scholarly journals Automated Attendance Monitoring System using Face Detection and RFID Cards

2020 ◽  
Vol 9 (8) ◽  
pp. 539-544
Keyword(s):  
Monitoring System ◽  
Face Detection ◽  
Radio Frequency Identification ◽  
Traditional Approach ◽  
Second Step ◽  
Automatic Process ◽  
Adaboost Algorithm ◽  
Cascade Classifiers ◽  
The Face ◽  
Frequency Identification

The attendance serves the most important role in the academic life of any student. Most of the colleges follow the traditional approach of attendance in which the professor speaks out student’s name and record attendance. For each lecture, this repetition of attendance calling is actually wastage of time and a time-taken procedure for calculating attendance of each student. Here an automatic process is proposed which is based on image processing with radio-frequency identification to avoid the losses. In this project approach, there is a use of face detection & RFID cards. Firstly, use the pre-processing step for the face detection and RFID receiver for the RFID cards counting and the second step is to detect, recognize and then the face is matched with stored images in the database. In this paper, viola-Jones algorithm is used for face detection, in which first step of integral image is used for feature computation and Adaboost algorithm is used for feature selection in second step. Then for discarding the non-faces, cascade classifiers is used in the third step of algorithm. The working of this project is to detect and recognize the face and RFID cards then mark the attendance for the corresponding face in the database on matching the face and unique number to the stored dataset. Face detection and RFID cards will be used as input and the attendance will be marked as output. This project is being conferred as a clarification for the “Automated attendance monitoring system.” Here a system of automatic face detection and recognition is proposed to mark the attendance automatically in database. This will save the time of person who is using traditional pen & paper based approach for attendance and hence is a solution for the automated attendance monitoring system. RFID cards are very helpful here for tracking or monitoring the student/teacher/employees within the campus. This system can be used in schools, colleges for students as well as for teachers also and it can be also used in companies, hospitals and malls for maintain records of accurate attendance of their employees.

A Realization of Face Detection System Based on ARM Linux

2013 ◽  
Vol 333-335 ◽  
pp. 864-867 ◽  
Author(s):  
Cong Ting Zhao ◽  
Hong Yun Wang ◽  
Jia Wei Li ◽  
Zi Lu Ying
Keyword(s):  
Embedded System ◽  
Monitoring System ◽  
Face Detection ◽  
Detection System ◽  
Detection Algorithm ◽  
Video Monitoring ◽  
Adaboost Algorithm ◽  
Arm Processor ◽  
The Face ◽  
Detection Effect

In order to adapt to the requirements of intelligent video monitoring system, this paper presents an ARM-Linux based video monitoring system for face detection. In this system, an ARM processor with a Linux operating system was used, and the USB camera was used to capture data, and then the face detection was conducted in the ARM device. The OpenCV library was transplanted to Linux embedded system. The algorithm of face detection was realized by calling the OpenCV library. Specially, adaboost algorithm was chose as the face detection algorithm. Experimental results show that the face detection effect of the system is satisfactory and can meet the real time requirement of video surveillance.

A RFID-Based Monitoring System for Abnormal Logistics Events in Internal Material Supply Chain

2011 ◽  
Vol 179-180 ◽  
pp. 949-954 ◽  
Author(s):  
Xiao Hua Cao ◽  
Juan Wan
Keyword(s):  
Supply Chain ◽  
Monitoring System ◽  
Radio Frequency Identification ◽  
Accurate Information ◽  
Prototype System ◽  
Rfid Technology ◽  
Material Management ◽  
Production Logistics ◽  
Material Supply ◽  
Frequency Identification

Internal material supply management for manufacturing workshops usually suffers from message delay and abnormal logistics events, which seriously holdback the reactivity capability of production system. As a rapid, real-time, accurate information collection tools, Radio Frequency identification (RFID) technology has become an important driver in the production and logistics activities. This paper presents a new idea that uses RFID technology to monitor real-timely the abnormal logistics events which occur at each work space in the internal material supply chain and proposes its construction method in details. With the experimental verification of prototype system, the proposed RFID-based monitoring system can find in time the abnormal logistics events of internal material supply chain and largely improve the circulation velocity of production logistics, and reduce the rate of mistake which frequently occurred in traditional material management based on Kanban.

Based on the Adaboost Algorithm of Face Detection Research

2014 ◽  
Vol 635-637 ◽  
pp. 985-988
Author(s):  
Wei Bo Yu ◽  
Lin Zhao ◽  
Wei Ming He
Keyword(s):  
Face Detection ◽  
Recognition System ◽  
Detection Algorithm ◽  
Detection Accuracy ◽  
Adaboost Algorithm ◽  
Complex Background ◽  
Complex Image ◽  
Face Recognition System ◽  
Lower Accuracy ◽  
The Face

Because of the influence of complex image background, illumination changes, facial rotation and some other factors, makes face detection in complex background is much more difficult, lower accuracy and slower speed. Adaboost algorithm was used for face detection, and implemented the test process in OpenCV. Face detection experiments were performed on images with facial rotation and complex background, the detection accuracy rate was 85% and 99% respectively, the average detection time of each picture was 16.67ms and 76ms.Experimental results show that the face detection algorithm can accurately and quickly realize face detection in complex background, and can satisfy the requirements of real-time face recognition system.

scholarly journals Rule Based Reasoning Untuk Monitoring Distribusi Bahan Bakar Minyak Secara Online dan Realtime menggunakan Radio Frequency Identification

2017 ◽  
Vol 7 (1) ◽  
pp. 39
Author(s):  
Mokhamad Iklil Mustofa
Keyword(s):  
Radio Frequency ◽  
Monitoring System ◽  
Radio Frequency Identification ◽  
Fuel Oil ◽  
Computer Application ◽  
Rule Base ◽  
Rule Based ◽  
Safety Stock ◽  
Frequency Identification ◽  
Radio Frequency Identification Technology

The scarcity of fuel oil in Indonesia often occurs due to delays in delivery caused by natural factors or transportation constraints. Theaim of this  research is to develop systems of fuel distribution monitoring online and realtime using rule base reasoning method and radio frequency identification technology. The rule-based reasoning method is used as a rule-based reasoning model used for monitoring distribution and determine rule-based safety stock. The monitoring system program is run with a web-based computer application. Radio frequency identification technology is used by utilizing radio waves as an media identification. This technology is used as a system of tracking and gathering information from objects automatically. The research data uses data of delayed distribution of fuel from fuel terminal to consumer. The monitoring technique uses the time of departure, the estimated time to arrive, the route / route passed by a fuel tanker attached to the radio frequency Identification tag. This monitoring system is carried out by the radio frequency identification reader connected online at any gas station or specified position that has been designed with study case in Semarang. The results of the research covering  the status of rule based reasoning that sends status, that is timely and appropriate paths, timely and truncated pathways, late and on track, late and cut off, and tank lost. The monitoring system is also used in determining the safety stock warehouse, with the safety stock value determined based on the condition of the stock warehouse rules.

Radio Frequency Identification as a Challenge to Informaiotn Security and Privacy

2008 ◽  
pp. 3848-3855
Author(s):  
Jorma Kajava ◽  
Juhani Anttila ◽  
Rauno Varonen
Keyword(s):  
Information Technology ◽  
Information Processing ◽  
Radio Frequency ◽  
Computer Architecture ◽  
Radio Frequency Identification ◽  
New Technology ◽  
Security And Privacy ◽  
Dark Side ◽  
The Face ◽  
Frequency Identification

New technology has continuously changed the face of computing, and each change has involved an improvement in computer architecture and information processing. There are strong indications that the next paradigm shift in information technology will be kicked off by tiny radio frequency identification (RFID) tags. These lowly devices are being ushered in by corporations like Wal-Mart to facilitate business logistics, but other uses are waiting in the wings. As usual with any technology, criminally-minded individuals have been quick to exploit smart tags for their own purposes. Thus, it is in place to take a look at the dark side of RFID technology to see how it may affect the security and privacy of citizens.

Distributed Monitoring

2013 ◽  
pp. 144-167
Author(s):  
Matthew Brundage ◽  
Anastasia Mavridou ◽  
James Johnson ◽  
Peter J. Hawrylak ◽  
Mauricio Papa
Keyword(s):  
Data Acquisition ◽  
Monitoring System ◽  
Radio Frequency Identification ◽  
Environmental Conditions ◽  
Distributed Monitoring ◽  
The World ◽  
Scada Systems ◽  
Frequency Identification ◽  
Intelligent Tools ◽  
And Control

SCADA systems monitor and control many critical installations around the world, interpreting information gathered from a multitude of resources to drive physical processes to a desired state. In order for the system to react correctly, the data it collects from sensors must be reliable, accurate, and timely, regardless of distance and environmental conditions. This chapter presents a framework for secure data acquisition in SCADA systems using a distributed monitoring solution. An overview of the framework is followed by a detailed description of a monitoring system designed specifically to improve the security posture and act as a first step towards more intelligent tools and operations. The architecture of the Smart Grid is used to analyze and evaluate benefits that the proposed monitoring system can provide. Finally, the effects and use of Radio Frequency Identification (RFID) and ZigBee as data acquisition platforms are discussed in the context of the proposed solution.

Multi-View Face Detection Based on Multi-Features AdaBoost Collaborative Learning Algorithm

2014 ◽  
Vol 998-999 ◽  
pp. 884-888
Author(s):  
Rong Bing Huang ◽  
Hong Zhang ◽  
Chang Ming Shu
Keyword(s):  
Collaborative Learning ◽  
Face Detection ◽  
Skin Color ◽  
Local Binary Pattern ◽  
Learning Algorithm ◽  
Standard Test ◽  
System Structure ◽  
Adaboost Algorithm ◽  
The Face ◽  
Candidate Regions

In View of the Multi-View Face Detection Problem under Complex Background, an Improved Face Detection Method Based on Multi-Features Boosting Collaborative Learning Algorithm Integrating Local Binary Pattern (LBP) is Presented. Firstly, Facial Skin Color Information is Used to Exclude most of the Background Regions. then, Haar-like Feature and LBP Feature are Extracted from Facial Candidate Regions and Inputted into a Modified Adaboost Algorithm to Obtain a Strong Classifier. Lastly, in Order to Improve the Detection Speed, Pyramid Classifier System Structure is Adopted to Determine the Face. the Experimental Results on CMU Standard Test Set and Life Photos, the Proposed Method has Achieved the Rapid Detection of Multi-View Face Image.

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