Construction of a smart management system for physical health based on IoT and cloud computing with big data

2021 ◽  
Vol 179 ◽  
pp. 183-194
Author(s):  
Ning Zhang ◽  
Chenfei Zhang ◽  
Dengpan Wu
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Physical Health ◽  
Management System

Learning Management System 2.0

Web Services ◽  
2019 ◽  
pp. 2255-2270
Author(s):  
Muhammad Anshari ◽  
Yabit Alas ◽  
Norazmah Yunus ◽  
Norakmarul Ihsan binti Pg Hj Sabtu ◽  
Malai Hayati Sheikh Abdul Hamid ◽  
...  
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Big Data ◽  
Knowledge Management ◽  
Management System ◽  
Learning Management System ◽  
New Paradigm ◽  
Efficiency And Effectiveness ◽  
Main Driver ◽  
Learning Management

The recent adoption of cloud computing, Web 2.0 (web as a platform), and Big Data technologies have become the main driver of the paradigm shift. For higher education, choosing the right platform for a next generation of Learning Management System (LMS) namely LMS 2.0 is becoming more important than choosing a tool in the new paradigm. This chapter discusses factors for higher institution in determining a future direction for its LMS to take advantage of pervasive knowledge management, efficiency and effectiveness of operations. Literature studies have deployed for this study to portray the state of future LMS initiative. We found that the trends of cloud computing and big data will be predominant factor in viewing future LMS adoption and implementation. LMS 2.0 can be a solution to make learning systems in a higher education is flexible in terms of resources adoption, quality of learning, knowledge management, and implementation.

Learning Management System 2.0

2016 ◽  
pp. 265-279 ◽  
Author(s):  
Muhammad Anshari ◽  
Yabit Alas ◽  
Nor'Azmah Hj Mohd Yunus ◽  
Norakmarul Ihsan binti Pg Hj Sabtu ◽  
Malai Hayati Sheikh Abdul Hamid ◽  
...  
Keyword(s):  
Higher Education ◽  
Cloud Computing ◽  
Big Data ◽  
Knowledge Management ◽  
Management System ◽  
Learning Management System ◽  
New Paradigm ◽  
Efficiency And Effectiveness ◽  
Main Driver ◽  
Learning Management

The recent adoption of cloud computing, Web 2.0 (web as a platform), and Big Data technologies have become the main driver of the paradigm shift. For higher education, choosing the right platform for a next generation of Learning Management System (LMS) namely LMS 2.0 is becoming more important than choosing a tool in the new paradigm. This chapter discusses factors for higher institution in determining a future direction for its LMS to take advantage of pervasive knowledge management, efficiency and effectiveness of operations. Literature studies have deployed for this study to portray the state of future LMS initiative. We found that the trends of cloud computing and big data will be predominant factor in viewing future LMS adoption and implementation. LMS 2.0 can be a solution to make learning systems in a higher education is flexible in terms of resources adoption, quality of learning, knowledge management, and implementation.

Waste Management System for Smart City Using IoT

2019 ◽  
pp. 1-15
Author(s):  
Golden Julie E.
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Waste Management ◽  
Smart City ◽  
Management System ◽  
Smart Cities ◽  
Smart Devices ◽  
Construction Technology ◽  
Waste Management System

In the present scenario, sensors place a major role for implementing smart devices. Internet of Things (IoT) is an advancement of sensors which can communicate with non-communicate things (devices). Many of the developed counties are using smartness in creating and communicating devices using IoT. In India, major challenges focus on how and where to implement smartness. Hence, authors found some different areas like healthcare, education, transport, water, energy, communication, security & safety, citizen services, and so on. All these areas are covered by a smart way using recent technology (IoT) in smart cities concepts. Various technologies like IoT, Big Data, and cloud computing are used for constructing smartness in the form of devices. In this Chapter, authors focus on a smart waste management system using IoT. They provide various smart bin construction technology, advantages, standards and challenges in detail. It is very useful to the reader to understand the various method of waste management in smart cities development using IoT.

Challenges and Cloud Computing Environments Towards Big Data

2014 ◽  
pp. 203-208
Author(s):  
Kiran Kumar S V N Madupu
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Technology Development ◽  
Computing Environments ◽  
Modern Technologies

Big Data has terrific influence on scientific discoveries and also value development. This paper presents approaches in data mining and modern technologies in Big Data. Difficulties of data mining as well as data mining with big data are discussed. Some technology development of data mining as well as data mining with big data are additionally presented.

Model Knowledge Management System Konseling Mahasiswa Berbasis Cloud Computing

CCIT Journal ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 138-148
Author(s):  
H. Abdul Hamid Arribathi ◽  
Dedeh Supriyanti ◽  
Lusyani Sunarya
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Knowledge Management ◽  
Management System ◽  
Positive Impact ◽  
Professional Staff ◽  
Knowledge Management System ◽  
Literature Study ◽  
Student Counseling ◽  
The World

Information technology is increasingly developing and has a positive impact on the world of education. The implementation of student counseling with a Knowledge Management System is one of the contributions of information technology in the world of education. Many benefits provided by the Student Counseling Knowledge Management System, in managing the knowledge needed by the counselor section to document student consultations. The development and implementation of a KMS counseling system costs more to employ professional staff to maintain and improve; KMS student counseling application; For this reason, it is necessary to design a Cloud Computing-based Student Counseling Knowledge Management System. The research method carried out in the first stage is to collect data and information about Knowledge Management and Student Counseling, and how to use it to create a Knowledge Management System Application, Student Counseling Based on cloud computing. Furthermore, conducting a literature study and literature review, system design is in the form of data architecture compounding, process design, network design, and user interface design. The design results of this system can facilitate educational institutions in conducting online cloud computing-based student counseling

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Issues in security and privacy of big data

2018 ◽  
Vol 7 (12) ◽  
pp. 1
Author(s):  
Shaveta Bhatia
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Approximate Method ◽  
Biomedical Research ◽  
Cyber Security ◽  
Data Science ◽  
Third Party ◽  
Security And Privacy ◽  
Security Threats ◽  
The Third

 The epoch of the big data presents many opportunities for the development in the range of data science, biomedical research cyber security, and cloud computing. Nowadays the big data gained popularity.  It also invites many provocations and upshot in the security and privacy of the big data. There are various type of threats, attacks such as leakage of data, the third party tries to access, viruses and vulnerability that stand against the security of the big data. This paper will discuss about the security threats and their approximate method in the field of biomedical research, cyber security and cloud computing.

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