The purpose of this research is to implement a smart receptionist system with facial recognition and voice interaction using deep learning. The facial recognition component is implemented using real time image processing techniques, and it can be used to learn new faces as well as detect and recognize existing faces. The first time a customer uses this system, it will take the person’s facial data to create a unique user facial model, and this model will be triggered if the person comes the second time. The recognition is done in real time and after which voice interaction will be applied. Voice interaction is used to provide a life-like human communication and improve user experience. Our proposed smart receptionist system could be integrated into the self check-in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and provide customized user interactions. This system could also be used in smart home environment where smart cameras have been deployed and voice assistants are in place.
A Bring Your Own Device Risk Assessment ModelCSCJournals
Bring Your Own Device (BYOD), a technology where individuals or employees use their own devices on the organization’s network to perform tasks assigned to them by the organization has been widely embraced. The reasons for adoption are diverse in every organization. In spite of the security control strategies implemented by these organizations to safeguard their information resources, there has been an upsurge in information security breaches as a result of existing vulnerabilities in these systems and the legacy systems in use. Various approaches have been employed to deal with security challenges in BYOD, but according to literature, risk assessment has proved to be the first key step towards improving security of the BYOD environment in an enterprise. Risk assessment models have been proposed by various researchers, although, most are largely influenced by the degree of technological advancement and utilization as well as the working cultures within institutions. The existing models were largely developed in technologically advanced countries and thus do not fit well in developing countries. This study sought to develop flexible BYOD risk assessment model that can be adopted by varied institutions to secure their information resources. The study was carried out in Five (5) purposively selected state universities in Kenya. The research adopted a mixed research design approach with mixed sampling technique utilized to select the participants. Reliability and validity of data collection tools were evaluated and recommended by IT security and network experts. The qualitative and quantitative data was collected by interviewing experts and administering a questionnaire to sampled participants. The developed model was validated both statistically and by experts. The findings revealed that threats and vulnerabilities contributed to 39.9% and 69.2% respectively to the risk of the BYOD environment while Data Encryption (DE) and Software Updates (SU) came out strongly as intervening variables which have a major impact on the relationship between the dependent and independent variables.
A LITERATURE SURVEY AND ANALYSIS ON SOCIAL ENGINEERING DEFENSE MECHANISMS AND...IJNSA Journal
Social engineering attacks can be severe and hard to detect. Therefore, to prevent such attacks, organizations should be aware of social engineering defense mechanisms and security policies. To that end, the authors developed a taxonomy of social engineering defense mechanisms, designed a survey to measure employee awareness of these mechanisms, proposed a model of Social Engineering InfoSec Policies (SE-IPs), and designed a survey to measure the incorporation level of these SE-IPs. After analyzing the data from the first survey, the authors found that more than half of employees are not aware of social engineering attacks. The paper also analyzed a second set of survey data, which found that on average, organizations incorporated just over fifty percent of the identified formal SE-IPs. Such worrisome results show that organizations are vulnerable to social engineering attacks, and serious steps need to be taken to elevate awareness against these emerging security threats.
Hazards of Biometric Authentication in PracticeITIIIndustries
With the increase in cyber threats and attacks many institutions are exploring how newer technologies may be applied to strengthen the way users are verified when bestowing permissions for carrying out web transactions. In particular, many institutions are under increasing pressure to improve the security instruments used to authenticate users, while permitting access to their personal records to approve transactions. Whilst multifactor authentication protocols have been adopted to validate more sensitive transactions, this has added an additional physical interaction during the verification process. More recently, the industry has turned its attention to the use of biometric authentication as a way to securely verify user identities. This has reduced the complexity associated with existing authentication processes that require passwords, tokens, and challenge-response keywords. This paper explores these new authentication techniques, discussing the benefits while highlighting the challenges in practice to using biometrics. In particular, identity theft of biometric markers and its potential impact to customers and liability challenges for institutions are presented.
Trusting Smart Speakers: Understanding the Different Levels of Trust between ...CSCJournals
The growing usage of smart speakers raises many privacy and trust concerns compared to other technologies such as smart phones and computers. In this study, a proxy measure of trust is used to gauge users’ opinions on three different technologies based on an empirical study, and to understand which technology most people are most likely to trust. The collected data were analyzed using the Kruskal-Wallis H test to determine the statistical differences between the users’ trust level of the three technologies: smart speaker, computer and smart phone. The findings of the study revealed that despite the wide acceptance, ease of use and reputation of smart speakers, people find it difficult to trust smart speakers with their sensitive information via the Direct Voice Input (DVI) and would prefer to use a keyboard or touchscreen offered by computers and smart phones. Findings from this study can inform future work on users’ trust in technology based on perceived ease of use, reputation, perceived credibility and risk of using technologies via DVI.
Top cited managing information technology articlesIJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental.
A Bring Your Own Device Risk Assessment ModelCSCJournals
Bring Your Own Device (BYOD), a technology where individuals or employees use their own devices on the organization’s network to perform tasks assigned to them by the organization has been widely embraced. The reasons for adoption are diverse in every organization. In spite of the security control strategies implemented by these organizations to safeguard their information resources, there has been an upsurge in information security breaches as a result of existing vulnerabilities in these systems and the legacy systems in use. Various approaches have been employed to deal with security challenges in BYOD, but according to literature, risk assessment has proved to be the first key step towards improving security of the BYOD environment in an enterprise. Risk assessment models have been proposed by various researchers, although, most are largely influenced by the degree of technological advancement and utilization as well as the working cultures within institutions. The existing models were largely developed in technologically advanced countries and thus do not fit well in developing countries. This study sought to develop flexible BYOD risk assessment model that can be adopted by varied institutions to secure their information resources. The study was carried out in Five (5) purposively selected state universities in Kenya. The research adopted a mixed research design approach with mixed sampling technique utilized to select the participants. Reliability and validity of data collection tools were evaluated and recommended by IT security and network experts. The qualitative and quantitative data was collected by interviewing experts and administering a questionnaire to sampled participants. The developed model was validated both statistically and by experts. The findings revealed that threats and vulnerabilities contributed to 39.9% and 69.2% respectively to the risk of the BYOD environment while Data Encryption (DE) and Software Updates (SU) came out strongly as intervening variables which have a major impact on the relationship between the dependent and independent variables.
A LITERATURE SURVEY AND ANALYSIS ON SOCIAL ENGINEERING DEFENSE MECHANISMS AND...IJNSA Journal
Social engineering attacks can be severe and hard to detect. Therefore, to prevent such attacks, organizations should be aware of social engineering defense mechanisms and security policies. To that end, the authors developed a taxonomy of social engineering defense mechanisms, designed a survey to measure employee awareness of these mechanisms, proposed a model of Social Engineering InfoSec Policies (SE-IPs), and designed a survey to measure the incorporation level of these SE-IPs. After analyzing the data from the first survey, the authors found that more than half of employees are not aware of social engineering attacks. The paper also analyzed a second set of survey data, which found that on average, organizations incorporated just over fifty percent of the identified formal SE-IPs. Such worrisome results show that organizations are vulnerable to social engineering attacks, and serious steps need to be taken to elevate awareness against these emerging security threats.
Hazards of Biometric Authentication in PracticeITIIIndustries
With the increase in cyber threats and attacks many institutions are exploring how newer technologies may be applied to strengthen the way users are verified when bestowing permissions for carrying out web transactions. In particular, many institutions are under increasing pressure to improve the security instruments used to authenticate users, while permitting access to their personal records to approve transactions. Whilst multifactor authentication protocols have been adopted to validate more sensitive transactions, this has added an additional physical interaction during the verification process. More recently, the industry has turned its attention to the use of biometric authentication as a way to securely verify user identities. This has reduced the complexity associated with existing authentication processes that require passwords, tokens, and challenge-response keywords. This paper explores these new authentication techniques, discussing the benefits while highlighting the challenges in practice to using biometrics. In particular, identity theft of biometric markers and its potential impact to customers and liability challenges for institutions are presented.
Trusting Smart Speakers: Understanding the Different Levels of Trust between ...CSCJournals
The growing usage of smart speakers raises many privacy and trust concerns compared to other technologies such as smart phones and computers. In this study, a proxy measure of trust is used to gauge users’ opinions on three different technologies based on an empirical study, and to understand which technology most people are most likely to trust. The collected data were analyzed using the Kruskal-Wallis H test to determine the statistical differences between the users’ trust level of the three technologies: smart speaker, computer and smart phone. The findings of the study revealed that despite the wide acceptance, ease of use and reputation of smart speakers, people find it difficult to trust smart speakers with their sensitive information via the Direct Voice Input (DVI) and would prefer to use a keyboard or touchscreen offered by computers and smart phones. Findings from this study can inform future work on users’ trust in technology based on perceived ease of use, reputation, perceived credibility and risk of using technologies via DVI.
Top cited managing information technology articlesIJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental.
Malware threat analysis techniques and approaches for IoT applications: a reviewjournalBEEI
Internet of things (IoT) is a concept that has been widely used to improve business efficiency and customer’s experience. It involves resource constrained devices connecting to each other with a capability of sending data, and some with receiving data at the same time. The IoT environment enhances user experience by giving room to a large number of smart devices to connect and share information. However, with the sophistication of technology has resulted in IoT applications facing with malware threat. Therefore, it becomes highly imperative to give an understanding of existing state-of-the-art techniques developed to address malware threat in IoT applications. In this paper, we studied extensively the adoption of static, dynamic and hybrid malware analyses in proffering solution to the security problems plaguing different IoT applications. The success of the reviewed analysis techniques were observed through case studies from smart homes, smart factories, smart gadgets and IoT application protocols. This study gives a better understanding of the holistic approaches to malware threats in IoT applications and the way forward for strengthening the protection defense in IoT applications.
A Multimedia Data Mining Framework for Monitoring E-Examination Environmentijma
Academic dishonesty has been a growing concern in e-learning environment due to the fact that eexamination takes place under supervised and unsupervised learning environment despite its huge advantages. The e-examination environment has faced various security breaches such as academic dishonesty (impersonation), identity theft, unauthorised access and illegal assistance as a result of inefficient measures employed. Hence, an efficient framework which will aid the monitoring of the eexamination is needed. This paper reviews the process of mining multimedia data and propose a framework for monitoring the e-examination environment in order to extract images and audio features. The framework has four major phases: data pre-processing, mining, association and post processing. The
pre-processing phases carries out the extraction and transformation of multimedia data features, the mining phase does the classification and clustering of these features, the association does pattern matching while the post processing carries out the knowledge interpretation and reporting. The approach presented in this study will allow for efficient and accurate monitoring of e-examination environment which will help provide adequate security and reduce unethical behaviour in e-examination environment.
Face Recognition Based Attendance System using Machine LearningYogeshIJTSRD
In the era of modern technologies emerging at rapid pace there is no reason why a crucial event in education sector such as attendance should be done in the old boring traditional way. Attendance monitoring system will save a lot of time and energy for the both parties teaching staff as well as the students. Attendance will be monitored by the face recognition algorithm by recognizing only the face of the students from the rest of the objects and then marking the students as present. The system will be pre feed with the images of all the students enrolled in the class and with the help of this pre feed data the algorithm will detect the students who are present and match the features with the already saved images of the students in the database. Benazir Begum A | Sreeyuktha R | Haritha M P | Vishnuprasad "Face Recognition Based Attendance System using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39856.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/39856/face-recognition-based-attendance-system-using-machine-learning/benazir-begum-a
An Overview on Authentication Approaches and Their Usability in Conjunction w...IJERA Editor
The usage of sensitive online services and applications such as online banking, e-commerce etc is increasing day by day. These technologies have tremendously improved making our daily life easier. However, these developments have been accompanied by E-piracy where attackers try to get access to services illegally. As sensitive information flow through Internet, they need support for security properties such as authentication, authorization, data confidentiality. Perhaps static password (User ID & password) is the most common and widely accepted authentication method. Online applications need strong password such as a combination of alphanumeric with special characters. In general, having one password for a single service may be easy to remember, but controlling many passwords for different services poses a tedious task on users online applications . Usually users try to use same password for different services or make slight changes in the password which can be easy for attacker to guess adding increased security threat. In order to overcome this, stronger authentication solutions need to be suggested and adapted for services based network.
THE PROPOSED IMPLEMENTATION OF RFID BASED ATTENDANCE SYSTEM ijseajournal
Recent trends in Information and Communication Technology (ICT) embrace several smartphone applications in a variety of educational and industrial domains in the last several years. This research focuses to solve one of the promising problems of an educational domain to take attendance smartly using the Radio Frequency Identification (RFID) system. Current attendance system in King Abdul-Aziz University (KAU) Saudi Arabia is partly solving the attendance problem. There are several problems in the existing attendance systems such as time-consuming, the chance of mistakes, truancy issues, no contact with parent/guardian and not efficient because of roll call as taking manual attendance. The proposed RFID based attendance system will provide robust, secure and automatic attendance. The proposed system will use modern technology and support to institutions and parents to deal with most of the problems of existing attendance systems. There are several other benefits of RFID based system such as web-based and mobile interfaces, daily absent report, an automatic SMS alert to parent/guardian, reduce administrative work, improve the ratio of attendance, economical and highly efficient. The case study method will be used as a research design. The proposed system is developed and tested in KAU Saudi Arabia. The proposed system will have both web and mobile interfaces. The web interface will need the Internet to access the proposed system and the mobile interface will use the Android platform for the testing scenarios. The user will access the system to generate customized reports to review the status of students for a particular course. It is anticipated that the proposed system will significantly improve students’ monitoring mechanisms hence enabling both parents and teachers in making appropriate decisions.
Interactive Technologies for Improving Quality of Education to Build Collabor...ijsrd.com
Today with advancement in Information Communication Technology (ICT) the way the education is being delivered is seeing a paradigm shift from boring classroom lectures to interactive applications such as 2-D and 3-D learning content, animations, live videos, response systems, interactive panels, education games, virtual laboratories and collaborative research (data gathering and analysis) etc. Engineering is emerging with more innovative solutions in the field of education and bringing out their innovative products to improve education delivery. The academic institutes which were once hesitant to use such technology are now looking forward to such innovations. They are adopting the new ways as they are realizing the vast benefits of using such methods and technology. The benefits are better comprehensibility, improved learning efficiency of students, and access to vast knowledge resources, geographical reach, quick feedback, accountability and quality research. This paper focuses on how engineering can leverage the latest technology and build a collaborative learning environment which can then be integrated with the national e-learning grid.
Anomaly Threat Detection System using User and Role-Based Profile Assessmentijtsrd
In network security the organizations are ever-growing to identify insider threats. Those who have authorized access to sensitive organizational data are placed in a position of power that could well be abused and could cause significant damage to an organization. Traditional intrusion detection systems are neither designed nor capable of identifying those who act maliciously within an organization. We describe an automated system that is capable of detecting insider threats within an organization. We define a tree-structure profiling approach that incorporates the details of activities conducted by each user and each job role and then use this to obtain a consistent representation of features that provide a rich description of the users behavior. Deviation can be assessed based on the amount of variance that each user exhibits across multiple attributes, compared against their peers. We have performed experimentation using that the system can identify anomalous behavior that may be indicative of a potential threat. We also show how our detection system can be combined with visual analytics tools to support further investigation by an analyst. U. Indumathy | M. Nivedha | Mrs. K. Alice"Anomaly Threat Detection System using User and Role-Based Profile Assessment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd10956.pdf http://www.ijtsrd.com/engineering/computer-engineering/10956/anomaly-threat-detection-system-using-user-and-role-based-profile-assessment/u-indumathy
SMART AGENT BASED SEARCH FOR ADMISSION IN INSTITUTIONS OF HIGHER LEARNINGIJITE
Early admission systems saw people applying to universities by filling out applications forms and placing
them in suitable envelopes and sending them through the local postal agency. This was not considered to
be cost or time effective, and this method was also not efficient. This system however needed some
improvement due to the huge workload on administrators. So researchers and software developers
improved the system so that between 1999 and 2008 application and admission was done via the Internet.
Also many Ranking system like ARWU, shanghai etc. been used for ranking the universities and colleges
around the world which would enable people choosing the universities and colleges for education on
factors like publication, funding, infrastructure and so.
The Internet has already brought the humans together in a new, exciting, and unexpected ways, and the
same is also happening to our prevalent adoption of digital mobile devices that has paved the way for the
development of many innovative applications in the commercial domain. While considering such mobile
devices for an application towards higher education in an educational institution, there has been some
amount of work done using intelligent agents. But still those agent based systems got some drawbacks
which motivated towards developing the present Agent based system to provide Smart agent based system
for higher Learning search not in Jamaican context alone but also elsewhere with these drawbacks
alleviated. The agents developed will be based on using fuzzy preference rules and heuristics, to make
accurate decisions based on the user’s criteria or specifications using JADE-LEAP on Android handset.
The system got Google map feature, intelligence in admission system and also warning for universities
with low rating. These findings of this research will be presented as screenshots.
Information Technology of Metro (MCC)- TQMSalma Bashir
METRO Cash & Carry, international market leader in self-service wholesale, plans its market entry into Pakistan. With this move, the retailer would expand both its international presence and its activities in the important growth region Asia.
Smart information desk system with voice assistant for universities IJECEIAES
This article aims to develop a smart information desk system through a smart mirror for universities. It is a mirror with extra capabilities of displaying answers for academic inquiries such as asking about the lecturers’ office numbers and hours, exams dates and times on the mirror surface. In addition, the voice recognition feature was used to answer spoken inquiries in audio responds to serve all types of users including disabled ones. Furthermore, the system showed general information such as date, weather, time and the university map. The smart mirror was connected to an outdoor camera to monitor the traffics at the university entrance gate. The system was implemented on a Raspberry Pi 4 model B connected to a two-way mirror and an infrared (IR) touch frame. The results of this study helped to overcome the problem of the information desk absence in the university. Therefore, it helped users to save their time and effort in making requests for important academic information.
"Attendance Management System bridges the effective communication between students, teachers, and parents by keep them notified about their wards' attendance via Email or SMS.
A.T.S.I. offers best biometric attendance management system, face recognition attendance system, fingerprint based attendance system, and RFID based attendance system and gives flexibility to institutions to choose the suitable system for them."
SYSTEM END-USER ACTIONS AS A THREAT TO INFORMATION SYSTEM SECURITYIJNSA Journal
As universities migrate online due to the advent of Covid-19, there is a need for enhanced security in information systems in the institution of higher learning. Many opted to invest in technological approaches to mitigate cybersecurity threats; however, the most common types of cybersecurity breaches happen due to the human factor, well known as end-user error or actions. Thus, this study aimed to identify and explore possible end-user errors in academia and the resulting vulnerabilities and threats that could affect the integrity of the university's information system. The study further presented state-of-the-art humanoriented security threats countermeasures to compliment universities' cybersecurity plans. Countermeasures include well-tailored ICT policies, incident response procedures, and education to protect themselves from security events (disruption, distortion, and exploitation). Adopted is a mixedmethod research approach with a qualitative research design to guide the study. An open-ended questionnaire and semi-structured interviews were used as data collection tools. Findings showed that system end-user errors remain the biggest security threat to information systems security in institutions of higher learning. Indeed errors make information systems vulnerable to certain cybersecurity attacks and, when exploited, put legitimate users, institutional network, and its computers at risk of contracting viruses, worms, Trojan, and expose it to spam, phishing, e-mail fraud, and other modern security attacks such as DDoS, session hijacking, replay attack and many more. Understanding that technology has failed to fully protect systems, specific recommendations are provided for the institution of higher education to consider improving employee actions and minimizing security incidents in their eLearning platforms, post Covid-19.
Attendance management system using face recognitionIAESIJAI
Traditional attendance systems consist of registers marked by teachers, leading to human error and a lot of maintenance. Time consumption is a key point in this system. We wanted to revolutionize the digital tools available in today's time i.e., facial recognition. This project has revolutionized to overcome the problems of the traditional system. Face recognition and marking the present is our project. A database of all students in the class is kept in single folder, and attendance is marked if each student's face matches with one of the stored faces. Otherwise, the face is ignored and not marked for attendance. In our project, face detection (machine learning) is used.
Globally, the presence of biometrics is highly approachable to fix any hurdle and irrelevant input and make a secure and tangible environment. Indeed biometrics helps you tremendously. You can manage everything on your basis to compete in the market. Especially for the attendance services in any organization, office, and building, it is the most important thing to record the presence of someone.
Malware threat analysis techniques and approaches for IoT applications: a reviewjournalBEEI
Internet of things (IoT) is a concept that has been widely used to improve business efficiency and customer’s experience. It involves resource constrained devices connecting to each other with a capability of sending data, and some with receiving data at the same time. The IoT environment enhances user experience by giving room to a large number of smart devices to connect and share information. However, with the sophistication of technology has resulted in IoT applications facing with malware threat. Therefore, it becomes highly imperative to give an understanding of existing state-of-the-art techniques developed to address malware threat in IoT applications. In this paper, we studied extensively the adoption of static, dynamic and hybrid malware analyses in proffering solution to the security problems plaguing different IoT applications. The success of the reviewed analysis techniques were observed through case studies from smart homes, smart factories, smart gadgets and IoT application protocols. This study gives a better understanding of the holistic approaches to malware threats in IoT applications and the way forward for strengthening the protection defense in IoT applications.
A Multimedia Data Mining Framework for Monitoring E-Examination Environmentijma
Academic dishonesty has been a growing concern in e-learning environment due to the fact that eexamination takes place under supervised and unsupervised learning environment despite its huge advantages. The e-examination environment has faced various security breaches such as academic dishonesty (impersonation), identity theft, unauthorised access and illegal assistance as a result of inefficient measures employed. Hence, an efficient framework which will aid the monitoring of the eexamination is needed. This paper reviews the process of mining multimedia data and propose a framework for monitoring the e-examination environment in order to extract images and audio features. The framework has four major phases: data pre-processing, mining, association and post processing. The
pre-processing phases carries out the extraction and transformation of multimedia data features, the mining phase does the classification and clustering of these features, the association does pattern matching while the post processing carries out the knowledge interpretation and reporting. The approach presented in this study will allow for efficient and accurate monitoring of e-examination environment which will help provide adequate security and reduce unethical behaviour in e-examination environment.
Face Recognition Based Attendance System using Machine LearningYogeshIJTSRD
In the era of modern technologies emerging at rapid pace there is no reason why a crucial event in education sector such as attendance should be done in the old boring traditional way. Attendance monitoring system will save a lot of time and energy for the both parties teaching staff as well as the students. Attendance will be monitored by the face recognition algorithm by recognizing only the face of the students from the rest of the objects and then marking the students as present. The system will be pre feed with the images of all the students enrolled in the class and with the help of this pre feed data the algorithm will detect the students who are present and match the features with the already saved images of the students in the database. Benazir Begum A | Sreeyuktha R | Haritha M P | Vishnuprasad "Face Recognition Based Attendance System using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd39856.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/39856/face-recognition-based-attendance-system-using-machine-learning/benazir-begum-a
An Overview on Authentication Approaches and Their Usability in Conjunction w...IJERA Editor
The usage of sensitive online services and applications such as online banking, e-commerce etc is increasing day by day. These technologies have tremendously improved making our daily life easier. However, these developments have been accompanied by E-piracy where attackers try to get access to services illegally. As sensitive information flow through Internet, they need support for security properties such as authentication, authorization, data confidentiality. Perhaps static password (User ID & password) is the most common and widely accepted authentication method. Online applications need strong password such as a combination of alphanumeric with special characters. In general, having one password for a single service may be easy to remember, but controlling many passwords for different services poses a tedious task on users online applications . Usually users try to use same password for different services or make slight changes in the password which can be easy for attacker to guess adding increased security threat. In order to overcome this, stronger authentication solutions need to be suggested and adapted for services based network.
THE PROPOSED IMPLEMENTATION OF RFID BASED ATTENDANCE SYSTEM ijseajournal
Recent trends in Information and Communication Technology (ICT) embrace several smartphone applications in a variety of educational and industrial domains in the last several years. This research focuses to solve one of the promising problems of an educational domain to take attendance smartly using the Radio Frequency Identification (RFID) system. Current attendance system in King Abdul-Aziz University (KAU) Saudi Arabia is partly solving the attendance problem. There are several problems in the existing attendance systems such as time-consuming, the chance of mistakes, truancy issues, no contact with parent/guardian and not efficient because of roll call as taking manual attendance. The proposed RFID based attendance system will provide robust, secure and automatic attendance. The proposed system will use modern technology and support to institutions and parents to deal with most of the problems of existing attendance systems. There are several other benefits of RFID based system such as web-based and mobile interfaces, daily absent report, an automatic SMS alert to parent/guardian, reduce administrative work, improve the ratio of attendance, economical and highly efficient. The case study method will be used as a research design. The proposed system is developed and tested in KAU Saudi Arabia. The proposed system will have both web and mobile interfaces. The web interface will need the Internet to access the proposed system and the mobile interface will use the Android platform for the testing scenarios. The user will access the system to generate customized reports to review the status of students for a particular course. It is anticipated that the proposed system will significantly improve students’ monitoring mechanisms hence enabling both parents and teachers in making appropriate decisions.
Interactive Technologies for Improving Quality of Education to Build Collabor...ijsrd.com
Today with advancement in Information Communication Technology (ICT) the way the education is being delivered is seeing a paradigm shift from boring classroom lectures to interactive applications such as 2-D and 3-D learning content, animations, live videos, response systems, interactive panels, education games, virtual laboratories and collaborative research (data gathering and analysis) etc. Engineering is emerging with more innovative solutions in the field of education and bringing out their innovative products to improve education delivery. The academic institutes which were once hesitant to use such technology are now looking forward to such innovations. They are adopting the new ways as they are realizing the vast benefits of using such methods and technology. The benefits are better comprehensibility, improved learning efficiency of students, and access to vast knowledge resources, geographical reach, quick feedback, accountability and quality research. This paper focuses on how engineering can leverage the latest technology and build a collaborative learning environment which can then be integrated with the national e-learning grid.
Anomaly Threat Detection System using User and Role-Based Profile Assessmentijtsrd
In network security the organizations are ever-growing to identify insider threats. Those who have authorized access to sensitive organizational data are placed in a position of power that could well be abused and could cause significant damage to an organization. Traditional intrusion detection systems are neither designed nor capable of identifying those who act maliciously within an organization. We describe an automated system that is capable of detecting insider threats within an organization. We define a tree-structure profiling approach that incorporates the details of activities conducted by each user and each job role and then use this to obtain a consistent representation of features that provide a rich description of the users behavior. Deviation can be assessed based on the amount of variance that each user exhibits across multiple attributes, compared against their peers. We have performed experimentation using that the system can identify anomalous behavior that may be indicative of a potential threat. We also show how our detection system can be combined with visual analytics tools to support further investigation by an analyst. U. Indumathy | M. Nivedha | Mrs. K. Alice"Anomaly Threat Detection System using User and Role-Based Profile Assessment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd10956.pdf http://www.ijtsrd.com/engineering/computer-engineering/10956/anomaly-threat-detection-system-using-user-and-role-based-profile-assessment/u-indumathy
SMART AGENT BASED SEARCH FOR ADMISSION IN INSTITUTIONS OF HIGHER LEARNINGIJITE
Early admission systems saw people applying to universities by filling out applications forms and placing
them in suitable envelopes and sending them through the local postal agency. This was not considered to
be cost or time effective, and this method was also not efficient. This system however needed some
improvement due to the huge workload on administrators. So researchers and software developers
improved the system so that between 1999 and 2008 application and admission was done via the Internet.
Also many Ranking system like ARWU, shanghai etc. been used for ranking the universities and colleges
around the world which would enable people choosing the universities and colleges for education on
factors like publication, funding, infrastructure and so.
The Internet has already brought the humans together in a new, exciting, and unexpected ways, and the
same is also happening to our prevalent adoption of digital mobile devices that has paved the way for the
development of many innovative applications in the commercial domain. While considering such mobile
devices for an application towards higher education in an educational institution, there has been some
amount of work done using intelligent agents. But still those agent based systems got some drawbacks
which motivated towards developing the present Agent based system to provide Smart agent based system
for higher Learning search not in Jamaican context alone but also elsewhere with these drawbacks
alleviated. The agents developed will be based on using fuzzy preference rules and heuristics, to make
accurate decisions based on the user’s criteria or specifications using JADE-LEAP on Android handset.
The system got Google map feature, intelligence in admission system and also warning for universities
with low rating. These findings of this research will be presented as screenshots.
Information Technology of Metro (MCC)- TQMSalma Bashir
METRO Cash & Carry, international market leader in self-service wholesale, plans its market entry into Pakistan. With this move, the retailer would expand both its international presence and its activities in the important growth region Asia.
Smart information desk system with voice assistant for universities IJECEIAES
This article aims to develop a smart information desk system through a smart mirror for universities. It is a mirror with extra capabilities of displaying answers for academic inquiries such as asking about the lecturers’ office numbers and hours, exams dates and times on the mirror surface. In addition, the voice recognition feature was used to answer spoken inquiries in audio responds to serve all types of users including disabled ones. Furthermore, the system showed general information such as date, weather, time and the university map. The smart mirror was connected to an outdoor camera to monitor the traffics at the university entrance gate. The system was implemented on a Raspberry Pi 4 model B connected to a two-way mirror and an infrared (IR) touch frame. The results of this study helped to overcome the problem of the information desk absence in the university. Therefore, it helped users to save their time and effort in making requests for important academic information.
"Attendance Management System bridges the effective communication between students, teachers, and parents by keep them notified about their wards' attendance via Email or SMS.
A.T.S.I. offers best biometric attendance management system, face recognition attendance system, fingerprint based attendance system, and RFID based attendance system and gives flexibility to institutions to choose the suitable system for them."
SYSTEM END-USER ACTIONS AS A THREAT TO INFORMATION SYSTEM SECURITYIJNSA Journal
As universities migrate online due to the advent of Covid-19, there is a need for enhanced security in information systems in the institution of higher learning. Many opted to invest in technological approaches to mitigate cybersecurity threats; however, the most common types of cybersecurity breaches happen due to the human factor, well known as end-user error or actions. Thus, this study aimed to identify and explore possible end-user errors in academia and the resulting vulnerabilities and threats that could affect the integrity of the university's information system. The study further presented state-of-the-art humanoriented security threats countermeasures to compliment universities' cybersecurity plans. Countermeasures include well-tailored ICT policies, incident response procedures, and education to protect themselves from security events (disruption, distortion, and exploitation). Adopted is a mixedmethod research approach with a qualitative research design to guide the study. An open-ended questionnaire and semi-structured interviews were used as data collection tools. Findings showed that system end-user errors remain the biggest security threat to information systems security in institutions of higher learning. Indeed errors make information systems vulnerable to certain cybersecurity attacks and, when exploited, put legitimate users, institutional network, and its computers at risk of contracting viruses, worms, Trojan, and expose it to spam, phishing, e-mail fraud, and other modern security attacks such as DDoS, session hijacking, replay attack and many more. Understanding that technology has failed to fully protect systems, specific recommendations are provided for the institution of higher education to consider improving employee actions and minimizing security incidents in their eLearning platforms, post Covid-19.
Attendance management system using face recognitionIAESIJAI
Traditional attendance systems consist of registers marked by teachers, leading to human error and a lot of maintenance. Time consumption is a key point in this system. We wanted to revolutionize the digital tools available in today's time i.e., facial recognition. This project has revolutionized to overcome the problems of the traditional system. Face recognition and marking the present is our project. A database of all students in the class is kept in single folder, and attendance is marked if each student's face matches with one of the stored faces. Otherwise, the face is ignored and not marked for attendance. In our project, face detection (machine learning) is used.
Globally, the presence of biometrics is highly approachable to fix any hurdle and irrelevant input and make a secure and tangible environment. Indeed biometrics helps you tremendously. You can manage everything on your basis to compete in the market. Especially for the attendance services in any organization, office, and building, it is the most important thing to record the presence of someone.
AI Approach for Iris Biometric Recognition Using a Median FilterNIDHI SHARMA
The Artificial Intelligence approach is used for Iris recognition by understanding the distinctive and measurable characteristics of the human body such as a person’s face, iris, DNA, fingerprints, etc. AI methods analyzed the attributes like iris images. Privacy and Security being a major concern nowadays, Recognition Technique can find numerous applications.
Face Recognition Based Automated Student Attendance Systemijtsrd
Face recognition system is very beneficial in real time applications, concentrated in security control systems. Face Detection and Recognition is a vital area in the province of validation. In this project, the Open CV based face recognition strategy has been proposed. This model integrates a camera that captures an input image, an algorithm Haar Cascade Algorithm for detecting face from an input image, identifying the face and marking the attendance in an excel sheet. The proposed system implements features such as detection of faces, extraction of the features, exposure of extracted features, analysis of students attendance, and monthly attendance report generation. Faces are recognized using advanced LBP using the database that contains images of students and is used to identify students using the captured image. Better precision is accomplished in results and the system takes into account the changes that occurs in the face over some time. Ms. Pranitha Prabhakar | Mr. Kathireshan "Face Recognition Based Automated Student Attendance System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-1 , December 2020, URL: https://www.ijtsrd.com/papers/ijtsrd38083.pdf Paper URL : https://www.ijtsrd.com/computer-science/other/38083/face-recognition-based-automated-student-attendance-system/ms-pranitha-prabhakar
HMM-Based Face Recognition System with SVD Parameterijtsrd
Today an increasing digital world, personal reliable authentication has become an important human Computer interface activity. It is very important to establish a persons identity. In today existing security mainly depends on passwords, swipe cards or token based approach and attitude to control access to physical and virtual spaces passport. Universal, such as methods, although very secure. Such as tokens, badges and access cards can be shared or stolen. Passwords and PIN numbers can be also stolen electronically. In addition, they cannot distinguish between authentic have access to or knowledge of the user and tokens. To make a system more secure and simple with the use of biometric authentication system such as face and hand gesture recognition for personal authentication. So in this paper, A Hidden Markov Model (HMM) based face recognition system using Singular Value Decomposition (SVD) is proposed. Neha Rana | Bhavna Pancholi"HMM-Based Face Recognition System with SVD Parameter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd12938.pdf http://www.ijtsrd.com/engineering/electrical-engineering/12938/hmm-based-face-recognition-system-with-svd-parameter/neha-rana
The home security system has become vital for every house. Previously, most doors can be open by using traditional ways, such as keys, security cards, password or pattern. However, incidents such as a key loss has led to much worrying cases such as robbery and identity fraud. This has become a significant issue. To overcome this problem, face recognition using deep learning technique was introduced and Internet of Thing (IoT) also been used to perform efficient door access control system. Raspberry Pi is a programmable small computer board and used as the main controller for face recognition, youth system and locking system. The camera is used to capture images of the person in front of the door. IoT system enables the user to control the door access.
This documentation provides a brief insight of face recognition based attendance system using neural networks in terms of product architecture which can be used for educational purpose.
Campus Management System with ID Card using Face Recognition with LBPH Algorithmijait
The Face recognition system mentioned is a computer vision and image processing application designed to carry out two primary functions: identifying and verifying a person from an image or a video database. The objective of this research is to provide a more efficient and effective alternative to traditional manual management systems. It can be used in offices, schools, and organizations where security is critical. In the proposed system, initially, all students enrolled in the Academic Year whose information is stored in a database server and released a unique ID Card with their facial image to be a smart campus. The main objective of the proposed system is to automate the time-in, and time-out of students, teachers, staff, and anyone who enters and leaves the campus of the University of Computer Studies, Hinthada (UCSH). This system is implemented with the 405 students in the 2022-2023 Academic Year, 86 permanent staff including the principal whose ID card (Name, Year, Roll No, NRC, Father Name: for students, Name, Rank, Department, NRC, Address: for teachers and staffs). As soon as someone enters the campus of a university, the ID card is scanned, the images of the ID card are captured and the face onthe card will be matched with the faces in the trained dataset to detect by using the Haar cascade classifier, and recognize the face using Local Binary Pattern LBPH algorithm. The proposed system demonstrates strong performance, achieving an accuracy rate of over 90% for everyone entering the campus. It is both effective and efficient, providing a smart solution for identification.
Accounting for people is the first step of every manpower-based organization in today’s world. Hence, it takes up a signification amount of energy and value in the form of money from respective organizations for both implementing a suitable system for manpower management as well as maintaining that same system. Although this amount of expenditure for big organizations is near to nothing, rather just a formality, it does not hold as much truth for small organizations such as schools, colleges, and even universities to a certain degree. This is the first point. The second point for discussion is that much work has been done to solve this issue. Various technologies like Biometrics, RFID, Bluetooth, GPS, QR Code, etc., have been used to tackle the issues of attendance collection. This study paves the path for researchers by reviewing practical methods and technologies used for existing attendance systems
LUIS: A L IGHT W EIGHT U SER I DENTIFICATION S CHEME FOR S MARTPHONES IJCI JOURNAL
Smartphone usage has reached its peak. There has be
en a tremendous growth in the number of people
migrating from PCs to smart phones. Numerous scenar
ios such as loss of a phone, phone theft etc., can
lead to unauthorized use of one’s own smartphone. T
his raises the concern for securing personal and
private data. This project proposes a light weight
two level user identification scheme to recognize a
nd
authenticate the mobile phone based on the device h
olding and usage patterns. To validate the proposed
scheme, an application is created which takes a ges
ture input characterized by time of swiping the scr
een,
finger pressure, phone movements and location of sw
ipe on the screen through X and Y co-ordinate. A
threshold based matching scheme performs classifica
tion to find the true owner. Results show that the
scheme was able to achieve 90% true positives and 1
0% false positives with a 0.5% of battery usage.
Comparative Analysis of Face Recognition Methodologies and TechniquesFarwa Ansari
In the field of computer sciences such as
graphics and also analyzing the image and its processing,
face recognition is the most prominent problem due to the
comprehensive variation of faces and the complexity of
noises and image backgrounds. The purpose and working
of this system is that it identifies the face of a person from
the real time video and verifies the person from the images
store in the database. This paper provides a review of the
methodologies and techniques used for face detection and
recognition. Firstly a brief introduction of Facial
Recognition is given then the review of the face
recognition’s working which has been done until now, is
briefly introduced. Then the next sections covered the
approaches, methodologies, techniques and their
comparison. Holistic, Feature based and Hybrid
approaches are basically used for face recognition
methodologies. Eigen Faces, Fisher Faces and LBP
methodologies were introduced for recognition purpose.
Eigen Faces is most frequently used because of its
efficiencies. To observe the efficient techniques of facial
recognition, there are many scenarios to measure its
performance which are based on real time.
India is one of the countries which has the electronic voting machine for parliamentary and assembly polls. But in every poll election commission is facing so much of troubles and various types of issues through the election. The most familiar issue which is faced by the election commission is, no proper acknowledgement regarding the confirmation of casting the votes, duplication or illegal casting of votes. In this project all these issues has been handled and overcome with the perfect solution. The main advantage of this project is handling of data by using biometric system such as finger print and face recognition (is done by masking technique). This is used to ensure the security to avoid fake and repeating voting. It also enhances the accuracy and speed of the process. The system performs with perfect recognition on a face and thumb impression of all the eligible voters in a constituency, which is done as pre-polled procedure. During election, thumb impression and face templates of voters is given as an input to the system. This is then compared with the already stored database and available records. If the particular pattern matches with the record then the voters are allowed to vote but incase if it doesn’t match or in case of repetition, voters vote are denied or gets rejected. The result is instant and counting is done.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
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This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Designing Great Products: The Power of Design and Leadership by Chief Designe...
A Smart Receptionist Implementing Facial Recognition and Voice Interaction
1. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 37
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
A Smart Receptionist Implementing Facial Recognition
and Voice Interaction
Osman Mohammed Ahmed ahmed028@cougars.csusm.edu
Department of Computer Science and Information Systems
California State University San Marcos
San Marcos, 92096, USA
Yanyan Li yali@csusm.edu
Department of Computer Science and Information Systems
California State University San Marcos
San Marcos, 92096, USA
Ahmad Hadaegh ahadaegh@csusm.edu
Department of Computer Science and Information Systems
California State University San Marcos
San Marcos, 92096, USA
Abstract
The purpose of this research is to implement a smart receptionist system with facial recognition
and voice interaction using deep learning. The facial recognition component is implemented using
real time image processing techniques, and it can be used to learn new faces as well as detect
and recognize existing faces. The first time a customer uses this system, it will take the person’s
facial data to create a unique user facial model, and this model will be triggered if the person
comes the second time. The recognition is done in real time and after which voice interaction will
be applied. Voice interaction is used to provide a life-like human communication and improve
user experience. Our proposed smart receptionist system could be integrated into the self check-
in kiosks deployed in hospitals or smart buildings to streamline the user recognition process and
provide customized user interactions. This system could also be used in smart home environment
where smart cameras have been deployed and voice assistants are in place.
Keywords: Face Recognition, Deep Learning, Django Framework, Image Processing.
1. INTRODUCTION
The tasks of a receptionist depend on the sector he/she works in and automation of such a job
can be in high demand in hotels, commercial complexes or even for security purposes in certain
organizations. Considering a hotel room reservation system, a receptionist needs to interact with
the customers, getting his/her information, identification, booking and payment of the rooms, etc.
Further, in businesses, scheduling appointments with individuals can be automated where
security is an important factor to be considered and these systems can be strengthened by
imposing features such as facial recognition, voice interaction and server-side security such that
this automation that would help making the tasks of a receptionist system more secure and
reliable to recognize and interact efficiently with the customers. The process of accepting,
addressing and guiding the customers’ needs can be done easily such that the users have no
inconvenience to be recognized by the automated receptionist system.
Authentication is necessary in order to implement security and present systems allow for some
methods to incorporate authentication. Traditional systems use either biometric authentication or
non-biometric authentication. Non-biometric authentication allows for the use of physical objects
such as a swiping card or a key. These systems are further classified into object-based
authentication or knowledge-based authentication. They also allow for the use of passkeys,
2. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 38
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
tokens, PINS, etc which are prone to be guessed or accessed by attackers. In order to overcome
these limitations posed by non-biometric authentication systems, modern systems now use more
advanced authentication systems that implement Biometric authentication systems. These
systems allow identification of an individual through physiological traits and real-time behaviour
which makes the passkey unique. These kind of authentication systems include fingerprints,
retina scans, electronic signature, voice or face recognition, which are difficult to imitate or be
stolen or duplicated by attackers as they’re unique to that user.
Face recognition has gained a lot of popularity in implementing secure systems and have been
constantly in use to improve the accuracy of the systems. This is done to tackle the challenging
tasks because most methods don’t really provide a robust solution to different situations. Example
of these simulations include different expressions, pose invariants, lighting variations, etc.
Furthermore, capturing real-time face recognition has a higher overhead computational cost when
it is implemented with Deep Convolutions Neural Networks.
With advancements in technology, machine learning is now covering vast areas of application
fields wherein implementations of certain algorithms allow for systems to be more discrete,
secure and time saving to automate a lot of different sectors. The accuracy and easy deployment
of these algorithms are the main reasons why these systems are trusted in many fields and
require less manpower. The vast areas of application include automatic driving and self-
transportation vehicles, smart gaming and other entertainment systems, healthcare, home
business security, etc. These systems take in a lot of raw data that and process it to generate
desirable outputs. They learn by repeatedly processing the information and use that experience
to make the systems better.
FIGURE 1: Face Recognition Parameters.
One major application is facial recognition that is used in security systems and business
companies where certain algorithms can detect the face of an individual, store the data and learn
them, and later use the data mining techniques to identify that individual. It is a way to recognize
the human face by using certain biometrics to map the different facial features as depicted in
Figure 1 and compare them with all the other existing faces in the database to find a match. In
business organizations, facial recognition can be used as a security feature, as well as identifying
individuals to automate the task of receiving the clients data and proceeding them to their
required destination. For a commercial complex or office system, a smart receptionist system can
capture the data of the customers and interact with them. This reduce the need of manpower,
time, and money. Unlike humans who need to look up for the records, smart receptionists can
store large amounts of data in their database and use the machine learning techniques to identify
the individuals faster and more efficient.
3. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 39
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
2. RELATED WORK
Face recognition has been a booming topic in the field of automating certain tasks in
establishments and smart receptionist implement several different algorithms and systems to
execute efficient reception tasks. In a research done by Hteik et al. [1], face recognition was
executed by using a MATLAB program on a PC where the access control is done by a
microcontroller. The system that is used in [1] is less efficient as modern-day systems require
faster response and interaction, more accuracy, and better security.
In the papers written by Salvador and Foresti [2], facial recognition was done by implementing
Regularized Linear Discriminant method that only captures frontal facial data by assuming that
user cooperation is present. This might not be the case in every situation and to allow for little or
no inconvenience it is more acceptable to have a more robust and dynamic method to have a
quick scan of the whole picture in lesser time.
Rohit et al. developed their system [3] using IoT devices by integrating Raspberry Pi to detect a
person coming at a door. This allows for efficient face detection but has a higher response time
due to the lag that is generated from using IoT devices.
[4] describes their design and implementation of a smart e-receptionist that can greet visitors and
talk to them with natural language understanding. However, it can only sense a nearby visitor
through motion detection, it doesn’t have the capability of recognizing a user, which we have via
facial recognition and can thus provide more customized interactions.
An interactive robot receptionist system was proposed and designed in [5] that is able to provide
directional guidance using physical gestures and answer simple questions with speech
recognition. Similarly, a smart humanoid receptionist was developed in [6] using WeegreeOne
robot that is connected to several IoT sensors, camera, databases and AI services to enable the
functionalities of user recognition and voice interaction. They tested their humanoid receptionist in
a smart office environment and demonstrated its effectiveness.
In [7], the authors proposed a cloud-based robot receptionist that works in a home environment to
provide both reception and home assistance. The authors in [8] focus on helping the receptionist
to gain context-aware capability and to interact with people in a natural way.
Hwang et al. [9] focused on the dialog system in human robot interaction, and proposed a
recurrent neural network based dialog system. Their proposed system has been validated in the
context of hospital receptionist and their evaluation result shows it is able to efficiently choose
responses and gestures to welcome and help check-in users.
In this work, our main focus is on facial recognition based user authentication and voice
interaction part of a smart receptionist. The chatting, conversation and question understanding
part could be implemented using Google Dialogflow service [10] or word embedding algorithms
such as bert or word2vec [11][12].
3. METHODOLOGY
Our goal is to build a system that manages users who login with a face ID using facial recognition
concepts of machine learning. We have created a web application that can be set up in offices or
business establishments, or even at a certain individual’s reception who might have to schedule
meetings with other people. The system would recognize people who have already visited the
office. For a person who is visiting the first time, the system asks the user to feed in his/her
information. Then, the next time the user makes a visit, the system uses the user stored data to
recognize the user.
4. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 40
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
FIGURE 2: User details for first time users.
Our smart reception system uses facial recognition that allows the user to log in to the system
with his/her facial ID which is unique to user. We have implemented different concepts of
machine learning to perform deep facial recognition using certain libraries in python which will be
discussed later. To be specific, we have used python’s libraries that implement OpenCV that uses
a form of deep Convolutional Neural Networks to allow for a deeper scan of the picture in real
time which can scan all sides including frontal and the sides. Our system takes care of the
limitations of existing system and is relatively more accurate.
FIGURE 3: System Workflow.
This system can be enhanced further to add other essential tasks of a smart receptionist and
thereby creating a perfect application that can be used in large scale commercial complexes. Our
system is embedded in a GUI that gives reliability for both client and server side. Figure 2 shows
the login page where one can log in as a user or the manager. The manager is the one who
manages the Reception.
5. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 41
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
3.1 Basic Workflow
Figure 3 shows the detailed outline of the system workflow. The system will have the
Receptionist’s ‘Wake me Up’ module for a user to come up and use it to record the user face. The
steps include:
a. A user clicks on the button that initializes the face recognition. For first time users, the
system asks for the name and email address as shown in Figure 2.
b. The manager will then be able to schedule new meetings with that new user or other
users as shown in Figure 4.
FIGURE 4: List of Meetings.
c. The manager then schedules a new meeting adding necessary details and the user will
be able to view the same as in Figure 5.
FIGURE 5: Meeting Details.
d. User receives an email with a code from the manager along with meeting details.
e. User logs in the system again using face recognition that opens the page where he/she
enters that code in the system, where the receptionist asks the user to click on a button
and enter the meeting ID by giving audio input of the meeting ID.
f. After the user speaks the id, the receptionist again asks the user to enter the meeting
code, again giving audio input of that code.
g. If the code is correct, the receptionist sends an alert to the manager saying that the user
has arrived, and the manager can authorize that meeting.
h. Finally, the receptionist tells the user to proceed and attend the meeting.
3.2 System Architecture
Figure 6 shows the system architecture of our web application. The back-end system is based on
the Django Framework [13] for developing web applications with python. This facilitates for robust
and simple managing of the different sections in the entire system. In a system where we need to
work with a larger dataset, Django allows for the efficient managing and creating faster access to
each of these items whilst managing the whole application with the database. Django uses a
system called “Models” that are used to handle the database.
6. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 42
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
FIGURE 6: System Architecture.
“Models” is a single entity that defines all our information for a field related to a particular dataset.
It consists of the important fields and behavioural aspects of our data that we have been storing
and maps each of those to a single database table. Every python class is basically a model that
has necessary subclasses and different attributes related to it. Combining the models gives a
layout of the entire system connecting our database to the web application. With these Models,
we can create new tables in the database, and therefore calling models as objects to add rows in
the tables of the database.
FIGURE 7: Django Framework.
FIGURE 8: Admin page backend.
7. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 43
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
Views in this framework are the logic layers for business models. Hence it is well suited for our
application that allows to process the input given by a user and sends back the necessary valid
response. The system takes in the input and fetches the required data from the database and
sends an output onto the screen. In our application, each page is a different view that has its own
GUI to interact with the user such as adding his/her name, email id, and the necessary meeting
details. These entities are all connected to allow for a dynamic managing of different sections of
the system as shown in Figure 7.
We have written the backend system in python programming language due to its ease of use and
compatibility with the Django framework. Python has built-in libraries that we have used for our
face recognition feature, as well as the voice automation. The libraries will be discussed in the
subsequent sections. Figure 8 shows how admin side is managed with the help of Django to keep
track of all the users and sections in the system.
The voice recognition module has been implemented with python’s built-in library based on
gTTS that is “Google’s text to speech” library that allows us to interface with “Google Translating
text to speech” and gives us a vocal speech output. For database management, we have used
SQLite which is a widely used highly reliable and self-contained database engine that is well
suited to work with the Django Framework.
4. IMPLEMENTATION
In this system, we have used different python libraries with implementation of OpenCV that uses
deep neural network that allows us to exploit the face recognition module. We have used the
Convolutional Neural Networks (CNN) to extract the key and essential components of images that
have been taken as the input without any pre-processing of the raw images. CNN also has the
potential to recognize patterns that have different geometrical variations such as rotations in the
image, scaling, noise, etc.
FIGURE 9: Initializing Face Recognition button.
Convolutional Neural Networks reduce the training performance of the traditionally used Back
propagation (BP) algorithm [14] by reducing the number of learning parameters in that process to
avoid any required pre-processing. The network relationship in CNNs are spatial that allows for
the minimizing the pre-processing. Figure 9 is the homepage that initializes the face recognition
algorithm on clicking the ‘wake me up’ button.
FIGURE 10: Face Recognition with python.
8. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 44
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
In addition, the main reason for implementation of CNNs is to capture 3D image recognition in all
angles and directions, whereas traditional systems using HOG (Histogram of Oriented Gradients)
[15] or Regularized Linear Discriminant Analysis (R-LDAs) [16][17] rely mostly on frontal face
detection. To make our system more user friendly, we have used the libraries in python that
allows for reading and capturing of faces laid in all axis, doing the translations and the rotations
as shown in Figure 10.
FIGURE 11: Encoding Faces.
Figure 11 shows a block of code where we have performed the face encoding of some people for
whom we were able to deploy the system to. We can use CNNs through OpenCV to train the
system to generate 128 measurements for each of the faces. Then for all the people with different
measurements, the neural network learns to generate 128 measurements for each person. Next,
we run our face images through our pre-trained network to get the 128 measurements for each
face and we can generate a string or array for each face that contains the encoded list.
Therefore, at the end, each face (or person) has its unique string with its encoded array.
FIGURE 12: View Page after Authentication.
4.1 Receptionist Task
The main task of the smart receptionist in our system is to accept incoming users, record their
faces and ask for their names and email address.
9. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 45
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
FIGURE 13: One-time Code sent via email to User.
When a user logs in for the second time, the system identfies the image of the user by comparing
the existing data in the database. The system search the individual and checks if the user has
any meeting (Figure 12).
Figure 14: Voice Input for Meeting ID and Code
Next, the receptionist generates a one time code after the manager schedules a meeting. The
code is sent to the user’s email address (See Figure 13) that he/she had entered. The message
includes details of the meeting including the time and the description of the meeting. The user will
use the code in that email and enter it in the system as shown in Figure 14 in order to
aunthenticate himself for that specific meeting.
FIGURE 15: Alert to Manager.
FIGURE 16: Testing.
10. Osman Mohammed Ahmed, Yanyan Li & Ahmad Hadaegh
International Journal of Image Processing (IJIP), Volume (15) : Issue (3) : 2021 46
ISSN: 1985-2304, https://www.cscjournals.org/journals/IJIP/description.php
The receptionist then tells the user to proceed for the meeting, after the manager approves the
alert (Figure 15) that was sent to user when the suer had arrived. This is the basic task of the
receptionist that we have implemented in this system. Many other functionalities can be added
later as the future work.
4.2 Results
We have deployed the application to about 40 different individuals who were able to log into the
system after feeding in their facial data, and storing their name and email address into the
database. We have allowed them to enter their first image with a regular face. Later, we have
tested the accuracy of the system by having them face the camera wearing sunglasses, or hats
as we seen in Figure 16. The system was able to detect the faces of those individuals. Each
facial data was unique and did not overlap with any of the other data.
For each of the individuals, we were able to record their faces in different lighting and
backgrounds and the system was able to recognize and authenticate that individual as well as
welcoming the person with his/her name. The model has an accuracy of 99.38% for the face
recognition module.
5. CONCLUSION
The smart receptionist system allows for an efficient, robust and dynamic use of the face
recognition and voice interaction modules as well as providing an easy GUI that would allow
users to come in and authenticate themselves and schedule meetings.
The smart receptionist system can be further enhanced by adding advanced facial recognition to
avoid existing security issues. Furthermore, voice automation can be improved by creating a
more dynamic interaction between the user and the receptionist to have a proper conversation
between the two. It is also possible to assign more tasks to the receptionist. Receptionists in the
existing system, are capable of scheduling meetings, and few other minor jobs. The front-end of
our application is built on HTML, CSS and Bootstrap, and future work would include refining it to a
more dynamic application with buttons and drop-down menus depending on the added tasks of
the receptionist. Further, we have used the webcam in laptop HP EliteBook, and future
implementations would be extended over to use Raspberry Pi, or other IoT devices.
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