Fingerprint Sensor Research Articles

Biometric based Fingerprint Identification for Bank Locker Security System

tract: This paper presents the human detection and recognition field is very significant and has undergone rapid changes with time. An important and very reliable human identification method is fingerprint identification. Fingerprint of every person is unique. So, this helps in identifying a person or improving security of a system. Finger print of a person is read by a special type of sensor. Finger print sensor can be interfaced with a microcontroller. Through fingerprint we can add new user and delete the existing user. In this project we use a fingerprint sensor to read one’s identity to automatically operate the door of the locker. For this, we use a microcontroller to enable the door opening or closing if the matching between scanned data and the already existing data is correct. Comparison is done inside the fingerprint module itself and its output is given to microcontroller. Result is displayed in an LCD display whether the user is authorized or not. The aim of our project is to design finger print based bank locker security system, which uses candidate’s fingerprint to decide the authenticity of candidate.

System of Biometric Approach for Metro Ticket Expenses Using Finger Print Recognition

Abstract: This paper based on automated system for ticketing in the Metro Train System which is based on unique passenger identification. This is a user friendly system, which will automatically identify the passenger and deduct the passenger’s fare according to the distance travelled. Transportation plays a vital role in ones life. The main goal of this paper is to eradicate the day to day and one of the major problems with regard to carrying a ticket during transportation from ones life and make traveling a lot more peaceful. For this purpose, we are proposing a biometric-based ticketing system in the metro railway scenario but not limited to the same. In order to get a unique identifier for each person, we are considering their fingerprint right away from registration, booking tickets and validating the fingerprint on the day of the journey so he/she can travel on a particular day and on the desired train to his/her preferred destination. The fingerprint sensor will be interfaced with Arduino which in turn will store the fingerprint data to the cloud. We are proposing a two-way encryption standard for storing the sensitive fingerprint data in the cloud. This two-way encryption standard involves encrypting the data during data generation at the hardware end and encrypting it again before storing it in the cloud database.

Design of Women Safety Device with Fingerprint Sensor

bstract: The safety of women has always been a global concern, and despite various measures adopted, the number of cases of misconduct against women is steadily rising. To address this issue, a new approach in the form of a device has been proposed. The purpose of this gadget is to give women a tool to safeguard their security and safety in the incident of an accident. To ensure that no woman feels helpless in the face of such crime issues, defense mechanisms must be proposed in large-scale productions. The suggested gadget is an embedded system designed on an Arduino board and a NodeMCU module with GPS that delivers a warning sound will be heard in the event of danger and an emergency message is sent with the user's location. To safeguard women's safety, this technology follows the location and transmits a message to the police control room, family, and friends. Moreover, a fingerprint module built into the system makes sure that only authorized users are utilizing the equipment. The smartphone will deem it dangerous and automatically send an SMS to the appropriate authority if the user does not touch their fingertips on the module that stores fingerprints within a predetermined amount of time. In conclusion, the proposed device could be a valuable tool in ensuring the safety and security of women. With the integration of technology, this device could provide a sense of security to women and help prevent crimes against them.

Development of a Parking System Using the High Sensitive R503 Fingerprint Sensor for Sequential Search Algorithm Based Customer Detection

Today's technological developments are very sophisticated. It can be seen with various innovations in this era, from simple innovations to innovations that are trending in the world. Parking is a condition where the driver places his vehicle in a parking lot. The parking system using the Radio Frequency Identification (RFID) system has become a technology applied to parking systems, by facilitating and providing security to customers when parking, even though they have used an RFID card, the drawbacks of the system are that anyone who has an RFID card can issue the owner's vehicle another by using the same RFID card. The solution to the lack of an RFID-based parking system is by using the High Sensitive R503 Fingerprint Sensor which will make security much better than using an RFID card, by applying the Sequential Search Algorithm to detect customers in fingerprint registration applications and using the Fingerprint R503 sensor with data verification speed. average 0.78 Second to open the parking portal.

APPLICATIONS OF MULTIMODAL BIOMETRICS AUTHENTICATION FOR ENHANCING THE IOT SECURITY USING DEEP LEARNING

The Internet of Things (IoT) integrates billions of electronic devices into computer networks to provide advanced and intelligent services that enable devices to communicate with each other by exchanging information with minimal human interaction. The security issue is at higher risk in IoT systems than in other computing systems. Maintaining the security requirement when attacking the physical surface of the IoT system device is a challenging task. Implementing security mechanisms like authentication and access control for the IoT ecosystem is necessarily needed to ensure the security of IoT devices. The key used for security may be stolen, forgotten, or forged. Also, the key may be generated by intruders or men in the middle of traditional security mechanisms. Biometric security is becoming more advanced and sophisticated with technological advancements and is mostly used in authentication systems. In unimodal biometrics, only one biometrics character can be applied which does not apply to ensure the security of IoT systems. In this paper, Multimodal biometrics authentication was used for securing edge devices in the IoT ecosystems. Face image and fingerprint image were used as multimodal biometrics systems for authenticating users to secured IoT devices. A pi-camera module and fingerprint sensor were used to capture biometric data. Image processing techniques were then applied to the images. Then CNN algorithms were used for feature extraction and model creation. During model creation, the RELU function was used as an activation function, soft-max for image classification, and Max-pooling for image dimensional reduction which helped the model speed up the training process. Experimental results show that the accuracy of the face image and fingerprint image is 92% and 89% respectively, which is a promising result that achieves the objective of the study.
 Keywords: Internet of Things, Multimodal Biometrics, Authentication, CNN, Deep Learning

Identification of geographical origins of Astragalus membranaceus in China using electrochemical fingerprinting

Astragalus membranaceus quality differs across different geographical locations. The electrochemical fingerprint technique is a detection technology that captures the electrochemical activity of a sample. The electrochemical fingerprint feature represents each sample, and can collect information about the electrochemical active components in traditional Chinese medicine, which can be used to distinguish between different medicinal materials and verify their authenticity. In this study, electrochemical fingerprinting was used to collect data from three different geographical locations of Astragalus membranaceus. We employed differential pulse voltammetry (DPV) to establish an electrochemical fingerprint of Astragalus membranaceus, reflecting the proportional content of various components. Ten potential markers were selected from the collected data for similarity calculations. Additionally, the original fingerprint data was used for cluster analysis and heatmap construction. The results demonstrate the potential of electrochemical fingerprinting as a technique for identifying the origin of traditional Chinese medicinal materials. This study explored the feasibility of using electrochemical fingerprint sensors for identifying the origin of the same medicinal material from different geographical locations.

A Stress Test for Robustness of Photo Response Nonuniformity (Camera Sensor Fingerprint) Identification on Smartphones

In the field of forensic imaging, it is important to be able to extract a camera fingerprint from one or a small set of images known to have been taken by the same camera (or image sensor). Note that we are using the word fingerprint because it is a piece of information extracted from images that can be used to identify an individual source camera. This technique is very important for certain security and digital forensic situations. Camera fingerprint is based on a certain kind of random noise present in all image sensors that is due to manufacturing imperfections and is, thus, unique and impossible to avoid. Photo response nonuniformity (PRNU) has become the most widely used method for source camera identification (SCI). In this paper, a set of attacks is designed and applied to a PRNU-based SCI system, and the success of each method is systematically assessed both in the case of still images and in the case of video. An attack method is defined as any processing that minimally alters image quality and is designed to fool PRNU detectors or, in general, any camera fingerprint detector. The success of an attack is assessed as the increment in the error rate of the SCI system. The PRNU-based SCI system was taken from an outstanding reference that is publicly available. Among the results of this work, the following are remarkable: the use of a systematic and extensive procedure to test SCI methods, very thorough testing of PRNU with more than 2000 test images, and the finding of some very effective attacks on PRNU-based SCI.

IoT and AI Based Student’s Attendance Monitoring System to Mitigate the Dropout in Non-boarding Secondary Schools of Rwanda: A Case Study of Wisdom School Musanze

Purpose: This project aimed to test an IoT and AI based system that monitor students from home to schools, during class hours and from school to home and notify parents and school administrators about the irregularity observed to their respective children.
 Methodology: In this project, secondary data was used and was retrieved from the school’s record of Wisdom School Musanze located in Musanze District. The main data to consider were sex whether male or female. Another important data was orphanage,whether pupil is orphan or not orphan, and school fees payment by checking whether student paid school fees or had not paid. These mentioned data were taken randomly from senior one (S1) to senior six (S6) in academic year 2020-2021.
 Findings: The system is equipped of a finger print sensor to register and verify students and staff attendance, a Passive Infrared (PIR) sensor to detect the presence of human to wake-up the device, a real time clock to synchronize each generated report with the local time. A web application is developed to allow students real-time monitoring for parents and school administrators and the system is be able to generate a daily, monthly and annually report. 
 Unique contribution to theory, practice and policy: Classification machine learning with decision-tree algorithm is used to analyze data and generate a model to evaluate the impact of monitoring attendance on preventing students to dropout. The generated model with accuracy of 91.4% shows that keeping students’ attendance at high percentage would reduce significantly the dropout rate in secondary schools of Rwanda. 

From Attack to Identification: MEMS Sensor Fingerprinting Using Acoustic Signals

A device pretending to be behaving normally can carry out malicious acts that result in the leakage of sensitive information, invasion of privacy, damage property, or even loss of life. The first step to detect these malicious acts is to identify whether a device is authorized or not. There are existing methods for identifying devices based on cryptographic schemes or physical unclonable function (PUF), but each of these methods has disadvantages in that key management costs are incurred or additional chips or circuits are required. In this article, we propose a device identification method that overcomes these shortcomings. Based on the fact that MEMS sensors are built-in to most devices due to their various applications and the property that MEMS sensors are sensitive to acoustic signals with resonant frequencies, the proposed method uses MEMS sensor readings to acoustic signals. Many attack methods have been studied using this property to disable the normal function of the sensor or eavesdrop on speech around a device. On the other hand, our method is the first to fingerprint MEMS sensors using raw sensor readings to acoustic signals from a security point of view rather than from this conventional attack point of view. Furthermore, our method is based on a challenge-response structure to be secure from replay attacks; here, a challenge is a random acoustic signal, and a response is the unique MEMS sensor reading to the challenge. In our evaluation, we use commercial MEMS sensors and a low-cost speaker that costs less than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\$ $ </tex-math></inline-formula> 1. The results show that under various conditions that may affect MEMS sensor readings, the macro F1-scores when identifying authorized devices is 1.0, and the macro accuracy of detecting attacks using devices other than authorized ones is 0.994. As a result, our method can identify devices well at a low cost.

VEHICLE STARTER SYSTEM FOR SAFETY BASED MICROCONTROLLER USING INTERNET OF THINGS

Technology is currently growing very fast which affects and has a significant purpose in human life. In the current era, the technology of the security system is something that is very necessary. The high crime rate has now reached an alarming stage. Motorcycles currently only use conventional ignition keys to turn them on to improve the vehicle's security system, so a vehicle security system with a microcontroller connected to an Internet of Things-based fingerprint sensor is needed to improve the vehicle's security system. Research shows that a motorcycle security system with a microcontroller is connected to a fingerprint sensor based on the Internet of Things, namely turning on and turning off the vehicle with fingerprints owned or via the internet of things using the telegram application for remote and realtime systems. The way the results of this study work is when the first finger taps on the fingerprint sensor on the registered finger, the motor will turn on, then the second finger taps on the fingerprint sensor, the motor will die, for remote systems, namely using telegram bots, the prefix is to enter chat instructions on the telegram bot if the telegram bot replies to the instruction then the motor will follow according to the instruction on or off and if the instruction is wrong then the telegram bot will tell that the instruction is wrong. The results of this study show that when adding fingerprints it has a delay of 1.74s, removing fingerprints is 0.24s and the IoT system itself is 90% successful.

High Step-Up Ratio DC-AC Converter Using Fourth-Order LCLC Resonant Circuit for Ultrasonic Fingerprint-Sensor Drivers

Ultrasonic fingerprint sensors are becoming more widely used in thick or flexible displays. In order to better identify fingerprint information, ultrasonic sensors need to generate more ultrasonic energy, which can be transmitted to the display surface through media with higher acoustic impedance. In this paper, a DC-AC converter with a high lift ratio was proposed to enhance the transmission energy of the ultrasonic fingerprint sensor, thus helping to improve the identification. The converter comprises a full-bridge inverter and two LC resonant circuits. The introduction of an additional LC resonant circuit into the traditional Class-D LC resonant converter effectively increases the boost ratio of the proposed converter from 5 to 22. When used as a part of the ultrasonic fingerprint sensing system, the proposed converter can amplify the 20-V low-voltage DC required to drive the piezoelectric organic film to 376 V high-voltage AC. The voltage of the wave received from this new driver is equal to 970 mV, which greatly exceeds the 376 mV achieved by using the Class-D converter alone. In this paper, the topology proposed by the ultrasonic fingerprint sensor converter driver was experimentally verified, which greatly improved the boost ratio and can be considered suitable for wider applications.

Implementation security system using motorcycle fingerprint identification and notification Telegram

A motorcycle security system using fingerprint recognition and Telegram notification is a solution to solve motorcycle safety problems and reduce motorcycle loss cases by using fingerprint sensors attached to the owner’s motorcycle and Telegram application as a monitor connected to the motorcycle. The microcontroller used is the Wemos D1 mini connected to the Telegram application as a communication line between the user and the motorcycle. The sensor used is the fingerprint sensor. There are differences in data obtained from the fingerprint sensor response results and the response of the Telegram notification system by testing fingerprints that have been registered and that are not registered on the fingerprint sensor with the measurement results using the stopwatch. Measurement differences on the fingerprint sensor have errors with an average time dispute of 0.27 seconds. Measurement differences in Telegram notifications have errors with an average dispute time of 1 second. Hygiene conditions on the fingerprint sensor influence the difference in reading duration. If there is fingerprint oil before it, then the reading tends to be slow. The difference in measurements obtained is small enough that it can be used as a reference.

Inpatient WiFi-enabled medication dispenser for improving ward-based clinical pharmacy services

Medications are vital for patients and especially for those who are receiving treatment in hospitals. Providing medications for these people is essential to maintain their health. On the other hand, medication dispensing error is one of the most common challenges that face clinical pharmacists and medical staff. These errors frequently occurred due to poor medication systems and/or human factors (i.e. environmental conditions, fatigue or staff shortage). These factors may affect prescribing, transcribing, administration, dispensing and monitoring practices which can result in disability, severe harm and even death. Avoiding medication dispensing errors is the key motivation of this paper. Consequently, a biometric-based dispensing system has been designed and implemented. The system can be installed at hospital wards and used for delivering and monitoring inpatients doses. It consists of three parts; hardware, software and mechanical part. Three 4-phase stepper motors are used for controlling the mechanical part of this system. An optical fingerprint sensor is used which is compatible with the ESP32 low-power SoC for scanning patients’ fingerprints to recognize and store their data. The system directly updates its database whenever is used by the inpatients, so that nobody can get additional doses. This system is cost-effective, reliable and easy to use.

SISTEM KEAMANAN PENYIMPANAN SURAT PENTING BERBASIS FINGER PRINT

Administrative work in an institution is inseparable from correspondence. Correspondence documents will then be stored as archives. Storage of important letters requires a storage area with a secure level of security, one of which is using a safety deposit box. The security system is one of the efforts to prevent theft or loss of an object. The security system on conventional storage cabinet doors is prone to file theft because it is easy to break into. Therefore, it is necessary to implement a safe deposit box security system that is safer and has today's technology in order to minimize the occurrence of security deposit box locks being stolen. One way is to use a fingerprint sensor to open a cupboard door, often known as security with a fingerprint. The fingerprint sensor connected to Arduino uno will record the user's registered fingerprint. Through the fingerprint data endroll process. Fingerprint function to open the safe cabinet door, after the finger is pasted on the Finger print sensor. The specialty of this system is that only fingerprints that have been endrolled can open the safe door. Through this system, it can minimize the crime of breaking into storage cabinets. The method used is a prototype so that the design of this system can be developed according to the size of the safe deposit box for important documents

Comparison of Battery Electric Power Consumption in a Fingerprint System or a Motor Manual Lock System

Motorcycle security systems using fingerprint sensors are needed to avoid theft because of their high level of security compared to manual systems. This study underscores the importance of using this fingerprint sensor for motorcycle security. The formulation of the problem in this study is how much electricity is required in the motorcycle battery for this fingerprint security system. This system uses various components, such as the R503 fingerprint sensor, Arduino Uno, buzzer, 4-channel relay, ignition key, and motorcycle starter. Testing of this system is performed by inserting a finger in a wet, oily, dusty, or normal condition, and the result is that this sensor is capable of detecting the entire condition of the finger. Attempts to start a motorcycle with all ten fingers showed that the left index finger started faster under normal conditions, in 1.55 seconds compared to the manual method, which took 2.05 seconds longer. It also measures power consumption and calculates how long the battery can power this device. The result is that the battery can power this device for 180 hours without interruption

Medibot for Emergency Vehicle

To create a medical robot that would be installed in an ambulance and use IoT to observe and communicate so that the patient might receive care before being brought to the hospital. In the case of a mishap, installing a finger print sensor will enable the hospital emergency room, police station, and the patient’s guardian to be informed of the unfamiliar patient’s bio-data. There are still significant problems with overpopulation and health-related illiteracy in India, and an accident-related mortality happens every minute. To build a clever smart health system, a MediBoT made up of sensors and microcontrollers is intended. It will assess the body’s condition and send information to the IoT.

Real Time Implementation of Biometric-based EVM System for Distinct Verification

In current existences, many techniques have been developed to cast votes. The existing scenario is tremendously aiming towards the development of an efficient voting system, which ensures individual authentication and reduces malpractices. It is a challenging perspective to recognize each and every individual person casting the vote. The proposed work considers this scenario and developed a controller based electronic voting machine using R305 Fingerprint sensor for biometric authentication of every individual. The controlled electronic voting machine gives ample scope to cast the votes in simpler manner without minimizing the efficient results. The proposed digital Biometric-based EVM is presented in this work. The processed flow for creating this biometric based EVM is implemented on FPGA board using Verilog software on Xilinx ISE. The experimental results produce efficient verification of unique authentication on selections of political parties.

Effect of Smaller Fingerprint Sensors on the Security of Fingerprint Authentication

Effect of Smaller Fingerprint Sensors on the Security of Fingerprint Authentication

A 1.05-A/m Minimum Magnetic Field Strength Single-Chip, Fully Integrated Biometric Smart Card SoC Achieving 792.5-ms Transaction Time With Anti-Spoofing Fingerprint Authentication

A single-chip, fully integrated biometric authentication smart card system-on-a-chip (SoC) has been developed that integrates an analog front-end for fingerprint sensors (FPSs), a high-speed processor dedicated to fingerprint information processing, and a dual-interface smart card system with a secure element. The chip is mounted on a cost-effective single package with a capacitive FPS and a few external capacitors. The implemented biometric smart card system shows a total processing time of 792.5 ms including anti-spoofing fingerprint authentication at a magnetic field strength of 1.05 A/m.

Advanced optical terahertz fingerprint sensor based on coherent perfect absorption.

An advanced optical terahertz (THz) fingerprint sensor based on coherent perfect absorption (CPA) is proposed. Based on a one-dimensional layered photonic structure, the sensor contains a cavity that is developed for THz fingerprint measurement. Utilizing the magneto-optical effect of magnetized InSb, CPA is excited in the structure of the sensor. Taking α-lactose as exemplar material, this numerical simulation is integrated with a Drude-Lorentz model. The transfer matrix method (TMM) is used to calculate the sensitivity (S), linear range (LR), quality (Q), the figure of merit (FOM*), and detection limit (DL) theoretically. Employing the amplitude modulation detection method, the qualitative and quantitative analysis of the α-lactose thickness of 0-0.5 μm could be realized. Because of the fragility of CPA, the S is 0.78255 μm-1, the value of average Q is up to 8019.2, the value of average FOM* is 13 234.4 (THz μm)-1, and the lower DL is 4.21 × 10-6. Moreover, the evolutions of ensemble-averaged absorption in the vicinity of the absorption peaks for different types of disorder effects are considered, which will be considered in the fabrication of sensors.