The "Industrial Convergence: 5G, AI, Cloud Computing, Data Analytics, IIoT and Robotics 2017 - 2022" report has been added to Research and Markets' offering.

This Research Represents the Most Comprehensive Analysis Available Focused on These Converging Technologies and Their Facilitation of Next Generation Solutions, Products, and Services for Industry

This research evaluates 5G, AI, Cloud Computing, Data Analytics, IIoT and Robotics technologies and solutions in support various industrial segments. The research also assesses the outlook of various converged technologies and solutions such as the integration of teleoperation, robotics, and cloud systems. The research analyzes the impact of each technology upon industrial automation such as the impact of SaaS, PaaS, and IaaS upon IIoT as well as cloud computing software, platforms, and infrastructure in support of edge computing. The research includes detailed quantitative analysis with forecasts for the 2017 to 2022 period.

The convergence of 5G wireless, artificial intelligence, cloud computing (including mobile edge computing), data analytics, industrial IoT technologies, and advanced robotics is transforming industrial automation and taking manufacturing and other industrial sub-sectors to new heights of productivity and innovation. While different industrial sub-sectors will realize certain unique benefits, industry as a whole will realize substantial improvements including greater efficiency, new and improved products and services, improved visibility and impact upon product life cycles, and greater flexibility such as products as a service.

The use of 5G for Industrial IoT (IIoT) networks will be of great importance to certain industry verticals such as agriculture, logistics, and manufacturing. All of these industrial sectors will also require efficient and effective computing systems. There is a substantial opportunity for both a centralized cloud as a service model for software, platforms, and infrastructure as well as edge computing cloud solutions for industry. The combination of robotics, teleoperation, and cloud technologies is poised to transform industrial processes across many industry verticals.

Data Analytics provides the means to process vast amounts of machine-generated and often unstructured data. Accordingly, Big Data technologies and predictive analytics enable stream lining of industrial processes. As IIoT progresses, there will an increasingly large amount of unstructured machine data. The growing amount of machine generated industrial data will drive substantial opportunities for AI support of unstructured data analytics solutions.

Select Research Benefits:

• Detailed forecasts in all technology areas 2017 to 2022
• Learn how converging technologies will impact industry
• Understand how cloud services and 5G will accelerate IIoT
• Recognize how cloud robotics will transform manufacturing
• Identify opportunities for AI in industrial predictive analytics
• Identify the impacts of 5G and teleoperation in the industrial sector
• Understand digital twinning and its impact on the production and PLM

Target Audience:

• Systems integrators
• IoT solution providers
• ICT infrastructure providers
• Industrial services companies
• Communications and computing providers
• Big data, analytics, and info processing companies

Key Topics Covered:

Industrial IoT and 5G: Emerging Technologies, Solutions, Market Outlook and Forecasts

1 Introduction
1.1 Why Industrial IoT and 5G?
1.2 Industrial IoT Platforms
1.3 Relationship between Industrial IoT and 5G
1.4 Industrial IoT: A View into the Period 2016 to 2020
1.5 5G as Key Enabler for IIoT Initiatives
1.6 5G Responsiveness to IIoT
1.7 Potential Contribution of Proprietary Platform
1.8 5G and Industrial Automation
1.9 5G to Enable Wireless IIoT Automation
1.10 5G for Industrial Internet Components
1.11 Role of Industrial Internet in IIoT Automation
1.12 Role of Mobile Edge Computing in IIoT and 5G
1.13 Role of Smart Grid in IIoT and 5G
1.14 Role of LPWAN Technology to IIoT
1.15 5G to Create News Business Model for IIoT
1.16 IIoT Security
1.17 IIoT and 5G: Where is the Money?
1.18 Virtual Reality, IIoT, and 5G
1.19 IIoT 5G Stakeholder Analysis

2 IIoT 5G Application Scenarios
2.1 Maritime Use Case
2.2 Oil and Gas Sector
2.3 Manufacturing Use Case
2.4 Mobile Cloud Robotics
2.5 Precision Agriculture
2.6 City Waste Management
2.7 Food Waste Management
2.8 Smart Buildings
2.9 Road Congestion Management
2.10 Efficient Energy Management
2.11 Enterprise Asset Management
2.12 Healthcare Applications
2.13 Shipping Automation
2.14 Autonomous Driving
2.15 Water Management
2.16 Aviation Management

3 IIoT 5G Market Forecasts
3.1 Global Forecasts 2020 - 2025
3.2 Regional Forecasts 2020 - 2025

4 Industrial IoT 5G Platforms, Solutions, and Initiatives
4.1 Time Sensitive Networking
4.2 General Electric
4.3 Qualcomm
4.4 Aware360
4.5 KAA
4.6 XILINX
4.7 AT&T
4.8 Bosch
4.9 Cisco System
4.10 Echelon Corporation
4.11 Object Management Group
4.12 Real Time Innovation
4.13 Google
4.14 Omron Corporation
4.15 BlackBerry
4.16 Rockwell Automation
4.17 Honeywell International
4.18 Fujitsu America

5 Conclusions and Recommendations
5.1 Success Factors for IIoT in 5G

Industrial Internet of Things (IIoT) Technologies, Solutions, and Services 2017 - 2022

1 Introduction
1.1 Scope of Research
1.2 Target Audience
1.3 Key Findings in Report
1.4 Companies in Report

2 Executive Summary
2.1 IIoT Markets by Region 2017 - 2022
2.2 IIoT Global Markets by Products 2017 - 2022

3 Overview
3.1 Defining Industrial Internet of Things
3.2 Critical Focal Areas for IIoT Execution
3.3 IIoT Application Areas
3.4 Forming a Foundation for IIoT
3.5 Evaluating the Future Potential of IIoT

4 IIoT Technologies
4.1 Hardware Technologies
4.2 Software Technologies
4.3 IIoT and Manufacturing Execution Systems (MES)
4.4 Network Technologies in IIoT

5 IIoT Global Market Analysis and Forecasts 2017 - 2022
5.1 IIoT Markets by Region 2017 - 2022
5.2 IIoT Global Markets by Products Offered 2017 - 2022
5.3 IIoT Global Markets by Industry Sector 2017 - 2022
5.4 Market for Teleoperation and Tele-robotics in IIoT 2016 - 2021

6 Company Analysis
6.1 AGT International
6.2 ARM Holdings
6.3 AT&T Inc.
6.4 B+B SmartWorx
6.5 Bayshore Networks
6.6 Bosch
6.7 Cisco System Inc.
6.8 Contiki
6.9 Digi International
6.10 Echelon Corporation
6.11 Elecsys Corporation
6.12 General Electric
6.13 Jasper Technologies Inc. (Cisco)
6.14 Lynx Software Technologies, Inc.
6.15 Object Management Group (OMG)
6.16 OneM2M Partners
6.17 ParStream (Cisco)
6.18 RIOT
6.19 Real Time Innovation (RTI)
6.20 Sensata Technologies
6.21 Symantec
6.22 Unisys Corporation
6.23 Wind River
6.24 Worldsensing
6.25 Wovyn LLC

Cloud Computing in Industrial IoT 2017 - 2022

1 Overview
1.1 Cloud Computing
1.2 Cloud Computing Structure
1.3 Traditional Industrial IoT Challenges
1.4 Cloud Computing in Industrial IoT
1.5 Consumer vs. Industrial Cloud Platforms
1.6 Evolution of Fog Computing
1.7 IIoT Cloud Computing Benefits
1.8 Industrial Internet and IIoT

2 IIoT Cloud Computing Ecosystem
2.1 IIoT Cloud Computing Services
2.2 Cloud Computing Deployment
2.3 IIoT Cloud Computing Applications
2.4 Cloud Manufacturing
2.5 Software Defined IIoT and Industry 4.0
2.6 Smart Connected Enterprise and Workplace
2.7 Cloud Technology in Robotics
2.8 Artificial Intelligence and IIoT Solutions
2.9 IIoT Cloud Computing Challenges
2.10 IIoT Cloud Computing Pricing Models

3 Industrial IoT Cloud Computing Market
3.1 Cloud Computing in IIoT Global Market Forecasts
3.2 Cloud Computing in IIoT Regional Market Forecasts

4 IIoT Cloud Connected Devices/Things Forecasts
4.1 Connected Device Forecasts 2017 - 2022
4.2 Connected Things/ Objects Forecasts

5 Company Analysis
5.1 Amazon Web Services
5.2 Cumulocity GmBH
5.3 CISCO Systems Inc.
5.4 SAP SE
5.5 Ampla Soluciones SL
5.6 General Electric
5.7 AT&T Inc.
5.8 Losant IoT Inc.
5.9 Thethings.io
5.10 XMPro
5.11 Siemens AG
5.12 Robert Bosch GmbH
5.13 IBM Corporation
5.14 Microsoft Corporation
5.15 C3IoT
5.16 Meshify
5.17 Sierra Wireless Inc.
5.18 Carriots
5.19 Intel Corporation
5.20 PTC
5.21 Uptake Technologies Inc.
5.22 TempolQ
5.23 Honeywell International
5.24 Enterox Systems
5.25 Aware360 Ltd.
5.26 XILINX Inc.
5.27 Echelon Corporation
5.28 Real Time Innovation
5.29 Fujitsu Ltd.
5.30 Reali Technologies Ltd

6 Conclusions and Recommendations

Cloud Robotics: Technologies, Leading Companies, Solutions, Market Outlook, and Forecasts 2017 - 2022

1 Introduction
1.1 Cloud Robotics Overview
1.2 Traditional vs. Cloud Robotics
1.3 Cloud Robotics Architecture
1.4 Robot Types
1.5 Cloud Technology in Robotics
1.6 AI and Machine Learning Solution
1.7 Connectivity Technology including 5G
1.8 Industrial Automation and Cloud Robotics
1.9 IoT, Industrial IoT and Cloud Robotics
1.10 Collaborative Robots
1.11 Market Challenges and Opportunities

2 Cloud Robotics Ecosystem Analysis
2.1 Market Segmentation
2.2 Ecosystem and Players
2.3 Most Likely Applications
2.4 Anticipated Regional Adoption
2.5 Emerging Cloud Robotics Business Models
2.6 Robotics Production
2.7 Robotics Cost Structure
2.8 Robotics ROI
2.9 Cloud Robotics Intellectual Property
2.10 Research and Development Activities

3 Cloud Robotics Market 2017 - 2022
3.1 Global Market Forecast 2017 - 2022
3.2 Regional Cloud Robotics Market Forecast

4 Company Analysis
4.1 Rockwell Automation Inc.
4.2 KUKA AG
4.3 ABB Group
4.4 FANUC Corporation
4.5 Yaskawa Electric Corporation
4.6 Universal Robots
4.7 Tend.ai
4.8 Rapyuta Robotics Co. Ltd.
4.9 HotBlack Robotics Srl
4.10 Calvary Robotics
4.11 Motion Controls Robotics Inc.
4.12 Wolf Robotics LLC
4.13 Tech-Con Automation Inc.
4.14 Matrix Industrial Automation
4.15 Automation IG
4.16 Ortelio Ltd
4.17 SoftBank Robotics Holding Corp.
4.18 iRobot Corp.
4.19 Google Inc.
4.20 IBM Corporation
4.21 Microsoft Corporation
4.22 Ecovacs Robotics Inc.
4.23 CloudMinds
4.24 Ozobot & Evollve Inc.
4.25 Segway Inc. and Ninebot
4.26 Erle Robotics
4.27 Adept Technology
4.28 Ekso Bionics
4.29 Lockheed Martin
4.30 Mazor Robotics
4.31 Pv-Kraftwerker
4.32 ReconRobotics Inc.
4.33 Seegrid
4.34 Spacex

5 Conclusions and Recommendations

6 Appendix
6.1 Total Robot Shipments
6.2 Robot Shipments by Type
6.3 Robot Shipments by Application Segment
6.4 Robot Shipments by Region

Big Data Market: Business Case, Market Analysis and Forecasts 2017 - 2022

1 Background
1.1 Introduction
1.2 Scope of the Report
1.3 Target Audience
1.4 Companies in Report

2 Executive Summary

3 Big Data Technology and Business Case
3.1 Defining Big Data
3.2 Key Characteristics of Big Data
3.3 Big Data Technology
3.4 New Paradigms and Techniques
3.5 Big Data Roadmap
3.6 Market Drivers
3.7 Market Barriers

4 Key Sectors for Big Data
4.1 Industrial Internet and Machine-to-Machine
4.2 Retail and Hospitality
4.3 Media
4.4 Utilities
4.5 Financial Services
4.6 Healthcare and Pharmaceutical
4.7 Telecommunications
4.8 Government and Homeland Security
4.9 Other Sectors

5 The Big Data Value Chain
5.1 Fragmentation in the Big Data Value
5.2 Data Acquisitioning & Provisioning
5.3 Data Warehousing & Business Intelligence
5.4 Analytics & Visualization
5.5 Actioning and Business Process Management
5.6 Data Governance

6 Big Data Analytics
6.1 What is Big Data Analytics?
6.2 The Importance of Big Data Analytics
6.3 Reactive vs. Proactive Analytics
6.4 Technology and Implementation Approaches

7 Standardization and Regulatory Initiatives
7.1 Cloud Standards Customer Council
7.2 National Institute of Standards and Technology
7.3 OASIS
7.4 Open Data Foundation
7.5 Open Data Center Alliance
7.6 Cloud Security Alliance
7.7 International Telecommunications Union
7.8 International Organization for Standardization

8 Global Markets and Forecasts for Big Data
8.1 Global Big Data Markets 2017 - 2022
8.2 Regional Markets for Big Data 2017 - 2022
8.3 Big Data Revenue by Product Segment 2017 - 2022

9 Key Players in the Big Data Market
9.1 Vendor Assessment Matrix
9.2 1010Data
9.3 Accenture
9.4 Actian Corporation
9.5 Amazon
9.6 Apache Software Foundation
9.7 APTEAN (Formerly CDC Software)
9.8 Booz Allen Hamilton
9.9 Bosch Software Innovations: Bosch IoT Suite
9.10 Capgemini
9.11 Cisco Systems
9.12 Cloudera
9.13 CRAY Inc.
9.14 Computer Science Corporation (CSC)
9.15 DataDirect Network
9.16 Dell
9.17 Deloitte
9.18 EMC
9.19 Facebook
9.20 Fujitsu
9.21 General Electric (GE)
9.22 GoodData Corporation
9.23 Google
9.24 Guavus
9.25 HP
9.26 Hitachi Data Systems
9.27 Hortonworks
9.28 IBM
9.29 Informatica
9.30 Intel
9.31 Jasper (Cisco Jasper)
9.32 Juniper Networks
9.33 Marklogic
9.34 Microsoft
9.35 MongoDB (Formerly 10Gen)
9.36 MU Sigma
9.37 Netapp
9.38 NTT Data
9.39 Open Text (Actuate Corporation)
9.40 Opera Solutions
9.41 Oracle
9.42 Pentaho
9.43 Qlik Tech
9.44 Quantum
9.45 Rackspace
9.46 Revolution Analytics
9.47 Salesforce
9.48 SAP
9.49 SAS Institute
9.50 Sisense
9.51 Software AG/Terracotta
9.52 Splunk
9.53 Sqrrl
9.54 Supermicro
9.55 Tableau Software
9.56 Tata Consultancy Services
9.57 Teradata
9.58 Think Big Analytics
9.59 TIBCO
9.60 Tidemark Systems
9.61 VMware (Part of EMC)
9.62 Wipro
9.63 Workday (Platfora)
9.64 Zettics

10 Appendix: Big Data Support of Streaming IoT Data

Real-time IoT Data in Smart Cities, Buildings, and Homes 2017 - 2022

1 Executive Summary

2 Introduction
2.1 Smart Cities
2.2 Intelligent Buildings
2.3 Connected Homes

3 Real Time IoT Data Analytics in Smart City Market 2017 - 2022
3.1 Global Market
3.2 Market by Type
3.3 Market by Deployment Model
3.4 Market by Sector
3.5 Market by Region

4 Real Time IoT Data Analytics Market in Intelligent Buildings 2017 - 2022
4.1 Global Market
4.2 Market by Type
4.3 Market by Business Model
4.4 Market by End User
4.5 Market by Region

5 Real Time IoT Data Analytics Market in Connected Homes 2017 - 2022
5.1 Global Market
5.2 Market by Type
5.3 Market by Business Model
5.4 Market by Region

6 Conclusions and Recommendations
6.1 Smart Cities
6.2 Intelligent Buildings
6.3 Connected Homes

Robotics in Industrial, Enterprise, Military, and Consumer Products, Services, and Solutions 2017 - 2022

1 Executive Summary

2 Introduction
2.1 Market Segmentation
2.2 Market Overview

3 Robotics Companies and Solutions
3.1 Americas
3.2 Asia-Pacific
3.3 Europe

4 Robotics Market Analysis and Forecasts
4.1 Global Robotics Market 2017 - 2022
4.2 Robotics Market by Segment 2017 - 2022
4.3 Industrial Robotics Market 2017 - 2022
4.4 Consumer Robotics Market 2017 - 2022
4.5 Enterprise Robotics Market 2017 - 2022
4.6 Military and Government Robotics Market 2017 - 2022
4.7 Robot Shipment Forecast 2017 - 2022

5 Conclusions and Recommendations

Internet of Things (IoT) Digital Twinning 2017 - 2022

1 Executive Summary

2 Introduction

2.1 Understanding Digital Twinning
2.2 Important Concepts

3 Supporting Technologies
3.1 Industrial IoT and Industry 4.0
3.2 Pairing Technology
3.3 Cyber Physical Systems
3.4 Augmented, Virtual, and Mixed Reality
3.5 Artificial Intelligence Technologies
3.6 Additive Manufacturing and 3D Printing
3.7 Digital Thread for Additive Manufacturing

4 Digital Twin Product and Service Ecosystem
4.1 Digital Twinning Impact on Industry Segments
4.2 Application Development and Operations
4.3 Digital Twin Use Cases and Applications
4.4 Digital Twinning as a Service (DTaaS)

5 IoT Digital Twinning Market Forecast 2017 - 2022
5.1 Global Market Forecast 2017 - 2022
5.2 Regional Market Forecast 2017 - 2022
5.3 Digital Twinning Connected IoT Things Forecast 2017 - 2022

6 Vendor Analysis
6.1 Google
6.2 General Electric
6.3 PTC
6.4 Siemens PLM Software
6.5 Computer Science Corporation
6.6 SAP SE
6.7 Sight Machine Inc.
6.8 Eclipse Software
6.9 Amazon Web Services
6.10 Oracle Corporation
6.11 Dassault Systemes
6.12 ANSYS Inc.
6.13 Arrayent Inc.
6.14 Autodesk Inc.
6.15 Sysmex Corporation
6.16 Core Systems

7 Conclusions and Recommendations

For more information about this report visit https://www.researchandmarkets.com/research/t97798/industrial

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