Open Access
Issue
E3S Web of Conf.
Volume 507, 2024
International Conference on Futuristic Trends in Engineering, Science & Technology (ICFTEST-2024)
Article Number 01019
Number of page(s) 10
DOI https://doi.org/10.1051/e3sconf/202450701019
Published online 29 March 2024
  1. P. Vamsikrishna, S. R. Hussain, N. Ramu, P. M. Rao, G. Rohan and B. D. S. Teja, “Advanced Raspberry Pi Surveillance (ARS) system”, 2015 Global Conference on Communication Technologies (GCCT), Thuckalay, India, 2015, pp. 860–862, DOI: 10.1109/GCCT.2015.7342784. [Google Scholar]
  2. D. Pavithra; Ranjith Balakrishnan, “IOT based monitoring and control system for home automation”, IEEE Explore, Communication Technologies (GCCT), 2015 Global Conference on Communication Technologies (GCCT), Thuckalay, India, 2015, pp. 169–173, DOI: 10.1109/GCCT.2015.7342646. [Google Scholar]
  3. S. Ramyasri, M. Mahalakshmi, “ IOT Based Progressive Anti Theft ATM Security System”, 2020 IOP Conference Series: Materials Science and Engineering 981 042095, DOI: 10.1088/1757-899X/981/4/042095 [Google Scholar]
  4. Manjunath M, Venkatesha G, Dinesh S, Raspberry Pi Based Anti-Theft Security System using Home Automation for Multi-Level Authentication, (PiCES) – An International Journal, vol. 4, no. 10, pp. 249 – 253, 2021. DOI: https://doi.org/10.5281/zenodo.4515527 [Google Scholar]
  5. Mamun, Kabir A. and Zahir Ashraf. “Anti-theft vehicle security system with preventive action.” 2015 2nd Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE) (2015): pp. 1–6, DOI: 10.1109/APWCCSE.2015.7476241. [Google Scholar]
  6. Asaad. S. Daghal, Ali Fadhel Athab, “Anti-theft security hidden alert system based on IoT”,AIP Conference proceedings 2404, 030006 (2021), DOI: https://doi.org/10.1063/5.0068890 [Google Scholar]
  7. Dr. M. Suresh, A. Amulya, M. Hari Chandana, P. Amani, T. Lakshmi Prasanna. “Anti-Theft Flooring System Using Raspberry PI Using IOT System”. Compliance Engineering Journal 2021, pp. 1759–1764, DOI: https://www.doi.org/10.56726/IRJMETS33793 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.