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[email protected] +91 9840521421 Scholarly Open Access, Peer-reviewed, Refereed Journal E-ISSN 3048-6408 Since 2024
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Research Article

Intruder Detection System Using Doppler Sensors and IoT Technology: A Secure and Efficient Approach

  • Paper ID 12
  • Volume 1, Issue 2
  • Pages: 15-17
  • Published Online: May-August 2024
  • 324 Views
Open Access Peer Reviewed

Authors

  • R. Sunil Kumar1
  • Konka Srishailam2
  • Pinnoji Srujana3
  • Ashangari Rakesh4
  • Poloju Mahesh5

1 2 Department of EEE, Scient Institute of Technology, Hyderabad, Telangana, India. 3 4 5 Department of ECE, Scient Institute of Technology, Hyderabad, Telangana, India

Article Information

DOI
No Doi
Published Online
May-August 2024
Pages
15-17
Article Type
Research Article
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Abstract

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This manuscript introduces an innovative intruder detection system that combines Doppler sensors and Internet of Things (IoT technology to overcome the constraints of conventional systems. The suggested system exploits the superior precision and dependability of Doppler sensors for motion detection, while making use of the real-time monitoring and alert features of IoT technology. The architecture of the system comprises a module for Doppler sensor (RCWL-0516, a unit for processing (Arduino Board, a module for IoT (ESP8266, and a system for sound alerts. Motion is detected by the Doppler sensor, which then transmits a signal to the processing unit for determining the presence of an intruder. Upon intruder detection, the IoT module dispatches an alert to authorities through the internet, and the sound alert system notifies nearby individuals. The proposed system presents numerous benefits compared to current approaches, including enhanced detection precision, reduced false alarm occurrences, secure data transmission, and minimal power consumption. Evaluation results indicate high detection accuracy and limited false alarms. Furthermore, the system integrates robust security measures like data encryption and password protection to guarantee the integrity and confidentiality of transmitted data. Prospective improvements encompass the incorporation of machine learning algorithms for enhanced detection precision, extension of system capabilities for multi-zone detection, and the creation of a mobile application for remote monitoring. The suggested intruder detection system signifies a substantial advancement in surveillance technology, effectively tackling the deficiencies of existing systems and establishing a new benchmark for security infrastructure.

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  • ISSN 3048-6408
  • Open Access
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