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Awais Khan Jumani

Bio: Awais Khan Jumani is an academic researcher from Shah Abdul Latif University. The author has contributed to research in topics: Computer science & Cloud computing. The author has an hindex of 6, co-authored 23 publications receiving 91 citations.

Papers
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Journal ArticleDOI
TL;DR: This paper describes fog computing technology, infrastructure, and applications, and presents the latest development of fog networking, quality of experience, cloud at the edge, platforms, security, and privacy.
Abstract: Over the last decade, data processing shifted from cloud computing to the local processing environment named Fog computing. Fog computing is an extension of cloud computing, which process data nearby device instead of sending to the cloud this will reduce the burden from the Internet and quick processing. In this paper, we describe fog computing technology, infrastructure, and applications. Specifically, we present the latest development of fog networking, quality of experience, cloud at the edge, platforms, security, and privacy. Finally, we discuss the current research, solutions and present open issues of future research in Fog computing.

33 citations

Posted Content
TL;DR: In this article, an effective and free solution for big data application in a distributed environment, with its advantages and indicating its easy use was presented. Apache Hadoop open source technology created in Java and keeps running on Linux working framework was used.
Abstract: The term, Big Data, has been authored to refer to the extensive heave of data that can't be managed by traditional data handling methods or techniques. The field of Big Data plays an indispensable role in various fields, such as agriculture, banking, data mining, education, chemistry, finance, cloud computing, marketing, health care stocks. Big data analytics is the method for looking at big data to reveal hidden patterns, incomprehensible relationship and other important data that can be utilize to resolve on enhanced decisions. There has been a perpetually expanding interest for big data because of its fast development and since it covers different areas of applications. Apache Hadoop open source technology created in Java and keeps running on Linux working framework was used. The primary commitment of this exploration is to display an effective and free solution for big data application in a distributed environment, with its advantages and indicating its easy use. Later on, there emerge to be a required for an analytical review of new developments in the big data technology. Healthcare is one of the best concerns of the world. Big data in healthcare imply to electronic health data sets that are identified with patient healthcare and prosperity. Data in the healthcare area is developing past managing limit of the healthcare associations and is relied upon to increment fundamentally in the coming years.

20 citations

Journal ArticleDOI
01 Oct 2017
TL;DR: The primary commitment of this exploration is to display an effective and free solution for big data application in a distributed environment, with its advantages and indicating its easy use.
Abstract: The term, Big Data, has been authored to refer to the extensive heave of data that can't be managed by traditional data handling methods or techniques. The field of Big Data plays an indispensable role in various fields, such as agriculture, banking, data mining, education, chemistry, finance, cloud computing, marketing, health care stocks. Big data analytics is the method for looking at big data to reveal hidden patterns, incomprehensible relationship and other important data that can be utilize to resolve on enhanced decisions. There has been a perpetually expanding interest for big data because of its fast development and since it covers different areas of applications. Apache Hadoop open source technology created in Java and keeps running on Linux working framework was used. The primary commitment of this exploration is to display an effective and free solution for big data application in a distributed environment, with its advantages and indicating its easy use. Later on, there emerge to be a required for an analytical review of new developments in the big data technology. Healthcare is one of the best concerns of the world. Big data in healthcare imply to electronic health data sets that are identified with patient healthcare and prosperity. Data in the healthcare area is developing past managing limit of the healthcare associations and is relied upon to increment fundamentally in the coming years.

14 citations

Journal ArticleDOI
TL;DR: It has been presented that face detection with voice and biometric technology can enhance the security measures and Employee’s attendance can be marked by simply detecting face that can increase punctuality.
Abstract: Background/objectives: The major changes which come across face recognition are to find the age and gender of the person. This study is centered on face detection with voice and biometric technology. Methodology: During this study, it has been worked on the input camera which takes multiple shots of person. After that, the Cascade Classification algorithm has been used inside the application which creates the multiple human templates. So the facial features have been detected. After that, it saved in particular database with their unique ID. Furthermore, the verification process has been started by matching the templates inside the database. Through this process, the student attendance has been marked automatically. Findings: It has been presented that face detection with voice and biometric technology can enhance the security measures. Employee’s attendance can be marked by simply detecting face that can increase punctuality. Students can be checked and marked by face detection process. As well, it can also be setup in banks to enhance the security by allowing authorized people only or who have accounts in that bank. Novelty/improvements: For finding the age and gender from a particular image, relevant techniques are discussed, with some new approaches for maintaining security. We discussed complete models with security measures in this research. Keywords: Face Detection, Image Processing, Distinctive Characteristic Location, Template Creation & Matching.

12 citations

Journal ArticleDOI
TL;DR: The study covers the issues regarding implementation plans, project management, and selection or designing of these systems and determines the role of different teams and workforce during the implementation process and after carrying out the process in the business environment.
Abstract: Motivation: In the modern computing and business world computerization, automation and Enterprise Resource Planning (ERP) system has become the backbone in both public and private sector organizations throughout the world. IT departments in organizations are playing major role in controlling the financial activities, procedures, business, and administrative operations. Problem: In this study, we have analyzed and examined the major issues which an organization could face while starting the ERP project. Objectives: This study will also discuss the significant elements which are crucial for an organization when they move towards the ERP system. Adopting the ERP system for an organization is not only a highly difficult task, but is also an expensive process. Therefore, the organization cannot afford the failure of this implementation plan. Solutions: Moreover, this study is also about the solutions regarding management and administrative plans as well as it helps to design comprehensive controls and procedures for the ERP system implementation project. The issues in the structure, functions, culture, human resource, and procedures of organizations are focused on the study and discussion is made to find out the solutions to control these issues during the implementation process. The study covers the issues regarding implementation plans, project management, and selection or designing of these systems and determines the role of different teams and workforce during the implementation process and after carrying out the process in the business environment. Keywords: Enterprise Resource Planning, Success Factors, Administrative & Management Issues and Challenges, CSF (Critical Success Factors), CFF (Critical Failure Factors).

12 citations


Cited by
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Journal Article
TL;DR: In this article, a book review featured in Quality Management Journal and reviewed by Nicole Radziwill is presented, which is based on the work of the authors of this article. But
Abstract: This a book review featured in Quality Management Journal and reviewed by Nicole Radziwill...

180 citations

Journal ArticleDOI
TL;DR: In this paper, a literature review of articles related to Industry 4.0 and environmental sustainability published between 2000 and 2020 is presented, showing that there is a negative relationship related to the flow of the production process from the inputs to the final product, including raw materials, energy requirements, information, and waste disposal.
Abstract: Industry 4.0 is a concept that originated from the German industry, and whose essence is the use of technology for efficient production. In business today, the emergence of Industry 4.0 for production, and its related technologies, such as the Internet of Things (IoT) and cyber-physical systems, amongst others, have, however, a negative impact on environmental sustainability as a result of air pollution, the poor discharge of waste, and the intensive use of raw materials, information, and energy. The method used in this study is an analysis of a literature review of manuscripts discussing topics related to Industry 4.0 and environmental sustainability published between 2000 and 2020. There is currently a gap existing between the actual and the desired situation, in that production occurs in a weak sustainability model, and, therefore, this research debates the effects on environmental sustainability and the challenges facing Industry 4.0. Four scenarios are discussed: a deployment scenario, an operation scenario, integration and compliance with sustainable development goals, and a long-run scenario. The results indicate that there is a negative relationship related to the flow of the production process from the inputs to the final product, including raw materials, energy requirements, information, and waste disposal, and their impacts on the environment. However, the integration of Industry 4.0 and the sustainable development goals enhance environmental sustainability to create ecological support that guarantees high environmental performance with a more positive impact than before. This paper will help stakeholders and companies to provide solutions to the existing environmental challenges that can be mediated through adopting new technologies. The novelty of this study is its depiction of Industry 4.0 and its technologies integrated with sustainable development goals to create a sustainable Industry 4.0 combining environmental protection and sustainability.

175 citations

Journal ArticleDOI
TL;DR: The utilization of IoT in the cloud, fog, IoT technologies with applications and security is described and IoT architecture for design and development with sensors in 6G is provided.
Abstract: The Internet of Things (IoT) is basically like a system for connecting computer devices, mechanical and digital machines, objects, or individuals provided with the unique system (UIDs) and without transfer to transmit data over an ability human-to-human or computer-to-human relation. Another thing on the internet is that the items in the IoT are like a connected manner with humans and computers to which internet protocol addresses can be assigned and which can transfer data over the network or another man-made object. In this paper, we describe the utilization of IoT in the cloud, fog, IoT technologies with applications and security. Specifically, we provide IoT architecture for design and development with sensors in 6G. Finally, we discuss the current research, solutions, and present open issues of future research in IoT.

125 citations

Journal ArticleDOI
TL;DR: The results posit that the credentials of the technology acceptance model together with task-technology fit contribute substantially to the enhancement of behavioral intentions to use the big data analytics system in healthcare, ultimately leading towards actual use.
Abstract: Big data analytics is gaining substantial attention due to its innovative contribution to decision making and strategic development across the healthcare field. Therefore, this study explored the adoption mechanism of big data analytics in healthcare organizations to inspect elements correlated to behavioral intention using the technology acceptance model and task-technology fit paradigm. Using a survey questionnaire, we analyzed 224 valid responses in AMOS v21 to test the hypotheses. Our results posit that the credentials of the technology acceptance model together with task-technology fit contribute substantially to the enhancement of behavioral intentions to use the big data analytics system in healthcare, ultimately leading towards actual use. Meanwhile, trust in and security of the information system also positively influenced the behavioral intention for use. Employee resistance to change is a key factor underlying failure of the innovative system in organizations and has been proven in this study to negatively moderate the relationship between intention to use and actual use of big data analytics in healthcare. Our results can be implemented by healthcare organizations to develop an understanding of the implementation of big data analytics and to promote psychological empowerment of employees to accept this innovative system.

81 citations