Mobile Big Data

2016 ◽  
pp. 138-158
Author(s):  
Shivom Aggarwal ◽  
Abhishek Nayak
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Value Chain ◽  
Mobile Technologies ◽  
Complex Concept ◽  
Current Trends ◽  
Mobile Big Data ◽  
Challenges And Opportunities ◽  
New Challenges ◽  
Data Ecosystem

Mobile technologies have given rise to tremendous amounts of data in real-time, which can be unstructured and uncertain. This growth can be attributed as Mobile Big Data and provides new challenges and opportunities for innovation. This chapter attempts to define the concept of Mobile Big Data, provide description of various sources of Mobile Big Data and discuss SWAI (Sources Warehousing Analytics Insights) model of Big Data processing. To understand this complex concept, it is important to visualize the Big Data ecosystem, respective players. Moreover, mobile computing, Internet of things, and other associated technologies have been discussed in light of marketing and communications based applications. The current trends in Mobile Big Data and associated value chain help us understand where the next frontiers of innovation are and how one can create value. This is linked to the future aspects of the Mobile Big Data and evolution of technologies from now onwards.

Mobile Big Data

2016 ◽  
pp. 1796-1816
Author(s):  
Shivom Aggarwal ◽  
Abhishek Nayak
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Value Chain ◽  
Mobile Technologies ◽  
Complex Concept ◽  
Current Trends ◽  
Mobile Big Data ◽  
Challenges And Opportunities ◽  
New Challenges ◽  
Data Ecosystem

Mobile technologies have given rise to tremendous amounts of data in real-time, which can be unstructured and uncertain. This growth can be attributed as Mobile Big Data and provides new challenges and opportunities for innovation. This chapter attempts to define the concept of Mobile Big Data, provide description of various sources of Mobile Big Data and discuss SWAI (Sources Warehousing Analytics Insights) model of Big Data processing. To understand this complex concept, it is important to visualize the Big Data ecosystem, respective players. Moreover, mobile computing, Internet of things, and other associated technologies have been discussed in light of marketing and communications based applications. The current trends in Mobile Big Data and associated value chain help us understand where the next frontiers of innovation are and how one can create value. This is linked to the future aspects of the Mobile Big Data and evolution of technologies from now onwards.

Big Data in manufacturing systems engineering – close up on a machine tool

2016 ◽  
Vol 64 (7) ◽  
Author(s):  
Christian Bauer ◽  
Zaigham-Faraz Siddiqui ◽  
Manuel Beuttler ◽  
Klaus Bauer
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Internet Of Things ◽  
Systems Engineering ◽  
Machine Tools ◽  
Manufacturing Systems ◽  
The Internet ◽  
New Approach ◽  
New Challenges ◽  
The Internet Of Things

AbstractWith the increasing connectivity of devices, the amount of data that is recorded and ready for analysis is growing correspondingly. This is also the case for shop floors in flexible sheet metal handling and production. With the growing need for flexibility in production, the availability of machine tools is imminent. This paper shows different approaches that a classical manufacturing systems company such as TRUMPF takes in applying data mining techniques to address the new challenges which come with the Internet of things. In addition to classical methods, a new approach is introduced that does not need any alteration of the machine or its interfaces.

A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system

2018 ◽  
Vol 82 ◽  
pp. 375-387 ◽  
Author(s):  
Gunasekaran Manogaran ◽  
R. Varatharajan ◽  
Daphne Lopez ◽  
Priyan Malarvizhi Kumar ◽  
Revathi Sundarasekar ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Smart Healthcare ◽  
Alerting System ◽  
Healthcare Monitoring ◽  
Data Ecosystem

scholarly journals Integration of Cloud Computing, Big Data, Artificial Intelligence, and Internet of Things

2021 ◽  
Vol 16 (1) ◽  
pp. 10-17
Author(s):  
Drissi Saadia
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Detailed Analysis ◽  
New Paradigm ◽  
Research Papers ◽  
Research Issues ◽  
New Challenges ◽  
Open Issues

Cloud computing, internet of things (IoT), artificial intelligence, and big data are four very different technologies that are already discussed separately. The use of the four technologies is required to be more and more necessary in the present day in order to make them important components in today's world technology. In this paper, the authors center their attention on the integration of cloud, IoT, big data, and artificial intelligence. Several kinds of research papers have surveyed artificial intelligence, cloud, IoT, and big data separately and, more precisely, their main properties, characteristics, underlying technologies, and open issues. However, to the greatest of the authors' knowledge, these works require a detailed analysis of the new paradigm that combines the four technologies, which suggests completely new challenges and research issues. To bridge this gap, this paper presents a survey on the integration of cloud, IoT, artificial intelligence, and big data.

scholarly journals Big Data: a Source of Mobility Behaviour and a Strategic Tool for Destination Management

2019 ◽  
Vol 8 (2) ◽  
pp. 85-102
Author(s):  
Filip Emmer ◽  
Andrea Holešinská
Keyword(s):  
Big Data ◽  
Point Of View ◽  
Mobile Technologies ◽  
Future Trends ◽  
Digital Footprint ◽  
Current Trends ◽  
Mobility Behaviour ◽  
Basic Characteristics ◽  
Use Of The Internet ◽  
Scientific Fields

Abstract The abundant use of the Internet and mobile technologies while traveling leaves a digital footprint in the form of big data that can be tracked. Big data bring information about spatial visitor behaviour that is valuable for strategic destination management. Big data enrich not only scientific fields (e. g. management, marketing, or geography) with their knowledge, but also represent the invention of new tools for their actual processing. Generally, big data are considered as a strategic tool enhancing the competitiveness of a destination. The paper presents the basic characteristics of big data and reviews research focused on big data in tourism. Moreover, it identifies its potential for tourism from both the theoretical and methodological point of view. The final part deals with current trends in using the big data in tourism and its application in destination management. The future trends of big data in the context of destination management are implied as well.

scholarly journals Single cells make big data: New challenges and opportunities in transcriptomics

2017 ◽  
Vol 4 ◽  
pp. 85-91 ◽  
Author(s):  
Philipp Angerer ◽  
Lukas Simon ◽  
Sophie Tritschler ◽  
F. Alexander Wolf ◽  
David Fischer ◽  
...  
Keyword(s):  
Big Data ◽  
Single Cells ◽  
Challenges And Opportunities ◽  
New Challenges

Decentralized Information Use

2017 ◽  
Author(s):  
Sundeep Sahay ◽  
T Sundararaman ◽  
Jørn Braa
Keyword(s):  
Public Health ◽  
Cloud Computing ◽  
Big Data ◽  
Social Order ◽  
Health Informatics ◽  
Information Use ◽  
Public Health Informatics ◽  
Challenges And Opportunities ◽  
New Challenges ◽  
Do So

This chapter seeks to explore the challenge and opportunities that cloud computing and big data offer to strengthen public health informatics in LMICs. Cloud computing is slowly becoming a norm, almost representing a technical and social order which we do not fully understand, but need to accept. While there is a multiplicity of understandings associated with the cloud, we often focus only on its technical elements, while ignoring the business model that underlies it. This incomplete understanding may lead to LMICs making investments in solutions which are unsustainable, while also creating new challenges and demands for capacity. The cloud also raises key dilemmas around participation, decentralization, and ownership of data. Developments in big data, necessarily dependent on the cloud, are another source of challenges and opportunities for LMICs. Whether we like it or not, cloud computing and big data are integral elements to develop the Expanded PHI perspective, and we need to find appropriate approaches to do so.

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