 10.14419/ijet.v7i2.24.11996

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