In today’s world, security is the biggest concern for everyone whether it be office, home, industry, or any other application and so the highest priority. Access control is one of the most identified security measures used in many applications for verification of the authorized person and monitoring his/her activities. There are various systems for this, but after recognizing the authorized person, opening the door automatically, which will be helpful in some scenarios like elderly people, accessing the locker system of a bank, and human independent systems, is useful in many systems. This work gives complete access to the owner with three levels of access control. Access to the system will be checked at the entrance, and the owner will be intimated. With the help of histogram of oriented gradients (HOG), face recognition algorithm, RFID, and one-time passcode on registered email id, an intruder-free security system can be achieved. The work comprises solenoid lock replacing the stereotypical method to open the door automatically. The owner can control the system from anywhere around the globe as alerts will be sent for intruder detection. With increasing concern of security in every domain, this system can provide the security solution to all types of threats. 

Three-Level Access Control System for Digital Door Lock

Abstract: Security is one of the major challenges faced by individuals, organizations, and the world at large. The evolution of technology assists in solving this menace of insecurity and with the continuous growth in technology; several techniques have been used in tackling this problem of insecurity, starting from traditional systems like the door locks with handles to automated doors. In recent times, most of these doors lock security systems are based on microcontrollers, GSM, GPS, sensors, biometrics like eye scanner, fingerprint, face recognition, password, etc., and each of these techniques has its advantages and disadvantages. The developed system involves the design of a prototype door access control system that will control the access of personnel to a location/office using voice recognition and Radio Frequency Identification (RFID) authentication techniques. The system at first detects the movement of a person and prompts the person for verification. If verified either by voice or by RFID, the door automatically opens and closes after 5 seconds. The aim of this developed system is to restrict the access of an office/location using Radio Frequency Identification and voice recognition authentication, thus offering security to the lives and properties of people. Keywords: Biometrics, Radio Frequency Identification (RFID), LCD, Arduino, GPS, GSM

/pdf/door-access-control-using-rfid-and-voice-recognition-system-3pksw095.pdf

Door Access Control Using RFID and Voice Recognition System

This paper addresses the issues of traditional authentication methods, such as the use of passwords, which often prove to be unreliable due to various vulnerabilities. The main drawbacks of these methods include the loss or theft of passwords, their weak resistance to various types of attacks, and the complexity of password management, especially in large systems. Biometric authentication methods, particularly those based on physical characteristics such as voice, present a promising alternative as they offer a higher level of security and user convenience. Biometric authentication systems have advantages over traditional methods because the voice is a unique characteristic for each person, making it substantially more challenging to forge or steal. However, there are challenges regarding the accuracy and reliability of such systems. Specifically, voice biometric systems can encounter issues related to changes in voice due to health, emotional state, or the surrounding environment. The primary objective of this paper is to compare contemporary deep learning models with traditional digital signal processing methods used for speaker recognition. For this study, text-dependent methods (Mel-Frequency Cepstral Coefficients — MFCC, Linear Predictive Coding — LPC) and text-independent methods (ECAPA-TDNN - Emphasized Channel Attention, Propagation and Aggregation in Time Delay Neural Network, ResNet - Residual Neural Network) were selected to compare their effectiveness in voice biometric authentication tasks. The experiment involved implementing biometric authentication systems based on each of the described methods and evaluating their performance on a specially collected dataset. Additionally, the paper provides a detailed examination of audio signal preprocessing methods used in voice authentication systems to ensure optimal performance in speaker recognition tasks, including noise reduction using spectral subtraction, energy normalization, enhancement filtering, framing, and windowing. 

Comparison of digital signal processing methods and deep learning models in voice authentication

/pdf/voice-recognition-system-for-door-access-control-using-uoqtjvj6rz.pdf

Voice Recognition System for Door Access Control Using Mobile Phone

/pdf/design-and-construction-of-speech-controlled-door-5758a2f3zt.pdf

Design and Construction of Speech Controlled Door

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Adegbola Oluwole Abiodun

Author Tools

Chat about Author

Papers

Voice Recognition System for Door Access Control Using Mobile Phone

Design and Construction of Speech Controlled Door