A sophisticated apartment safety system aimed at preventing unauthorized access and enhancing security within residential complexes. The system employs facial recognition technology to identify residents and regular visitors while capturing the pictures and data of unknown individuals upon entry. These individuals are provided with an RFID tag, enabling continuous tracking of their movement within the premises until they reach their intended destination so that we can monitor the person and keep checking if they are using the granted permission another way. A real-time notification is also sent to the resident or office where the visitor is headed, ensuring timely awareness and response. The visitor photograph along with details are sent so that they can take up the decision to allow them or not. For the daily visitors and residents, we will have another database to recognize the permission and grant them access without much trouble. The same can be implemented for vehicles as well. The system categorizes users by issuing distinct tags for residents, regular visitors, and daily workers, facilitating efficient monitoring and management. By integrating these features, the proposed system significantly improves security protocols, minimizing the risk of mishaps and ensuring a safe living environment for all residents without much hassle.

Keywords:RFID, photograph, security systems, protocols, image detection

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1. Qadri MT, Asif M. Automatic number plate recognition system for vehicle identification using optical character recognition. In 2009 International Conference on Education Technology and Computer; 2009 Apr 17. pp. 335–8. IEEE.
2. Boxey A, Jadhav A, Gade P, Ghanti P, Mulani AO. Face Recognition using Raspberry Pi. Journal of Image Processing and Intelligent Remote Sensing (JIPIRS) ISSN. 2022:2815-0953.
3. Sanath K, Meenakshi K, Rajan M, Balamurugan V, Harikumar ME. RFID and face recognition based smart attendance system. In2021 5th International Conference on Computing Methodologies and Communication (ICCMC); 2021 Apr 8. pp. 492–9. IEEE.
4. Xiong TW, Liu JJ, Yang YQ, Tan X, Min H. Design and implementation of a passive UHF RFID-based real time location system. In: Proceedings of 2010 International Symposium on VLSI Design, Automation and Test; 2010 Apr 26. pp. 95–98. IEEE.
5. Kurundkar S, Bhole G, Bele S, Bhoge B, Bhosale A. Advance Security System. In: 2023 IEEE 8th International Conference for Convergence in Technology (I2CT); 2023 Apr 7. pp. 1–4. IEEE.
6. Patil SK, Dr Narendra GN. Achieving Advance Security System over Raspberry Pi Controlled via Android Application. International Journal of Scientific Research in Science and Technology (IJSRST), Print ISSN. 2018:2395-6011.
7. Raptopoulos A, Yioultsis T, Dimitriou AG. Particle filter object tracking by a handheld UHF RFID reader. In2019 IEEE International Conference on RFID Technology and Applications (RFID-TA); 2019 Sep 25. pp. 342–7. IEEE.
8. Bah SM, Ming F. An improved face recognition algorithm and its application in attendance management system. Array. 2020 Mar 1;5:100014.
9. Kim I, Lee B, Kim H. Privacy protection based on user-defined preferences in RFID system. In2006 8th International Conference Advanced Communication Technology; 2006 Feb 20:(1):858–63. IEEE.
10. Kim DS, Shin TH, Park JS. A security framework in RFID multi-domain system. In: The Second International Conference on Availability, Reliability and Security (ARES’07); 2007 Apr 10. pp. 1227–1234. IEEE.
11. Nikita, Kashyap L, Singh BP, Tyagi D. AI enabled advance surveillance system. Int Res J Modernization Eng Technol Sci. 2023;5(4). DOI: https://www.doi.org/10.56726/IRJMETS37500.
12. Peña A, Morales A, Serna I, Fierrez J, Lapedriza A. Facial expressions as a vulnerability in face recognition. In: 2021 IEEE International Conference on Image Processing (ICIP); 2021 Sep 19. pp. 2988–92. IEEE.
13. Tushar NI, Saikat A, Rahat-Bin-Rafique AA, Abedin MM, Tahmiduzzaman KB, Zumma MT. Vehicle Number Plate Detection System Using Image Processing Approach. In: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT); 2023 Jul 6. pp. 1–5. IEEE.

A sophisticated apartment safety system aimed at preventing unauthorized access and enhancing security within residential complexes. The system employs facial recognition technology to identify residents and regular visitors while capturing the pictures and data of unknown individuals upon entry. These individuals are provided with an RFID tag, enabling continuous tracking of their movement within the premises until they reach their intended destination so that we can monitor the person and keep checking if they are using the granted permission another way. A real-time notification is also sent to the resident or office where the visitor is headed, ensuring timely awareness and response. The visitor photograph along with details are sent so that they can take up the decision to allow them or not. For the daily visitors and residents, we will have another database to recognize the permission and grant them access without much trouble. The same can be implemented for vehicles as well. The system categorizes users by issuing distinct tags for residents, regular visitors, and daily workers, facilitating efficient monitoring and management. By integrating these features, the proposed system significantly improves security protocols, minimizing the risk of mishaps and ensuring a safe living environment for all residents without much hassle.

Keywords:RFID, photograph, security systems, protocols, image detection

🔒 This is a subscription article

Full text is available to subscribers and institutional members. Please choose an option below to access it.

1. Qadri MT, Asif M. Automatic number plate recognition system for vehicle identification using optical character recognition. In 2009 International Conference on Education Technology and Computer; 2009 Apr 17. pp. 335–8. IEEE.
2. Boxey A, Jadhav A, Gade P, Ghanti P, Mulani AO. Face Recognition using Raspberry Pi. Journal of Image Processing and Intelligent Remote Sensing (JIPIRS) ISSN. 2022:2815-0953.
3. Sanath K, Meenakshi K, Rajan M, Balamurugan V, Harikumar ME. RFID and face recognition based smart attendance system. In2021 5th International Conference on Computing Methodologies and Communication (ICCMC); 2021 Apr 8. pp. 492–9. IEEE.
4. Xiong TW, Liu JJ, Yang YQ, Tan X, Min H. Design and implementation of a passive UHF RFID-based real time location system. In: Proceedings of 2010 International Symposium on VLSI Design, Automation and Test; 2010 Apr 26. pp. 95–98. IEEE.
5. Kurundkar S, Bhole G, Bele S, Bhoge B, Bhosale A. Advance Security System. In: 2023 IEEE 8th International Conference for Convergence in Technology (I2CT); 2023 Apr 7. pp. 1–4. IEEE.
6. Patil SK, Dr Narendra GN. Achieving Advance Security System over Raspberry Pi Controlled via Android Application. International Journal of Scientific Research in Science and Technology (IJSRST), Print ISSN. 2018:2395-6011.
7. Raptopoulos A, Yioultsis T, Dimitriou AG. Particle filter object tracking by a handheld UHF RFID reader. In2019 IEEE International Conference on RFID Technology and Applications (RFID-TA); 2019 Sep 25. pp. 342–7. IEEE.
8. Bah SM, Ming F. An improved face recognition algorithm and its application in attendance management system. Array. 2020 Mar 1;5:100014.
9. Kim I, Lee B, Kim H. Privacy protection based on user-defined preferences in RFID system. In2006 8th International Conference Advanced Communication Technology; 2006 Feb 20:(1):858–63. IEEE.
10. Kim DS, Shin TH, Park JS. A security framework in RFID multi-domain system. In: The Second International Conference on Availability, Reliability and Security (ARES’07); 2007 Apr 10. pp. 1227–1234. IEEE.
11. Nikita, Kashyap L, Singh BP, Tyagi D. AI enabled advance surveillance system. Int Res J Modernization Eng Technol Sci. 2023;5(4). DOI: https://www.doi.org/10.56726/IRJMETS37500.
12. Peña A, Morales A, Serna I, Fierrez J, Lapedriza A. Facial expressions as a vulnerability in face recognition. In: 2021 IEEE International Conference on Image Processing (ICIP); 2021 Sep 19. pp. 2988–92. IEEE.
13. Tushar NI, Saikat A, Rahat-Bin-Rafique AA, Abedin MM, Tahmiduzzaman KB, Zumma MT. Vehicle Number Plate Detection System Using Image Processing Approach. In: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT); 2023 Jul 6. pp. 1–5. IEEE.