The transportation challenges experienced in major cities as a result of influx of people in search of greener pastures is increasing on a daily basis. This results in an increase in the number of cars plying and competing for driving space on narrow roads. Many drivers violate traffic laws as a result of this and how to prosecute them without chasing them remains an issue to be addressed. Therefore, this research presents a model that can be used to solve this challenge using machine learning algorithms. The model consists of recognition modules such as image acquisition, Gaussian blur, localization of car plate, character segmentation and optical character recognition of car plate. K-NN Algorithm was used for training licensed plate font type spanning A-Z and 0-9 while the speed tracking module used a camera which is automatically self-initiated to track the speed of any moving object within its range of focus. The performance of the model was evaluated using metrics such as recognition accuracy, positive prediction value, negative prediction value, specificity and sensitivity. A tracking accuracy of 82% was achieved.
IRJET-A review of Face Recognition Based Car Ignition and Security SystemIRJET Journal
This document proposes a face recognition system to replace traditional car ignition keys. The system would use a Raspberry Pi and MATLAB algorithms to detect and track a user's face in order to start the car. It discusses how face recognition is a growing field in computer vision and security. The proposed system would work by detecting a user's face, recognizing it as an authorized user, and then enabling ignition. This adds security beyond a traditional key while maintaining convenience. It aims to prevent theft while incorporating modern computer vision techniques.
Application on character recognition system on road sign for visually impaire...IJECEIAES
Many visually impaired people worldwide are unable to travel safely and autonomously because they are physically unable to perceive effective visual information during their daily lives. In this research, we study how to extract the character information of the road sign and transmit it to the visually impaired effectively, so they can understand easier. Experimental method is to apply the Maximally Stable External Region and Stroke Width Transform method in Phase I so that the visually impaired person can recognize the letters on the road signs. It is to convey text information to the disabled. The result of Phase I using samples of simple road signs was to extract the sign information after dividing the exact character area, but the accuracy was not good for the Hangul (Korean characters) information. The initial experimental results in the Phase II succeeded in transmitting the text information on Phase I to the visually impaired. In the future, it will be required to develop a wearable character recognition system that can be attached to the visually impaired. In order to perform this task, we need to develop and verify a miniaturized and wearable character recognition system. In this paper, we examined the method of recognizing road sign characters on the road and presented a possibility that may be applicable to our final development.
International Journal of Computer Vision and machine learning (IJCVML) aciijournal
International Journal of Computer Vision and machine learning (IJCVML)carry original articles, review articles, case studies and short communications from all over the world. The main aim of this journal is to extend the state of the art on theoretical, computational and experimental aspects of expert systems related to the applied fields such as transportation, surveillance, medical and industrial domains.
IRJET- Number Plate Extraction from Vehicle Front View Image using Image ...IRJET Journal
This document summarizes a research paper on extracting vehicle number plates from front-facing images using image processing techniques. The paper proposes a system that uses a camera to capture vehicle images, processes the images to isolate and extract the number plate, recognizes the characters on the plate, and displays the plate text. The system works by first converting the color image to grayscale. Edge detection, morphological operations and binary thresholding are then used to segment and extract the number plate region. Bounding box techniques isolate individual characters which are converted to text using OCR. The method achieved accurate number plate extraction on vehicle images taken in different lighting conditions and resolutions. The system has applications in traffic monitoring, law enforcement and vehicle identification.
This document summarizes a research paper on a smart parking management system that uses IoT technology. The system uses infrared sensors to detect available parking spaces. It transmits parking availability data via Wi-Fi to a server, which then provides the information to a mobile app. The app allows users to check for and reserve available spaces conveniently and free of cost. The system aims to help users more efficiently find parking and reduce traffic and fuel consumption by eliminating unnecessary driving to locate spots. It integrates technologies like Arduino, Android apps, infrared sensors, and cloud computing within an IoT framework.
Automated License Plate detection and Speed estimation of Vehicle Using Machi...ijtsrd
A well ordered traffic management system is required in all types of roads, such as off roads, highways, etc. There has been several laws and speed controlled measures are taken in all places with different perspectives. Also Speed limit may vary from road to road. So there are number of methods has been proposed using computer Vision and machine learning algorithms for object tracking. Here vehicles are recognized and detected from the videos that taken using surveillance camera. The aim is to identification of the vehicles and tracking using Haar Classifier, then determine the speed of the vehicle and Finally Detecting the License plate of the vehicle. Detecting the License plate and vehicle speed using machine learning is tough but beneficial task. For the past few years Convolution Neural Network CNN has been widely used in computer vision for vehicle detection and identification. Dlibs are used to track the multiple objects at the same time. P. Devi Mahalakshmi | Dr. M. Babu "Automated License Plate detection and Speed estimation of Vehicle Using Machine Learning - Haar Classifier Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33395.pdf Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/33395/automated-license-plate-detection-and-speed-estimation-of-vehicle-using-machine-learning--haar-classifier-algorithm/p-devi-mahalakshmi
The Autonomous car is about to enter the mass-market. The question is not about when it will happen but in which conditions, under which form or who will be the first car manufacturer to release an efficient and reliable final product. Entirely unexpected ways to deal with building up the AI frameworks for self-driving vehicles exist and most of them are horribly best in class and with extremely high equipment needs. The appropriate response presented during this paper proposes the AI fundamentally based framework to be as simple as conceivable with low equipment needs. A straight forward three layers profound, totally associated neural system was prepared to outline pictures from a forward looking QVGA camera to directing orders. Upheld an information picture the neural system should settle on one among the four offered orders (Forward, Left, Right or Stop). With least of the instructing information (250 pictures) the framework figured out how to follow the street ahead and keep in its path.The framework precisely learns essential street alternatives with exclusively the directing point in light of the fact that the contribution from the human driver. it had been near explicitly prepared to watch lines out and about. Contrasted with rather progressively confounded arrangements like express decay of the issue, similar to path identification and the board and convolutional neural systems simply like the conclusion to complete the process of learning arranged by the N-Vidia this technique demonstrated to be amazingly solid and affordable. we will in general attempt to demonstrate that this methodology would bring about better and lower equipment necessities so making the occasion of oneself driving vehicles simpler and more financially savvy. Simple counterfeit neural system, much the same as the one gave during this paper, is sufficient for relatively muddled technique like path keeping.
Vehicle plate recognition is a successful image processing technique used to recognize vehicles' plate numbers. There are several applications for this method which enlarge through many fields and attention groups. Vehicle plate recognition may be considered as an advertising equipment, for the purpose of traffic and border securities for law enforcement, and travel. Many methods have been accompanied to make this technique easy. This learning proposes an edge-detection method to allow a Plate Recognition System of a vehicle through the practical situations like the various environmental or meteorological conditions. Image processing tools are used to examine the plate area, resize it, and change it on the way to a gray scale earlier to filtering of the image in order to remove the unwanted areas. The obtained objects is processed in such a way that the number plate image and the information related to that is completely perfect The information of the obtained image is processed through the average deviation of the Gaussian filter (sigma).
IRJET-A review of Face Recognition Based Car Ignition and Security SystemIRJET Journal
This document proposes a face recognition system to replace traditional car ignition keys. The system would use a Raspberry Pi and MATLAB algorithms to detect and track a user's face in order to start the car. It discusses how face recognition is a growing field in computer vision and security. The proposed system would work by detecting a user's face, recognizing it as an authorized user, and then enabling ignition. This adds security beyond a traditional key while maintaining convenience. It aims to prevent theft while incorporating modern computer vision techniques.
Application on character recognition system on road sign for visually impaire...IJECEIAES
Many visually impaired people worldwide are unable to travel safely and autonomously because they are physically unable to perceive effective visual information during their daily lives. In this research, we study how to extract the character information of the road sign and transmit it to the visually impaired effectively, so they can understand easier. Experimental method is to apply the Maximally Stable External Region and Stroke Width Transform method in Phase I so that the visually impaired person can recognize the letters on the road signs. It is to convey text information to the disabled. The result of Phase I using samples of simple road signs was to extract the sign information after dividing the exact character area, but the accuracy was not good for the Hangul (Korean characters) information. The initial experimental results in the Phase II succeeded in transmitting the text information on Phase I to the visually impaired. In the future, it will be required to develop a wearable character recognition system that can be attached to the visually impaired. In order to perform this task, we need to develop and verify a miniaturized and wearable character recognition system. In this paper, we examined the method of recognizing road sign characters on the road and presented a possibility that may be applicable to our final development.
International Journal of Computer Vision and machine learning (IJCVML) aciijournal
International Journal of Computer Vision and machine learning (IJCVML)carry original articles, review articles, case studies and short communications from all over the world. The main aim of this journal is to extend the state of the art on theoretical, computational and experimental aspects of expert systems related to the applied fields such as transportation, surveillance, medical and industrial domains.
IRJET- Number Plate Extraction from Vehicle Front View Image using Image ...IRJET Journal
This document summarizes a research paper on extracting vehicle number plates from front-facing images using image processing techniques. The paper proposes a system that uses a camera to capture vehicle images, processes the images to isolate and extract the number plate, recognizes the characters on the plate, and displays the plate text. The system works by first converting the color image to grayscale. Edge detection, morphological operations and binary thresholding are then used to segment and extract the number plate region. Bounding box techniques isolate individual characters which are converted to text using OCR. The method achieved accurate number plate extraction on vehicle images taken in different lighting conditions and resolutions. The system has applications in traffic monitoring, law enforcement and vehicle identification.
This document summarizes a research paper on a smart parking management system that uses IoT technology. The system uses infrared sensors to detect available parking spaces. It transmits parking availability data via Wi-Fi to a server, which then provides the information to a mobile app. The app allows users to check for and reserve available spaces conveniently and free of cost. The system aims to help users more efficiently find parking and reduce traffic and fuel consumption by eliminating unnecessary driving to locate spots. It integrates technologies like Arduino, Android apps, infrared sensors, and cloud computing within an IoT framework.
Automated License Plate detection and Speed estimation of Vehicle Using Machi...ijtsrd
A well ordered traffic management system is required in all types of roads, such as off roads, highways, etc. There has been several laws and speed controlled measures are taken in all places with different perspectives. Also Speed limit may vary from road to road. So there are number of methods has been proposed using computer Vision and machine learning algorithms for object tracking. Here vehicles are recognized and detected from the videos that taken using surveillance camera. The aim is to identification of the vehicles and tracking using Haar Classifier, then determine the speed of the vehicle and Finally Detecting the License plate of the vehicle. Detecting the License plate and vehicle speed using machine learning is tough but beneficial task. For the past few years Convolution Neural Network CNN has been widely used in computer vision for vehicle detection and identification. Dlibs are used to track the multiple objects at the same time. P. Devi Mahalakshmi | Dr. M. Babu "Automated License Plate detection and Speed estimation of Vehicle Using Machine Learning - Haar Classifier Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33395.pdf Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/33395/automated-license-plate-detection-and-speed-estimation-of-vehicle-using-machine-learning--haar-classifier-algorithm/p-devi-mahalakshmi
The Autonomous car is about to enter the mass-market. The question is not about when it will happen but in which conditions, under which form or who will be the first car manufacturer to release an efficient and reliable final product. Entirely unexpected ways to deal with building up the AI frameworks for self-driving vehicles exist and most of them are horribly best in class and with extremely high equipment needs. The appropriate response presented during this paper proposes the AI fundamentally based framework to be as simple as conceivable with low equipment needs. A straight forward three layers profound, totally associated neural system was prepared to outline pictures from a forward looking QVGA camera to directing orders. Upheld an information picture the neural system should settle on one among the four offered orders (Forward, Left, Right or Stop). With least of the instructing information (250 pictures) the framework figured out how to follow the street ahead and keep in its path.The framework precisely learns essential street alternatives with exclusively the directing point in light of the fact that the contribution from the human driver. it had been near explicitly prepared to watch lines out and about. Contrasted with rather progressively confounded arrangements like express decay of the issue, similar to path identification and the board and convolutional neural systems simply like the conclusion to complete the process of learning arranged by the N-Vidia this technique demonstrated to be amazingly solid and affordable. we will in general attempt to demonstrate that this methodology would bring about better and lower equipment necessities so making the occasion of oneself driving vehicles simpler and more financially savvy. Simple counterfeit neural system, much the same as the one gave during this paper, is sufficient for relatively muddled technique like path keeping.
Vehicle plate recognition is a successful image processing technique used to recognize vehicles' plate numbers. There are several applications for this method which enlarge through many fields and attention groups. Vehicle plate recognition may be considered as an advertising equipment, for the purpose of traffic and border securities for law enforcement, and travel. Many methods have been accompanied to make this technique easy. This learning proposes an edge-detection method to allow a Plate Recognition System of a vehicle through the practical situations like the various environmental or meteorological conditions. Image processing tools are used to examine the plate area, resize it, and change it on the way to a gray scale earlier to filtering of the image in order to remove the unwanted areas. The obtained objects is processed in such a way that the number plate image and the information related to that is completely perfect The information of the obtained image is processed through the average deviation of the Gaussian filter (sigma).
IRJET- Vehicle Seat Vacancy Identification using Image Processing TechniqueIRJET Journal
This document describes a system that uses image processing techniques on images captured by a webcam installed in a vehicle to detect passengers' faces and estimate the number of passengers and seat vacancy. The system first captures images of the passenger area and sends them to a server. It then uses techniques like morphological operations, CLAHE, and Haar classifiers for face detection. Features are extracted using LBP and HOG, and an SVM classifies images to estimate passengers' gender. Experimental results show the system can accurately detect faces and estimate numbers even from low quality images, providing real-time vacancy information to help passengers plan their travel.
IRJET- Identification of Accident Prone Spots using Mobile ApplicationIRJET Journal
This document describes a mobile application called Road Gazer that aims to identify accident-prone areas on roads by allowing users to report issues. The application allows users to submit a complaint that includes a location, image, and description of the issue like poor road conditions, unauthorized median cuts, or accidents. This data is stored in a database. Authorities can then access the database to analyze complaint data, identify high-risk areas, and take preventive measures. The goal is to reduce road accidents and fatalities by addressing infrastructure problems before more accidents occur. The application was created using Android Studio and stores data in a SQLite database and Google Firebase. It allows real-time reporting of issues directly from roads to help authorities improve safety
Deep Learning Algorithm Using Virtual Environment Data For Self-Driving Carsushilkumar1236
The document presents a deep learning algorithm for a self-driving car that uses computer vision techniques. It discusses using cameras, sensors, and machine learning models to process image data for tasks like lane detection, road sign identification, obstacle detection and avoidance. The design uses a convolutional neural network trained on thousands of images to classify objects. Experimental results showed this approach can reliably perform key computer vision tasks necessary for autonomous driving.
This document describes a system that uses image processing techniques to detect available and occupied parking spots in a parking area. Camera images of the parking area are processed every 20 seconds to identify circles marking spots, and information on vacant and occupied spots is sent to an Android app. The app allows users to view parking availability in real-time and get navigation directions to the parking area from their current location. The system aims to help drivers more efficiently find parking and reduce traffic and pollution from circling for spots.
This paper presents a system to monitor drop-off/pick up of school children to enhance the safety of children during the daily transportation from and to school. The system consists of two main units that are school unit and bus unit. The bus unit is used to detect when a child boards the bus or leaves the bus. This information is communicated to the school unit to identify the children did not board or leave the bus. The system has a developed web-based database-driven application which facilities its management and provides useful information about the children to authorized personal. A complete prototype of the proposed system was tested and implemented to validate the system functionality. The proposed system facilitates to know about the area where the vehicle has crossed the path using RFID Formulated by merging Global Positioning System (GPS) and Radio Frequency Identification. The GPS technology connected with this system helps in acquiring updates on student’s real time location. This proficient tracking structure with enriched features is designed and implemented for the purpose of protection in various streams. It is up and coming technology in the field of communication and network. The “TAGS ON ROAD” model is an evolving and justifiable technique in future world. The projected system here is planned to be implemented in school vehicles for the safety of the students and it can also be installed in the professional security system for VIP‟s and politicians.
This document describes a human-tracking robot that uses ultra-wideband (UWB) technology. It proposes using a modified hyperbolic positioning algorithm and virtual spring model to detect, locate, and track a target person in real-time. The robot is equipped with UWB anchors and ultrasound sensors, and an embedded control board processes sensor data to drive motors for following movements. An advantage of the UWB method over computer vision is robustness to varying lighting conditions outdoors. Experimental results demonstrate the tracking performance of the robot.
This document provides an overview of computer vision including its definition, applications, working concepts, popular models and datasets, advantages, and disadvantages. Computer vision is a field that uses computer algorithms to gain a high-level understanding from digital images or videos. It has applications in areas like face detection, object detection and tracking, developing social distancing tools, and medical image analysis. Popular computer vision models include ResNet, YOLO, and MobileNet, and datasets include COCO, ImageNet, and CIFAR10. Advantages are faster and more reliable processing while disadvantages include needing specialists and potential failures in image processing. The document also discusses uses of computer vision for COVID-19 response and in areas like healthcare, automotive, and retail
Statistics indicate that most road accidents occur due to a lack of time to react to instant traffic. This problem can be addressed with self-driving vehicles with the application of automated systems to detect such traffic events. The Autonomous Vehicle Navigation System (ATS) has been a standard in the Intelligent Transport System (ITS) and many Driver Assistance Systems (DAS) have been adopted to support these Advanced Autonomous Vehicles (IAVs). To develop these recognition systems for automated self-driving cars, it's important to monitor and operate in real-time traffic events. It requires the correct detection and response of traffic event an automated vehicle. In this paper proposed to develop such a system by applying image recognition to detect and respond to a road blocker by means of real-time distance measurement. To study the performance by measuring accuracy and precision of road blocker detection system and distance calculation, various experiments were conducted by using Shalom frame dataset and detection accuracy, precision of 99%, 100%, while distance calculation 97%, 99% has been achieved by this approach.
1) The document proposes techniques for real-time Indian road analysis using image processing and computer vision, including lane detection, pothole detection, object detection from video, and road sign classification.
2) It discusses using the Hough transform for lane detection, color segmentation and shape modeling with thin spline transformation for road sign classification, and k-means clustering for pothole detection.
3) The techniques are tested on images and video streams from Indian roads to show they can be used for real-time analysis in an automated driver guidance system.
Smart Card: A study of new invention on bus fare in Dhaka cityMd. Abdul Munem
Technology is developing day to day. So we have to be familiar with technology. Digital payment system
is one of them. Our government will launch a pilot project for transportation under 22 buses on 42 routes.
It will be better if the smart card will included in that project. In the term paper I have focused the problems
we faced on public transport.
Eye(I) Still Know! – An App for the Blind Built using Web and AIDr. Amarjeet Singh
This paper proposes eye(I) still know!, a voice control solution for the visually impaired people. The main purpose is even though the blind cannot see they can still know where to go and what to do! Nearby 60% of total blind population across the world is present in India. In a time where no one likes to rely on anyone, this is a small effort to make the blind independent individuals. This can be achieved using wireless communication, voice recognition and image scanning. The application with the use of object identification will priorly inform about the barriers in the path.
The software will use the camera of the device and scan all the obstacles with their corresponding distances from the user. This will be followed by audio instructions through audio output of the device.
This will efficiently direct the user through his/her way.
Vehicle Tracking System for Kid's SafetyDebabrata Bej
The document proposes a vehicle tracking system using RFID and GSM for child safety. The system aims to track the exact location of school buses using RFID tags placed at bus stops and a GPS device on the bus. RFID readers on buses would read the tags and send the bus location to a school server via GSM. Parents would receive SMS messages when their child enters or exits the bus, and about the current location of the bus. The system is intended to address issues of child safety and ease parents' worries regarding their children's transportation to school.
BUILDING INFORMATICS: REVIEW OF SELECTED INFORMATICS PLATFORM AND VALIDATING ...IAEME Publication
Automation has introduced new dimension to the advent of project and
construction execution in construction field. Virtually all aspect of construction is
being innovated with cutting edge technology. In this study cutting edge technologies
were evaluated and their various validation platforms were evaluated. The following
objectives were set and achieved in this study: Establishing different tests that could
be carried out to ascertain functionality of an informatics platform, review of features
present in available informatics platforms, exploratory study of platform validity
system through functionality tests and developing a semantic icon functionality test.
Ten (10) informatics platforms were selected for case study, while 40 structured
questionnaires was used to collate respondents data as related to on the critical
factors that influences the effective use of system usability test on ICT Informatics
platform and parameters for newly generated Icon functionality rating scale(IRS). A
new test protocol was designed that could be used for carrying out Icon functionality
rating evaluation tagged”IRS”.
IRJET-An Interline Dynamic Voltage Restorer (IDVR)IRJET Journal
This document summarizes a research paper on developing a biometric e-license system using fingerprints for driver identification and vehicle verification. The system aims to digitize driver's licenses and vehicle documents so that individuals do not need to carry physical documents. It involves developing Android and web applications to extract fingerprint minutiae and match them against a database to retrieve a person's driving records and vehicle details. The system architecture, hardware requirements, algorithm used and benefits of increasing efficiency and reducing documentation are discussed in less than 3 sentences.
Tugas Paper Teknik Penulisan Karya IlmiahSyahditaLika
This document summarizes 4 articles related to smart parking systems using technologies like IoT, RFID, fuzzy logic, and Arduino:
1) The 2019 article describes a smart parking location determination system for university campuses using fuzzy logic and IoT to detect available spaces and allow reservations via smartphone.
2) The 2019 article presents a parking access system using an e-ID card and Arduino-based RFID technology for identification and recording vehicle license plates.
3) The 2018 article proposes a smart parking payment system combining NFC and GPS on smartphones to allow contactless payment without paper tickets.
4) The 2017 article reviews automatic license plate recognition technologies and discusses challenges for implementing them in Indonesia.
International Journal of Computer Vision and machine learning (IJCVML) is an open access, peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced vision computing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding advances in vision computing and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of vision computing.
IRJET-Artificial Intelligence and its Applications GoalIRJET Journal
This document discusses artificial intelligence (AI) and its applications. It begins by defining AI as making machines capable of performing intelligent tasks like humans. It then discusses three areas of simulated AI: machine learning systems, machine intelligence systems, and machine consciousness systems. The document outlines various applications of AI in fields like finance, manufacturing, healthcare, transportation, and weather forecasting. It concludes by stating that AI will continue playing an important role in science and technology, but whether AI can achieve human-level consciousness is still unknown and depends on further research.
A novel real time video and data capture of vehicular accident in intelligent...IJCNCJournal
- The document proposes a novel scheme for real-time video and data capture of vehicular accidents in intelligent transportation systems.
- The scheme involves an in-vehicle system that alternates between two video files every 5 minutes to record video using a small storage size. When an accident is detected, it stops recording and saves the video.
- It also proposes a real-time video and data capture scheme where the vehicle streams video and sensor data to a remote ITS server in real-time. The server records this information using the same approach as the in-vehicle system to efficiently store accident data.
International Journal of Humanities, Art and Social Studies (IJHASS) ijfcst journal
International Journal of Humanities, Art and Social Studies (IJHASS)
http://flyccs.com/jounals/IJHASS/Home.html
Scope
Humanities, Art and Social Studies Of International Journal (IJHASS) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of humanities, art and social science. The journal focuses aims to promote interdisciplinary studies in humanities and social science and become the leading journal in humanities and social science in the world. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on areas of literary and social studies for a cross cultural exploration and subsequent innovation of subjects concerned and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles for the development of humanities and social science fields.
Topics of interest include, but are not limited to, the following
• Humanities and social science such as anthropology
• Visual Arts
• Anthropology, Area Studies, Archaeology
• Culture and Ethics Studies
• Economics, Ethics, Geography, History
• Business studies
• Communication studies
• Corporate governance
• Criminology, Cross-cultural studies
• Demography, Development studies
• Economics
• Education
• Language and Linguistics
• History
• Literature
• Performing Art
• Philosophy
• Religion
• Media studies, Methodology
• Paralegal, Performing arts (music, theatre & dance)
• Gender and Sexuality Studies, Geography
• Industrial relations, Information Science, International relations
• Law, Linguistics, Library science, Linguistics Literature
• Political science, Philosophy
• Psychology, Population Studies
• Public administration
• Religious studies
• Social welfare, Sociology
Paper Submission
Authors are invited to submit papers for this journal through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Other journals
• International Journal of Education (IJE)
• International Journal of Computer Vision and machine learning(IJCVML)
• International Journal of Mobile Robot Navigation(IJMRN)
Important Dates
• Submission Deadline :June 08, 2019
• Notification :July 08, 2019
• Final Manuscript Due :July 16, 2019
• Publication Date : Determined by the Editor-in-Chief
• TO SUBMIT YOUR PAPER, PLEASE CLICK THE FOLLOWING LINK Submit
Contacts
Here's where you can reach us : jcncjournal@yahoo.com
Research on object detection and recognition using machine learning algorithm...YousefElbayomi
This document discusses research on using machine learning and deep learning for object detection. It examines applications in autonomous vehicles, image detection for agriculture, and credit card fraud detection. For autonomous vehicles, deep learning is discussed for object identification and perception, though speed and real-world performance need improvement. Image detection for agriculture uses feature extraction and machine learning for automatic fruit identification. Credit card fraud detection uses ensemble methods like LightGBM, XGBoost and CatBoost on preprocessed transaction data to identify fraudulent transactions. The document evaluates different approaches and their challenges for these applications of object detection.
A Vision based Driver Support System for Road Sign Detectionidescitation
In this paper, we proposed a replacement hybrid multipath routing protocol for
MANET known as Hybrid Multipath Progressive Routing Protocol for MANET (HMPRP),
during this work we improve the performance of accepted MANET routing protocols,
namely, the Ad-hoc On-demand Distance Vector routing protocol and use of their most
popular properties to formulate a replacement Hybrid routing protocol using the received
signal strength. The proposed routing protocol optimizes the information measure usage of
MANETs by reducing the routing overload and overhead. This proposed routing protocol
additionally extends the battery lifetime of the mobile devices by reducing the specified
variety of operations for (i) Route determination (ii) for packet forwarding. Simulation
results are used to draw conclusions regarding the proposed routing algorithm and
compared it with the AODV, OLSR, and ZRP protocol. Experiments carried out based on
this proposed algorithm, shows that better performance are achieved with regard to AODV,
OLSR, and ZRP routing algorithm in terms of packet delivery ratio, throughput, energy
consumed and end-to-end packet delay.
IRJET- Vehicle Seat Vacancy Identification using Image Processing TechniqueIRJET Journal
This document describes a system that uses image processing techniques on images captured by a webcam installed in a vehicle to detect passengers' faces and estimate the number of passengers and seat vacancy. The system first captures images of the passenger area and sends them to a server. It then uses techniques like morphological operations, CLAHE, and Haar classifiers for face detection. Features are extracted using LBP and HOG, and an SVM classifies images to estimate passengers' gender. Experimental results show the system can accurately detect faces and estimate numbers even from low quality images, providing real-time vacancy information to help passengers plan their travel.
IRJET- Identification of Accident Prone Spots using Mobile ApplicationIRJET Journal
This document describes a mobile application called Road Gazer that aims to identify accident-prone areas on roads by allowing users to report issues. The application allows users to submit a complaint that includes a location, image, and description of the issue like poor road conditions, unauthorized median cuts, or accidents. This data is stored in a database. Authorities can then access the database to analyze complaint data, identify high-risk areas, and take preventive measures. The goal is to reduce road accidents and fatalities by addressing infrastructure problems before more accidents occur. The application was created using Android Studio and stores data in a SQLite database and Google Firebase. It allows real-time reporting of issues directly from roads to help authorities improve safety
Deep Learning Algorithm Using Virtual Environment Data For Self-Driving Carsushilkumar1236
The document presents a deep learning algorithm for a self-driving car that uses computer vision techniques. It discusses using cameras, sensors, and machine learning models to process image data for tasks like lane detection, road sign identification, obstacle detection and avoidance. The design uses a convolutional neural network trained on thousands of images to classify objects. Experimental results showed this approach can reliably perform key computer vision tasks necessary for autonomous driving.
This document describes a system that uses image processing techniques to detect available and occupied parking spots in a parking area. Camera images of the parking area are processed every 20 seconds to identify circles marking spots, and information on vacant and occupied spots is sent to an Android app. The app allows users to view parking availability in real-time and get navigation directions to the parking area from their current location. The system aims to help drivers more efficiently find parking and reduce traffic and pollution from circling for spots.
This paper presents a system to monitor drop-off/pick up of school children to enhance the safety of children during the daily transportation from and to school. The system consists of two main units that are school unit and bus unit. The bus unit is used to detect when a child boards the bus or leaves the bus. This information is communicated to the school unit to identify the children did not board or leave the bus. The system has a developed web-based database-driven application which facilities its management and provides useful information about the children to authorized personal. A complete prototype of the proposed system was tested and implemented to validate the system functionality. The proposed system facilitates to know about the area where the vehicle has crossed the path using RFID Formulated by merging Global Positioning System (GPS) and Radio Frequency Identification. The GPS technology connected with this system helps in acquiring updates on student’s real time location. This proficient tracking structure with enriched features is designed and implemented for the purpose of protection in various streams. It is up and coming technology in the field of communication and network. The “TAGS ON ROAD” model is an evolving and justifiable technique in future world. The projected system here is planned to be implemented in school vehicles for the safety of the students and it can also be installed in the professional security system for VIP‟s and politicians.
This document describes a human-tracking robot that uses ultra-wideband (UWB) technology. It proposes using a modified hyperbolic positioning algorithm and virtual spring model to detect, locate, and track a target person in real-time. The robot is equipped with UWB anchors and ultrasound sensors, and an embedded control board processes sensor data to drive motors for following movements. An advantage of the UWB method over computer vision is robustness to varying lighting conditions outdoors. Experimental results demonstrate the tracking performance of the robot.
This document provides an overview of computer vision including its definition, applications, working concepts, popular models and datasets, advantages, and disadvantages. Computer vision is a field that uses computer algorithms to gain a high-level understanding from digital images or videos. It has applications in areas like face detection, object detection and tracking, developing social distancing tools, and medical image analysis. Popular computer vision models include ResNet, YOLO, and MobileNet, and datasets include COCO, ImageNet, and CIFAR10. Advantages are faster and more reliable processing while disadvantages include needing specialists and potential failures in image processing. The document also discusses uses of computer vision for COVID-19 response and in areas like healthcare, automotive, and retail
Statistics indicate that most road accidents occur due to a lack of time to react to instant traffic. This problem can be addressed with self-driving vehicles with the application of automated systems to detect such traffic events. The Autonomous Vehicle Navigation System (ATS) has been a standard in the Intelligent Transport System (ITS) and many Driver Assistance Systems (DAS) have been adopted to support these Advanced Autonomous Vehicles (IAVs). To develop these recognition systems for automated self-driving cars, it's important to monitor and operate in real-time traffic events. It requires the correct detection and response of traffic event an automated vehicle. In this paper proposed to develop such a system by applying image recognition to detect and respond to a road blocker by means of real-time distance measurement. To study the performance by measuring accuracy and precision of road blocker detection system and distance calculation, various experiments were conducted by using Shalom frame dataset and detection accuracy, precision of 99%, 100%, while distance calculation 97%, 99% has been achieved by this approach.
1) The document proposes techniques for real-time Indian road analysis using image processing and computer vision, including lane detection, pothole detection, object detection from video, and road sign classification.
2) It discusses using the Hough transform for lane detection, color segmentation and shape modeling with thin spline transformation for road sign classification, and k-means clustering for pothole detection.
3) The techniques are tested on images and video streams from Indian roads to show they can be used for real-time analysis in an automated driver guidance system.
Smart Card: A study of new invention on bus fare in Dhaka cityMd. Abdul Munem
Technology is developing day to day. So we have to be familiar with technology. Digital payment system
is one of them. Our government will launch a pilot project for transportation under 22 buses on 42 routes.
It will be better if the smart card will included in that project. In the term paper I have focused the problems
we faced on public transport.
Eye(I) Still Know! – An App for the Blind Built using Web and AIDr. Amarjeet Singh
This paper proposes eye(I) still know!, a voice control solution for the visually impaired people. The main purpose is even though the blind cannot see they can still know where to go and what to do! Nearby 60% of total blind population across the world is present in India. In a time where no one likes to rely on anyone, this is a small effort to make the blind independent individuals. This can be achieved using wireless communication, voice recognition and image scanning. The application with the use of object identification will priorly inform about the barriers in the path.
The software will use the camera of the device and scan all the obstacles with their corresponding distances from the user. This will be followed by audio instructions through audio output of the device.
This will efficiently direct the user through his/her way.
Vehicle Tracking System for Kid's SafetyDebabrata Bej
The document proposes a vehicle tracking system using RFID and GSM for child safety. The system aims to track the exact location of school buses using RFID tags placed at bus stops and a GPS device on the bus. RFID readers on buses would read the tags and send the bus location to a school server via GSM. Parents would receive SMS messages when their child enters or exits the bus, and about the current location of the bus. The system is intended to address issues of child safety and ease parents' worries regarding their children's transportation to school.
BUILDING INFORMATICS: REVIEW OF SELECTED INFORMATICS PLATFORM AND VALIDATING ...IAEME Publication
Automation has introduced new dimension to the advent of project and
construction execution in construction field. Virtually all aspect of construction is
being innovated with cutting edge technology. In this study cutting edge technologies
were evaluated and their various validation platforms were evaluated. The following
objectives were set and achieved in this study: Establishing different tests that could
be carried out to ascertain functionality of an informatics platform, review of features
present in available informatics platforms, exploratory study of platform validity
system through functionality tests and developing a semantic icon functionality test.
Ten (10) informatics platforms were selected for case study, while 40 structured
questionnaires was used to collate respondents data as related to on the critical
factors that influences the effective use of system usability test on ICT Informatics
platform and parameters for newly generated Icon functionality rating scale(IRS). A
new test protocol was designed that could be used for carrying out Icon functionality
rating evaluation tagged”IRS”.
IRJET-An Interline Dynamic Voltage Restorer (IDVR)IRJET Journal
This document summarizes a research paper on developing a biometric e-license system using fingerprints for driver identification and vehicle verification. The system aims to digitize driver's licenses and vehicle documents so that individuals do not need to carry physical documents. It involves developing Android and web applications to extract fingerprint minutiae and match them against a database to retrieve a person's driving records and vehicle details. The system architecture, hardware requirements, algorithm used and benefits of increasing efficiency and reducing documentation are discussed in less than 3 sentences.
Tugas Paper Teknik Penulisan Karya IlmiahSyahditaLika
This document summarizes 4 articles related to smart parking systems using technologies like IoT, RFID, fuzzy logic, and Arduino:
1) The 2019 article describes a smart parking location determination system for university campuses using fuzzy logic and IoT to detect available spaces and allow reservations via smartphone.
2) The 2019 article presents a parking access system using an e-ID card and Arduino-based RFID technology for identification and recording vehicle license plates.
3) The 2018 article proposes a smart parking payment system combining NFC and GPS on smartphones to allow contactless payment without paper tickets.
4) The 2017 article reviews automatic license plate recognition technologies and discusses challenges for implementing them in Indonesia.
International Journal of Computer Vision and machine learning (IJCVML) is an open access, peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced vision computing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding advances in vision computing and establishing new collaborations in these areas. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of vision computing.
IRJET-Artificial Intelligence and its Applications GoalIRJET Journal
This document discusses artificial intelligence (AI) and its applications. It begins by defining AI as making machines capable of performing intelligent tasks like humans. It then discusses three areas of simulated AI: machine learning systems, machine intelligence systems, and machine consciousness systems. The document outlines various applications of AI in fields like finance, manufacturing, healthcare, transportation, and weather forecasting. It concludes by stating that AI will continue playing an important role in science and technology, but whether AI can achieve human-level consciousness is still unknown and depends on further research.
A novel real time video and data capture of vehicular accident in intelligent...IJCNCJournal
- The document proposes a novel scheme for real-time video and data capture of vehicular accidents in intelligent transportation systems.
- The scheme involves an in-vehicle system that alternates between two video files every 5 minutes to record video using a small storage size. When an accident is detected, it stops recording and saves the video.
- It also proposes a real-time video and data capture scheme where the vehicle streams video and sensor data to a remote ITS server in real-time. The server records this information using the same approach as the in-vehicle system to efficiently store accident data.
International Journal of Humanities, Art and Social Studies (IJHASS) ijfcst journal
International Journal of Humanities, Art and Social Studies (IJHASS)
http://flyccs.com/jounals/IJHASS/Home.html
Scope
Humanities, Art and Social Studies Of International Journal (IJHASS) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of humanities, art and social science. The journal focuses aims to promote interdisciplinary studies in humanities and social science and become the leading journal in humanities and social science in the world. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on areas of literary and social studies for a cross cultural exploration and subsequent innovation of subjects concerned and establishing new collaborations in these areas. Authors are solicited to contribute to this journal by submitting articles for the development of humanities and social science fields.
Topics of interest include, but are not limited to, the following
• Humanities and social science such as anthropology
• Visual Arts
• Anthropology, Area Studies, Archaeology
• Culture and Ethics Studies
• Economics, Ethics, Geography, History
• Business studies
• Communication studies
• Corporate governance
• Criminology, Cross-cultural studies
• Demography, Development studies
• Economics
• Education
• Language and Linguistics
• History
• Literature
• Performing Art
• Philosophy
• Religion
• Media studies, Methodology
• Paralegal, Performing arts (music, theatre & dance)
• Gender and Sexuality Studies, Geography
• Industrial relations, Information Science, International relations
• Law, Linguistics, Library science, Linguistics Literature
• Political science, Philosophy
• Psychology, Population Studies
• Public administration
• Religious studies
• Social welfare, Sociology
Paper Submission
Authors are invited to submit papers for this journal through Submission System. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Other journals
• International Journal of Education (IJE)
• International Journal of Computer Vision and machine learning(IJCVML)
• International Journal of Mobile Robot Navigation(IJMRN)
Important Dates
• Submission Deadline :June 08, 2019
• Notification :July 08, 2019
• Final Manuscript Due :July 16, 2019
• Publication Date : Determined by the Editor-in-Chief
• TO SUBMIT YOUR PAPER, PLEASE CLICK THE FOLLOWING LINK Submit
Contacts
Here's where you can reach us : jcncjournal@yahoo.com
Research on object detection and recognition using machine learning algorithm...YousefElbayomi
This document discusses research on using machine learning and deep learning for object detection. It examines applications in autonomous vehicles, image detection for agriculture, and credit card fraud detection. For autonomous vehicles, deep learning is discussed for object identification and perception, though speed and real-world performance need improvement. Image detection for agriculture uses feature extraction and machine learning for automatic fruit identification. Credit card fraud detection uses ensemble methods like LightGBM, XGBoost and CatBoost on preprocessed transaction data to identify fraudulent transactions. The document evaluates different approaches and their challenges for these applications of object detection.
A Vision based Driver Support System for Road Sign Detectionidescitation
In this paper, we proposed a replacement hybrid multipath routing protocol for
MANET known as Hybrid Multipath Progressive Routing Protocol for MANET (HMPRP),
during this work we improve the performance of accepted MANET routing protocols,
namely, the Ad-hoc On-demand Distance Vector routing protocol and use of their most
popular properties to formulate a replacement Hybrid routing protocol using the received
signal strength. The proposed routing protocol optimizes the information measure usage of
MANETs by reducing the routing overload and overhead. This proposed routing protocol
additionally extends the battery lifetime of the mobile devices by reducing the specified
variety of operations for (i) Route determination (ii) for packet forwarding. Simulation
results are used to draw conclusions regarding the proposed routing algorithm and
compared it with the AODV, OLSR, and ZRP protocol. Experiments carried out based on
this proposed algorithm, shows that better performance are achieved with regard to AODV,
OLSR, and ZRP routing algorithm in terms of packet delivery ratio, throughput, energy
consumed and end-to-end packet delay.
IRJET- Smart Parking System using Facial Recognition, Optical Character Recog...IRJET Journal
The document proposes a smart parking system using facial recognition, optical character recognition (OCR), and the Internet of Things (IoT). The system uses facial recognition to identify drivers and OCR to extract text from vehicle license plates to verify if the driver and vehicle match database records. An IoT device is integrated with parking gates to automatically open them if verification is successful. The system aims to optimize parking space usage, enhance security, reduce congestion and emissions, and make the parking process more convenient. It analyzes previous research on smart parking and aims to implement an accurate and cost-effective solution.
Implementation of Various Machine Learning Algorithms for Traffic Sign Detect...IRJET Journal
This document discusses implementing various machine learning algorithms for traffic sign detection and recognition. It compares the accuracies of KNN, multinomial logistic regression, CNN, and random forest algorithms on a German traffic sign dataset. For real-time traffic sign detection, it uses the YOLO v4 model. The document reviews several papers on traffic sign recognition using techniques like SVM, CNN, Capsule Networks and analyzes their reported accuracies. It then describes the proposed system for traffic sign recognition using two datasets and data preprocessing steps before applying the algorithms and evaluating their performance.
Automated Identification of Road Identifications using CNN and KerasIRJET Journal
The document proposes a model to automatically detect traffic signs using convolutional neural networks (CNN) and the Keras library, even if the signs are unclear or damaged. It aims to help autonomous vehicles properly identify different types of traffic signs. The methodology involves collecting a dataset of traffic sign images, training a CNN model using Keras, testing the model on new images, and using the trained model to recognize signs from user-provided inputs in real-time. Evaluation metrics like accuracy and loss are plotted to analyze the model's performance. The system is meant to achieve over 95% accuracy in identifying various traffic sign types to assist self-driving cars in safely following traffic rules.
This document discusses lane and object detection using computer vision techniques. It begins with an abstract discussing increasing safety in advanced driver assistance systems through tasks like lane and obstacle detection. It then reviews related literature on lane and object detection algorithms. The document outlines the software requirements for a lane and object detection system, including functional requirements like providing an easy user interface and non-functional requirements like performance, safety, and quality attributes. It presents the system design with architectures, UML diagrams, and discusses using a waterfall model for development. Finally, it provides a project plan with estimates for cost and effort using the COCOMO model.
This document describes a proposed 3M secure transportation system that provides security for people (drivers), vehicles, and cargo. The system uses several technologies including face recognition, fingerprint verification, vehicle tracking via GPS and GSM, and QR scanning of cargo. An Android application would be developed to integrate these security features and monitor them. The system is intended for mid-sized transportation businesses to help prevent theft of vehicles and cargo.
Feature Extraction and Gesture Recognition_978-81-962236-3-2.pdfTIRUMALAVASU3
Advanced man-machine interfaces may be built using gestural interfaces based on vision
technology, but size of pictures rather than specialized acquisition equipment. Segmentation of
the hand, tracking, and identification of the hand position are the three key issues (feature
extraction and classification). Since the first computer was invented in the modern age,
technology has impacted every aspect of our social and personal life, revolutionizing how we
live. A few examples are browsing the web, writing a message, playing a video game, or saving
and retrieving personal or business data.
The technique of turning raw data into numerical features that can be handled while keeping
the information in the original data set is known as feature extraction. Compared to using
machine learning on the raw data directly, it produces superior outcomes. It is possible to
extract features manually or automatically. Identification and description of the characteristics
that are pertinent to a particular situation are necessary for manual feature extraction, as is the
implementation of a method to extract those features. Having a solid grasp of the context or
domain may often aid in making judgements about which characteristics could be helpful.
Engineers and scientists have created feature extraction techniques for pictures, signals, and
text through many years of study. The mean of a signal's window is an illustration of a
straightforward characteristic. Automated feature extraction eliminates the need for human
involvement by automatically extracting features from signals or pictures using specialized
algorithms or deep networks. When you need to go from collecting raw data to creating
machine learning algorithms rapidly, this method may be quite helpful. An example of
automated feature extraction is wavelet scattering.
Feature Extraction and Gesture Recognition Book.pdfSAMREENFIZA3
Advanced man-machine interfaces may be built using gestural interfaces based on vision
technology, but size of pictures rather than specialized acquisition equipment. Segmentation of
the hand, tracking, and identification of the hand position are the three key issues (feature
extraction and classification). Since the first computer was invented in the modern age,
technology has impacted every aspect of our social and personal life, revolutionizing how we
live. A few examples are browsing the web, writing a message, playing a video game, or saving
and retrieving personal or business data.
The technique of turning raw data into numerical features that can be handled while keeping
the information in the original data set is known as feature extraction. Compared to using
machine learning on the raw data directly, it produces superior outcomes. It is possible to
extract features manually or automatically. Identification and description of the characteristics
that are pertinent to a particular situation are necessary for manual feature extraction, as is the
implementation of a method to extract those features. Having a solid grasp of the context or
domain may often aid in making judgements about which characteristics could be helpful.
Engineers and scientists have created feature extraction techniques for pictures, signals, and
text through many years of study. The mean of a signal's window is an illustration of a
straightforward characteristic. Automated feature extraction eliminates the need for human
involvement by automatically extracting features from signals or pictures using specialized
algorithms or deep networks. When you need to go from collecting raw data to creating
machine learning algorithms rapidly, this method may be quite helpful. An example of
automated feature extraction is wavelet scattering.
The initial layers of deep networks have essentially taken the position of feature extraction with
the rise of deep learning, albeit primarily for picture data. Prior to developing powerful
prediction models for signal and time-series applications, feature extraction continues to be the
first hurdle that demands a high level of knowledge. For this reason, among others, humancomputer interaction (HCI) has been regarded as a vibrant area of study in recent years. The
most popular input devices haven't changed much since they were first introduced, perhaps
because the current devices are still useful and efficient enough. However, it is also generally
known that with the steady release of new software and hardware in recent years, computers
have become more pervasive in daily life. The bulk of human-computer interaction (HCI) today
is based on mechanical devices such a keyboard, mouse, joystick, or game-pad, however due
to their capacity to perform a variety of tasks, a class of computational vision-based approaches
is gaining popularity in natural recognition of human motions.
AN IMAGE BASED ATTENDANCE SYSTEM FOR MOBILE PHONESAM Publications
Automatic attendance system is one of the significant issues of today’s research. Among other methods, human face recognition is highly used technique for attendance automation. Many systems have been proposed in literature using face recognition. Most of the systems are using fixed camera and desktop computers. We propose a system using mobile phones where an image is captured of group of peoples and face detection is done automatically. While considering computational and storage power of mobile devices, extracted local binary features for detected faces are then transferred to server machine using firebase database. Matching is done on server side, if face recognized than attendance is marked and feedback is sent back to client side. Experiments show effectiveness of proposed techniques with 95% correct recognition rate.
Intelligent Transportation System Based On Machine Learning For Vehicle Perce...IRJET Journal
The document discusses using machine learning for intelligent transportation systems based on vehicle perception. It provides an overview of how machine learning has been increasingly used for tasks like vehicle detection, counting, classification, identification and speed detection. Specifically, it describes approaches like background subtraction, optical flow and deep learning models that have been applied to problems in traffic monitoring, management and road safety. The document also reviews common computer vision algorithms in OpenCV that can be utilized for these tasks and considers factors like speed, accuracy and complexity in choosing the appropriate methods.
IRJET- Vehicle Detection and Tracking System IoT based: A ReviewIRJET Journal
This document reviews vehicle detection and tracking systems using IoT technologies like Raspberry Pi. It discusses how previous studies have used GPS, GSM, and other sensors to track vehicle location in real-time and identify issues with those approaches. The document proposes a new vehicle tracking system that uses Raspberry Pi connected to a 3G/4G USB dongle to obtain location data and send it to the cloud for representation on a map. This provides real-time tracking while aiming to reduce costs and power consumption compared to other methods.
A Survey Paper On Non Intrusive Texting While Driving Detection Using Smart P...Kim Daniels
This document summarizes research on detecting texting while driving using smartphones without user intervention. It proposes using sensors like gyroscopes, accelerometers and GPS to collect touch patterns, device orientation, and vehicle speed. Three patterns are identified to distinguish drivers from passengers: 1) editing messages after speed decreases, 2) stopping edits during turns, and 3) holding the phone upright while editing. The system would identify texting while driving patterns using sensor data without reading message content, preserving privacy. Existing approaches require user input or additional devices to detect location, while this proposed method requires only the user's smartphone.
APPLICATION OF VARIOUS DEEP LEARNING MODELS FOR AUTOMATIC TRAFFIC VIOLATION D...ijitcs
A rapid growth in the population and economic growth has resulted in an increasing number of vehicles on
road every year. Traffic congestion is a big problem in every metropolitan city. To reach their destination
faster and to avoid traffic, some people are violating traffic rules and regulations. Violation of traffic rules
puts everyone in danger. Maintaining traffic rules manually has become difficult over the time due to the
rapid increase in the population. This alarming situation has be taken care of at the earliest. To overcome
this, we need a real-time violation detection system to help maintain the traffic rules. The approach is to
detect traffic violations in real-time using edge computing, which reduces the time to detect. Different
machine learning models and algorithms were applied to detect traffic violations like traveling without a
helmet, line crossing, parking violation detection, violating the one-way rule etc. The model implemented
gave an accuracy of around 85%, due to memory constraints of the edge device in this case NVIDIA Jetson
Nano, as the fps is quite low.
2022- July Gamified_Mobile_Applications_for_Improving_Driving.pdfakhileshakm
The document summarizes a systematic mapping study of mobile applications that use gamification and machine learning to improve driving behavior. Over 220 mobile apps were identified and analyzed based on their functionalities, collected data types, gamification elements, and machine learning techniques. The study aims to provide an overview of how these technologies can help reduce accidents by motivating safer driving habits.
2022- July Gamified_Mobile_Applications_for_Improving_Driving.pdfakhileshakm
The document summarizes a systematic mapping study of mobile applications that use gamification and machine learning to improve driving behavior. Over 220 mobile apps were identified and analyzed based on their functionalities, collected data types, gamification elements, and machine learning techniques. The study aims to provide an overview of how these technologies can help reduce accidents by motivating safer driving habits.
Personalized Driver Alerting System using object detectionIRJET Journal
The document describes a "Personalized Driver Alerting System using Object Detection" that aims to improve driving safety. The system uses Google TensorFlow for real-time object detection to instantly alert drivers when objects like pedestrians, vehicles or obstructions are detected in the vehicle's path. It analyzes the width of bounding boxes around detected objects to assess collision threat levels and determine the urgency of alerts. The system allows customizable alerts through various notification styles. The goals are to increase road safety by reducing collisions through advanced object recognition and threat analysis techniques.
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A Model for Car Plate Recognition & Speed Tracking (CPR-STS) using Machine Learning Algorithms
1. Aworinde Halleluyah Oluwatobi, Lala Olusegun Gbenga, Alamu, Femi Ololade, Abidoye, Itunuoluwa
Feranmi & Olayiwola, Adedayo Amos
Advances in Multimedia – An International Journal (AMIJ), Volume (6) : Issue (1) : 2020 1
A Model for Car Plate Recognition & Speed Tracking (CPR-STS)
using Machine Learning Algorithms
Aworinde, Halleluyah Oluwatobi aworinde.halleluyah@bowen.edu.ng
College of Computing & Communication Studies
Bowen University
Iwo, Nigeria
Lala, Olusegun Gbenga segun.lala@bowen.edu.ng
College of Computing & Communication Studies
Bowen University
Iwo, Nigeria
Alamu, Femi Ololade falamu@unilag.edu.ng
Department of Computer Sciences
University of Lagos
Lagos, Nigeria
Abidoye, Itunuoluwa Feranmi itunu221@gmail.com
Gems Consulting
Lagos, Nigeria
Olayiwola, Adedayo Amos adedayoolayiwola@gmail.com
Department of Computer Engineering
Ladoke Akintola University of Technology
Ogbomoso, Nigeria
Abstract
The transportation challenges experienced in major cities as a result of influx of people in search
of greener pastures is increasing on a daily basis. This results in an increase in the number of
cars plying and competing for driving space on narrow roads. Many drivers violate traffic laws as
a result of this and how to prosecute them without chasing them remains an issue to be
addressed. Therefore, this research presents a model that can be used to solve this challenge
using machine learning algorithms. The model consists of recognition modules such as image
acquisition, Gaussian blur, localization of car plate, character segmentation and optical character
recognition of car plate. K-NN Algorithm was used for training licensed plate font type spanning
A-Z and 0-9 while the speed tracking module used a camera which is automatically self-initiated
to track the speed of any moving object within its range of focus. The performance of the model
was evaluated using metrics such as recognition accuracy, positive prediction value, negative
prediction value, specificity and sensitivity. A tracking accuracy of 82% was achieved.
Keywords: Pattern Recognition, Car Plate Recognition, Speed Tracking, Optical Character
Recognition (OCR), Machine Learning, Image Processing.
1. INTRODUCTION
The demand for machines that can think and perform independently has constantly been a priority
on the list of human desires. This dates back to the ancient Greece when the idea of
programmable computers was first conceived [1]. Observers wondered if a time would come
when such computers would be able to reason and make decisions independently. Today artificial
intelligence (AI) as a thriving field with several practical application and active research areas has
witnessed steady growth and improvement in the concept of machine independence resulting
2. Aworinde Halleluyah Oluwatobi, Lala Olusegun Gbenga, Alamu, Femi Ololade, Abidoye, Itunuoluwa
Feranmi & Olayiwola, Adedayo Amos
Advances in Multimedia – An International Journal (AMIJ), Volume (6) : Issue (1) : 2020 2
from the creation of such systems. Scientist in various part of the world has particularly looked
into automating routine labor to reduce human effort, improve throughput and manage time [2].
Hence, in the early days of artificial intelligence, the field rapidly tackled and solved problems that
are intellectually and routine difficult for humans. As such, activities or jobs whose result and
success require a high level of accuracy but are relatively straight forward for computers served
as the foundational areas to invest in and improve upon [3]. Gathering knowledge from
experience and historical data has served as a basis for creating several solutions to tackle
various issues relating to routine tasks in different fields. Indeed, AI can boast of successful
implementation in Agriculture, Security, Fraud detections and prevention, Medicine,
manufacturing, sport and many more. In security, AI is not a new concept. Massive amount of
data in its various forms collected with the use of video cameras and sensors serve as input to
machine learning and security systems to advance machine learning and make systems and
devices smarter. Video analyzing, drones & robots, natural language processing, anomaly
detection and activity recognition are areas that have been incorporated into the security sector to
help improve the sector [4][5]. Recognizing the need to improve security on the university campus
and a desire to reduce the current challenges in ensuring security based on manual approach,
this research work proposes a technological approach which would automate security by
controlling access (Automated gate control) and improving surveillance using vehicle movement
logging around the campus by using Car plate recognition and speed tracking system (CPR-
STS).
2. RELATED WORKS
Machine learning powers many aspects of modern society from web searches to email spam and
malware filtering, social media services, product recommendations, online customer services and
fraud detection. Machine learning systems are used to identify objects in images, transcribe
speech into text, match news items, recommend products based on user’s interest and also
select relevant results of search [6]. Pattern recognition is the study of how machines can
observe the environment, learn to distinguish patterns of interest from their background, and
make effective decisions about the categories of the patterns [7][8]. A pattern could be a finger
print image, a handwritten cursive word, a human face or a speech signal. Automatic (machine)
recognition, description, classification and grouping of patterns are key issues that is constantly
been addressed in variety of disciplines where pattern recognition has been incorporated [9]. The
process of recognition and classification may consist of one of the following two tasks: supervised
classification and unsupervised classification depending on information availability [6][9]. The
design of pattern recognition system essentially involves the following three aspects: Data
Acquisition and preprocessing, data representation and decision-making. The problem domain
indicates the choice of sensors, prepossessing technique, representation scheme, and the
decision making model used. This result in several algorithms that can be used for the purpose of
pattern recognition. In this research K-Nearest Neighbor algorithm was used.
For several years, there has been an increasing interest among researchers in problems related
to extracting text from video or images. In the 1990s, significant advances in technology took
automatic car plate recognition systems from limited expensive, hard to set up, fixed based
applications to simple point and shoot mobile ones. This created a possibility of creating software
that can run on cheaper non-specialist hardware that did not require the pre-defined angles [10].
Car plate recognition (CPR) is a mass surveillance method that uses optical character recognition
on images to read vehicle registration plates. This task can be accomplished using a computer
system, a closed circuit or road-rule enforcement cameras or specially designed/dedicated
system. This system has been used for different functions which include improving police force
activities, electronic toll collection on pay-per-use roads and cataloguing the movement of traffic
or individuals. License plate recognition systems (LPRS) which was invented in 1976 is an image
process technology used to identify vehicles license plates by using Optical Character
Recognition (OCR) to read the Automatic Number Plate Recognition [11] [12]. Authors in [13]
proposed an automatic number plate recognition (ANPR) which is a method that catches the
vehicle image and confirm its licence number. ANPR was proposed to be used in the retrieval of
3. Aworinde Halleluyah Oluwatobi, Lala Olusegun Gbenga, Alamu, Femi Ololade, Abidoye, Itunuoluwa
Feranmi & Olayiwola, Adedayo Amos
Advances in Multimedia – An International Journal (AMIJ), Volume (6) : Issue (1) : 2020 3
stolen vehicle on the highway. In a related manner, [14] asserted that high level of precision is
required to recognize car plates when streets are occupied and a number of vehicles are passing
through. By optimizing different parameters, 98% exactness was accomplished in the
implementation. It is essential for tracking stolen vehicles and monitoring of vehicles to attain
100% exactness level. Also, issues like stains, blurred regions, smudges with various text style
and sizes should not be constraints. [15] explained an automatic number recognition system
using morphological operations, histogram manipulation and edge discovery for plate localization
and character segmentation.
Also authors in [16] and [17] described plate localization as an algorithm that is responsible for
finding and isolating the plate on the picture. In this case, the plate is focused on while
disregarding any extraneous data in the picture. Some applications of automatic license plate
recognition which include apprehension of high speeders by comparing the average time it takes
to get from a fixed camera, access control, border control, parking, tolling, stolen cars,
enforcement, traffic control, marketing tool, travel, identification of unauthorized vehicles among
others were highlighted in [18] and [19]. Authors in [17] however, outlined attendant benefit of
putting vehicle plate recognition system in place which include easier vehicle’s arrival/departure
to/from parking lot, preparing updated and instantaneous reports from the situation within the
parking lot, enhancing security in an area, facilitating traffic inflow/outflow during rush hours,
possibility of exerting smart control at access points and traffic signals, among others. In this
research, pattern recognition as a branch of artificial intelligence was used to build a car plate
recognition system which as well serve as a surveillance tool on campus. The system has an
add-on of being able to also track the speed of respective vehicles.
3. METHODOLOGY
The research adopts KNN algorithm and Open CV for its training, character recognition and a
speed/object tracking algorithm. The process of operation involves getting the image of a vehicle
passed into the system and then is processed through an already trained KNN algorithm with
character and numbers for recognition. The process includes: Pre-Processing, Plate Localization,
Segmentation, Feature Extraction/Character Analysis, Character Recognition, Output and
Validation. Open CV and KNN algorithm are fused together to achieve the aim of this work. The
reason for choice of this algorithms is due to their high degree of sensitivity of the local structure
of data. This design is divided into physical and logical representation. The logical design deals
with the identification of system functionality and how users interact with the system to make use
of these functionalities. Logically, the process starts with Car Registration, after which a Vehicle
Identification can be done, followed by number plate validation and speed Tracking. The
architectural framework which showed the units that make up the developed system and their
relationship is presented in Figure 1. The vehicle identification module was carried out by training
the acquired dataset with K-NN algorithm so that the model could identify any vehicle
approaching an access point; the dataset was stored into classification.txt and flattened_image.txt
in order to identify vehicles on selected frames (images). The K-NN classifier’s performance is
tested by varying number of training samples and k value. The recognition rate is calculated by
total number of recognized character divided by total number of character in all the images in
database. Embedded in the vehicle identification module is optical character recognition algorithm
that helps extract vehicle number plate from its image which goes through series of process such
as image acquisition, binarization, character segmentation and character recognition. Plate
localization involves finding the number plate in the image of the vehicle gotten which thereafter is
isolated for further process such as segmentation which does the work of separating the figures
and alphabets on the plate into their constituent parts thereby obtaining the characters
individually. The speed tracking module adopted object motion speed tracking system through the
Open CV library for its processes.
4. Aworinde Halleluyah Oluwatobi, Lala Olusegun Gbenga, Alamu, Femi Ololade, Abidoye, Itunuoluwa
Feranmi & Olayiwola, Adedayo Amos
Advances in Multimedia – An International Journal (AMIJ), Volume (6) : Issue (1) : 2020 4
Get Car Speed at line of
sight of the moving
Object and calculate the
speed of the car. If limit
is exceeded Print Out
ticket for car else
continue surveillance
Binarization
Character Analysis
Optical Character Recognition
(OCR)
9 KE Y87
User Data Capturing
Camera at the
point of car Entry
to capture plate
number
Vehicle
PlateNumberof
Vehicle
Pre-ProcessingStagesGrey Scale Image
Character Segmentation
Speed Tracking
System
Validation
Check if plate
number is present
in the Database or
not. Due to
decision , Entry is
Made
ImageAcquisition
DataBase
Validate Plate
Number
Vehicle and User
information is gotten If
Speed Limit is Exceeded
and a Ticket is Printed
Storing of user and Vehicle Details
Grant Entry to
car whose
plate number
is recognized
Sending and Retrieval of Data for Validation Process
Sending and Retrieval of Vehicle and User information
Admin
FIGURE 1: Architectural Framework of the Model.
The speed tracking module uses a camera which is automatically self-initiated to track the speed
of any moving object within its range of focus; the module thereafter stores record of the vehicles
at range and gives some information in a web view layout such as the screenshot of the vehicle
on motion, its speed in kilometer per hour (kmph), date and time taken.
5. Aworinde Halleluyah Oluwatobi, Lala Olusegun Gbenga, Alamu, Femi Ololade, Abidoye, Itunuoluwa
Feranmi & Olayiwola, Adedayo Amos
Advances in Multimedia – An International Journal (AMIJ), Volume (6) : Issue (1) : 2020 5
4. RESULTS AND DISCUSSION
The model recognizes vehicles that are already registered on the system and automatically either
allow or deny access by controlling the gate. Beyond gate access, the model as well has the
capability to monitor the speed of vehicles. At different part of the campus, movement of vehicles
are automatically logged into the system; this enable tracking of vehicles on campus.
4.1 Components of the Developed System
The implementation of the system is divided into the Web View and System Desktop Application.
The web layout consists of web pages such as the user login page (which grants access to
authorized and registered users), vehicle registration page, vehicles entry page etc.
The System desktop application is divided mainly into 3 modules
a) Vehicle Identification
b) Vehicle Authentication
c) Speed Tracking
Vehicle Identification
The vehicle identification module consists of algorithms fused together to help identify vehicles
entering into the school. Embedded in the vehicle identification module is the character
recognition module that helps extract vehicles number plate from its image as shown in Figure 2.
This module is made up of image acquisition, threshold binarization, character segmentation and
character recognition.
FIGURE 2: Vehicle Plate Identification.
Vehicle Authentication
The Vehicle Authentication section is the section which takes care of the authenticity of the
vehicle i.e. the database verification process. All vehicles in the school must have gone through
the registration phase with the admin and must have been registered through the web registration
page; only vehicles registered are allowed access into the school except otherwise as shown in
Figure 3.
Speed Tracking
The Speed Tracking module adopts the Object Motion Speed Tracking system which helps track
the speed of moving object i.e. cars moving at a particular speed range. This module uses the
Open CV library well enough in its processes. The speed tracking module uses a camera which is
launched by the module itself and tracks the speed of any moving object within its range of focus.
As shown in Figure 4, the module also stores record of the cars/ vehicles at range and gives
some information in a web view layout which are the Screenshot of the vehicle on motion, its
speed in kilometre per hour (kmh), date and time taken.
6. Aworinde Halleluyah Oluwatobi, Lala Olusegun Gbenga, Alamu, Femi Ololade, Abidoye, Itunuoluwa
Feranmi & Olayiwola, Adedayo Amos
Advances in Multimedia – An International Journal (AMIJ), Volume (6) : Issue (1) : 2020 6
FIGURE 3: Vehicle Authentication.
FIGURE 4: Speed Tracking Details.
4.2 Performance Evaluation
The performance evaluation of the system was carried out using accuracy, sensitivity, specificity,
positive prediction value, negative prediction value, false positive rate and false negative rate. All
these are a function of the True Positive (TP), False Positive (FP), True Negative (TN) and False
Negative (FN) values. TP measures the number of characters that were accurately recognized
and extracted as characters from the number plate. TN measures the number of non-characters
that were predicted as not characters. FN measures the number of characters in the number
plate that were predicted as not characters. FP measures the number of non-characters predicted
as characters.TP, TN, FP, and FN values obtained are: 41, 23, 6 and 3 respectively.
%)82(82.0
632318
41
FNFPTNTP
TNTP
Accuracy
%)75(75.0
24
18
FNTP
TP
ySensitivit
7. Aworinde Halleluyah Oluwatobi, Lala Olusegun Gbenga, Alamu, Femi Ololade, Abidoye, Itunuoluwa
Feranmi & Olayiwola, Adedayo Amos
Advances in Multimedia – An International Journal (AMIJ), Volume (6) : Issue (1) : 2020 7
%)88(88.0
26
23
FPTN
TN
ySpecificit
%)86(86.0
21
18
ValuePredictionPositive
FPTP
TP
%)79(79.0
29
23
ValuePredictionNegative
TNFN
TN
%1212.088.011RatePositiveFalse ySpecificit
%)25(25.0
24
6
RateNegativeFalse
TPFN
FN
Therefore, with a total number of 50 images with True Positive=18, True Negative=23, False
Positive=3, False Negative=6 which gives an Accuracy level of 82%, Sensitivity level of 75%.
Specificity level =88%, Positive Prediction Value of 86%, Negative Prediction Value of 79%, False
Positive Rate(FPR) of 12%, False Negative Rate(FNR) = 25%. With the FNR higher than the
FPR the system is said to be save for implementation.
5. CONCLUSION
This research has illustrated how vehicle number plates can be extracted from moving vehicle
images captured in real time. The implemented model will in no small measure proffer solution to
age long challenge of having long queues of vehicles at access points with limited personnel
attending to them; with this, less time will be wasted and vehicle overcrowding will be reduced to
the barest minimum. With the STS fraction of the model, cases of hit-and-run and injurious driving
at restricted zones will be curtailed and put in check.
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