IoT Raspberry Pi Based Smart Parking System with Weighted K-Nearest Neighbours Approach

Due to the limited availability of parking slots in parking areas, drivers often have difficulty finding an empty parking slot. The number of parking slots available at a particular location is usually less than the number of vehicles. Hence, drivers spend a lot of time looking for vacant parking slots, which eventually delays the completion of their tasks, such as paying bills, attending a meeting, or visiting a patient at the hospital, etc. There are a couple of parking guidance systems that have been highlighted by the other researchers, but most of them lack real-time, convenient guidance. This research proposed a smart parking guidance system made of an IoT Raspberry Pi combined with an Android application that makes use of the weighted k nearest neighbours for positioning the vehicle. This was achieved through the use of Wi-Fi signal strength indicator fingerprinting, allowing for real-time navigation and parking detection. In order to achieve real-time parking over the internet, Raspberry Pi hardware and the ThingSpeak IoT cloud with ultrasonic sensors are used in the proposed method. An Android application was involved in this parking detection system, which adopted IoT approaches to estimate the location of users in real-time and provide routes using route-finding techniques to assist drivers in finding their desired parking slots. Data from the sensors was processed and translated into the Raspberry Pi using the Python programming language. They were sent using the Message Telemetry Transport protocol to send parking data to the ThingSpeak IoT cloud in real-time. This data was displayed via the Android app. The user is then able to view each available parking slot, acquire the route, and be directed with high accuracy to the parking slots of their choice. In this study, advanced sensing and communication technologies were used together with the weighted k nearest neighbours algorithm for positioning and wayfinding in order to improve parking guidance accuracy. Based on the experimental results, the proposed system showed a lower average error rate of 1.5 metres in comparison to other positioning techniques, such as GPS, or other similar algorithms for positioning, such as maximum a posteriori, which have shown average errors of 2.3 metres and 3.55 metres, respectively, a potential increase of more than 35% from the previous error rate. Doi: 10.28991/CEJ-2023-09-08-012 Full Text: PD

A hybrid-based modified adaptive fuzzy inference engine for pattern classification

The Neuro-Fuzzy hybridization scheme has become of research interest in pattern classification over the past decade. The present paper proposes a hybrid Modified Adaptive Fuzzy Inference Engine (MAFIE) for pattern classification. A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. A TSK type fuzzy inference system is constructed by the automatic generation of membership functions and rules by the hybrid fuzzy clustering and Apriori algorithm technique, respectively. The generated adaptive fuzzy inference engine is adjusted by the least-squares fit and a conjugate gradient descent algorithm towards better performance with a minimal set of rules. The proposed hybrid MAFIE is able to reduce the number of rules which increases exponentially when more input variables are involved. The performance of the proposed MAFIE is compared with other existing applications of pattern classification schemes using Fisher's Iris data set and shown to be very competitive

Glove-based Approach To Dynamic Signature Verification

The purpose of this research is to develop a novel, accurate and efficient on-line signature verification system

A Secured Fingerprint Authentication System

This study is a protection analysis of foremost privacy enhanced technologies for biometrics including watermark embedding technique and fixed digit encryption. A biometric authentication system is vulnerable to a mixture of attacks. These attacks are anticipated to either evade the security afforded by the system or to discourage the usual functioning of the system. Here, we briefly review some of the known attacks that can be encountered by a biometric system and some corresponding protection techniques. We explicitly focus on threats designed to extract information about the original biometric data of an individual from the stored data as well as the entire authentication system. We offer a biometric authentication scheme which uses two separate biometric features combined by watermark embedding with fixed digit encryption to obtain a non-unique identifier of the individual, in order to address security and privacy concerns. Moreover, we provide experimental results presenting the performance of the authentication system. In the client-server environment the transformed features and templates travel through insecure communication line like the internet or intranet. Our proposed technique causes security against eavesdropping and replay attacks on the internet or intranet, because the transmitted feature information and the templates are different every time

Webcam Based Fingerprint Authentication for Personal Identification System

In the networked world there are a huge number of systems that need biometric recognition, so at present it has become an important issue. For the personal identification various kinds of vision-based techniques have been proposed earlier. We present a novel one based on visual capturing of fingerprints using a webcam. Fingerprint image quality influences deeply the performance of fingerprint identification systems. This paper presents an improved authentication system using a low priced webcam as well as a preprocessing approach using gamma manipulation and gamma correction technique to adjust lightness and intensities of the fingerprint image due to enhance fingerprint image quality. We also implement and test our proposed approach using the FVC2004 database including the webcam database of 1200 fingerprint images which is obtained by proposed approach and compare the EER (Equal Error Rate), FRR (False Rejection Rate) and FAR (False Acceptance Rate) of each database. Experiment- al results show that our approach performs significantly improved and comparatively EER, FRR, FAR of the webcam database are very similar to the FVC2004 database

Fingerprint synthesis toward construct enhanced Authentication System using low resolution Webcam

Synthesis of several biometrics to improve the authentication performance has received significant attention over recent years due to a rising demand for reliable user identity authentication system. In this paper we present an approach to synthesis same biometrics because during capturing fingerprint it is not confirm that all minutiae of the whole fingerprint will be obtained in every ingestion. It is very essential to obtain whole minutiae from a fingerprint when we are using minutiae matching technique for fingerprint authentication. This paper introduces an Enhanced Authentication System using fingerprint synthesis by Projection Incorporated Subspace based on PCA (Principal Component Analysis). We have used a low resolution webcam to capture fingerprint images. So, an improved fingerprint image enhancement approach is presented. In the proposed approach, the traditional minutiae detection technique has been improved using fingerprint synthesis by Projection Incorporated Subspace based on PCA. The paper presents an analysis of why fingerprint synthesis approach is well suited for fingerprint enrolment, especially for the performance improvement of the minutiae extraction algorithm. Experimental results show that our approach is insensate to low resolution as well as with effectual performance and very effective for minutiae detection to improve authentication system

Precise Fingerprint Enrolment through Projection Incorporated Subspace Based on Principal Component Analysis (PCA)

Despite recent advances in the area of fingerprint identification, fingerprint enrolment continues to be a challenging pattern recognition problem. The first step to this problem is the enhancement of landmarks as well as precise minutiae points (ridge bifurcation and ridge ending), core, plain ridges from a print. Once enhanced, these fingerprint images are then ready to extract features and store into a database. Later these are compared to all sets on file in search of a match. The accurate fingerprint image is the basis for the entire identification and matching process. Various enhancement approaches have been proposed in the literature, each with its own merits and degree of success. The most common approach is to enhance and store the precise fingerprint image through normalization, orientation, frequencies calculation, contextual filtering and then binarisation and masking. Our emphasis in this paper is to enhance and store the fingerprint image accurately using Projection Incorporated Subspace based on Principal Component Analysis (PCA). In particular, we have implemented the methods based on eigenspace representations and neural network classifiers. Moreover, we present preliminary results of an attempt to mingle the outputs of these methods using a clustering algorithm unique to this type of problem

Fingerprint Authentication System using a low-priced Webcam

A number of biometric techniques have been proposed for personal identification in the past. Among the vision-based ones, we can point out fingerprint, face, palm, ear, iris and retina recognition. Voice recognition or signature verification are the most widely known among the non-vision based ones. Signature verification requires the use of electronic tablets or digitizers for on-line capturing and optical scanners for on-line adaptation. These interfaces have some negative aspect that they are large and convoluted to use, increasing the intricacy of the whole identification system. On the other hand, scanners and cameras are much smaller and easy to handle, and are becoming all over in the current computer atmosphere. Lots of vision-based biometric techniques have been projected in the past for personal identification. We present a novel one based on visual capturing of fingerprints using a Webcam. However, there is an open issue to use webcam in stead of any scanner because of the low price, available in the market and easy to adjust anywhere. In this paper, we describe our implementation of the fingerprint authentication system using webcam having Pentium IV CPU, 256 RAM and a piece of transparent glass and a light source. Also, we describe a preprocessing technique based on gamma manipulation and gamma correction that can be executed to adjust lightness and intensities of the fingerprint image before fingerprint image enhancement and feature extraction

Multimodality to improve Security and Privacy in Fingerprint Authentication System

With the pace of increasing online transactions and communication, the demand for security and privacy increases. To protect confidential information and to authenticate people electronically, several solutions already introduced. Traditional biometric systems that are based on single biometric usually suffer from problems like impostors’ attack or hacking, unacceptable error rates. To improve security and privacy and system’s reliability two or more biometrics of the same identity could be combined in a method that enhances the efficiency of the system. The biometric information, however, is irreplaceable information, when it is compromised. Thereby, one must give a special attention to protection of such information. We propose a novel protection technique for the biometric information, especially the feature information and the templates. The point of our proposal is securely embeds and extracts an iris template in a fingerprint image using a combined DWT and LSB based biometric watermarking algorithm in each authentication. The embedded data travel through insecure communication line like the internet, and they are used in matching process. This technique causes security against eavesdropping and replay attacks on the internet, because the watermark embedded transmitted data are used in the authentication session after watermark extraction

Biometric Template Protection Using Watermarking with Hidden Password Encryption

For quite a few years the biometric recognition techniques have been developed. Here, we briefly review some of the known attacks that can be encountered by a biometric system and some corresponding protection techniques. We explicitly focus on threats designed to extract information about the original biometric data of an individual from the stored data as well as the entire authentication system. In order to address security and privacy concerns, we present a biometric authentication scheme that uses two separate biometric features combined by watermark embedding with hidden password encryption to obtain a non-unique identifier of the personage. Furthermore, to present the performance of the authentication system we provide experimental results. The transformed features and templates trek through insecure communication line like the Internet or intranet in the client-server environment. Our projected technique causes security against attacks and eavesdropping because the original biometric will not be exposed anywhere in the authentication system