Big Data, Analytics, and Internet of Things (IoT) in Public Transport and Intelligent Transport Systems (ITS)
OVERVIEW
Data that is uncorrelated and does not have a pre-defined data model and is not organized in a pre-defined manner requires special handling and analytics techniques. The common industry term, Big Data, represents unstructured data sets that are large, complex, and prohibitively difficult to process using traditional management tools. Vehicles are at the forefront of a major convergence happening that includes a few key technologies: 5G, Artificial Intelligence, Data Management (Big Data, Analytics, Visualization, etc.), Cloud Technologies, and IoT.
Technology and market advances in three separate, yet related, areas are poised to cause disintermediation as well as many market opportunities for companies across a broad spectrum within telecom and digital technologies. This report provides an in-depth assessment of Big Data, Analytics, and Internet of Things (IoT) in transportation market, including business models, market drivers, challenges, and a an assessment of the industry from 2017 to 2022.
TARGET AUDIENCE:
Data that is uncorrelated and does not have a pre-defined data model and is not organized in a pre-defined manner requires special handling and analytics techniques. The common industry term, Big Data, represents unstructured data sets that are large, complex, and prohibitively difficult to process using traditional management tools. Vehicles are at the forefront of a major convergence happening that includes a few key technologies: 5G, Artificial Intelligence, Data Management (Big Data, Analytics, Visualization, etc.), Cloud Technologies, and IoT.
Technology and market advances in three separate, yet related, areas are poised to cause disintermediation as well as many market opportunities for companies across a broad spectrum within telecom and digital technologies. This report provides an in-depth assessment of Big Data, Analytics, and Internet of Things (IoT) in transportation market, including business models, market drivers, challenges, and a an assessment of the industry from 2017 to 2022.
TARGET AUDIENCE:
- Telematics companies
- Wireless service providers
- Automobile manufacturers
- Data and analytics companies
- Semiconductor manufacturers
- Embedded systems companies
- Component and OEM providers
- Wearable technology companies
- Wireless infrastructure providers
- Telematics and M2M apps providers
- IoT infrastructure and apps providers
- Public and personal safety companies
1 INTRODUCTION
1.1 Executive Summary
1.2 Target Audience
1.3 Companies Mentioned
2 BIG DATA APPLICATIONS IN INDUSTRY VERTICALS OVERVIEW
2.1 Big Data
2.2 Big Data Applications
2.2.1 Analytics
2.3 Big Data Impact on industry Verticals
2.3.1 Big Data in Telecommunications
2.3.2 Big Data in Media
2.3.3 Big Data Manufacturing
2.3.4 Big Data in Logistics
2.3.5 Big Data in Data Centers
2.4 Big Data Impact on the ICT Industry
2.4.1 Big Data and Decision Making
2.4.2 Big Data Techniques
2.4.3 MapReduce
2.4.4 Hadoop
2.4.5 Cascalog
2.4.6 MemCache
2.4.7 AppEngine
2.4.8 Java and Python Based
2.4.9 Persistent Storage via API in GFS II and BigTable
2.4.10 SSL encryption
2.4.11 SQL Database Support
2.4.12 Developer and Technical Support
3 BIG DATA AND ANALYTICS FOR THE INTELLIGENT TRANSPORT SYSTEMS (ITS)
3.1 ITS Architecture
3.1.1 Cloud Applications for ITS
3.1.2 Communications
3.1.3 Operators Role in the ITS Value Chain
3.1.4 Sensors
3.1.5 Traffic Information
3.2 Big Data Applications for ITS
3.2.1 Here and Now Data Approach
3.2.2 Time Series Analysis
3.2.3 Cluster Analysis
3.2.4 Classification
3.2.5 Change-Point Analysis
3.3 Cloud and Data Analytics
3.3.1 Public Cloud VS Private Clouds
3.3.2 Big Data in the Cloud
3.3.3 Data as a Service
3.3.4 Challenges
3.4 Artificial Networks
3.4.1 Clustering Traffic States
3.4.2 Traffic Routing Problem
3.5 Big Data Improvements to the ITS
3.5.1 Traffic Management with Big Data Analytics
3.5.2 The Improvement of the Transport Industry
3.5.3 Decision Making
3.5.4 Safety Improvement
3.6 Data Analysis for Traffic Management
3.7 Data for Traffic Routes and Decision Making
3.7.1 Platform Management
3.7.2 Journey Planning
3.8 Accident Preventions
3.8.1 Smart Lighting and Energy Efficiency
3.9 Online Ticket Booking and Real-Time Information
3.9.1 Smart Payment Systems
4 AUTONOMOUS SMART PUBLIC TRANSPORTATION
4.1 Electric Buses
4.1.1 Current Progress
4.1.2 Challenges
4.1.3 Battery Life Issues
4.1.4 Tesla gigafactory
4.2 Big Data Models for Smart Public Transport
4.2.1 Smart Navigation
4.2.2 GPS Tracking
4.2.3 Sensors and Communications
4.2.4 Big Data Analytics and Future Direction
5 INTERNET OF THINGS (IOT) AND ITS
5.1 Technologies
5.1.1 Communication Protocols
5.1.2 Sensory Inputs
5.2 Challenges
5.2.1 Security
5.3 Market Analysis
6 BIG DATA, ANALYTICS, AND IOT IN ITS MARKET ANALYSIS
6.1 Analysis
6.2 Market Overview
6.3 Challenges
6.4 Market Trends
6.5 Forecasts
6.5.1 By Infrastructure (Platforms, Hardware, and Software)
6.5.2 By Region
7 VENDOR LANDSCAPE (ITS SERVICE PROVIDERS)
7.1 Kapsch
7.1.1 Products landscape
7.1.2 Products reviews
7.1.3 Products benefits
7.1.4 Products Analysis
7.1.5 SWOT Analysis
7.1.6 Analysis methods
7.1.7 M&A Analysis
7.1.8 Clients’ Review
7.1.9 Analyst Review
7.1.10 Industry Expert Reviews
7.2 SWARCO
7.2.1 Products landscape
7.2.2 Products reviews
7.2.3 Products benefits
7.2.4 Products Analysis
7.2.5 SWOT Analysis
7.2.6 Analysis methods
7.2.7 M&A Analysis
7.2.8 Clients’ Review
7.2.9 Analyst Review
7.2.10 Industry Expert Reviews
7.3 Q-Free
7.3.1 Products landscape
7.3.2 Products reviews
7.3.3 Products benefits
7.3.4 Products Analysis
7.3.5 SWOT Analysis
7.3.6 Analysis methods
7.3.7 M&A Analysis
7.3.8 Clients’ Review
7.3.9 Analyst Review
7.3.10 Industry Expert Reviews
7.4 Siemens
7.4.1 Products Landscape
7.4.2 Products Reviews
7.4.3 Products Benefits
7.4.4 Products Analysis
7.4.5 SWOT Analysis
7.4.6 Analysis methods
7.4.7 M&A Analysis
7.4.8 Clients’ Review
7.4.9 Analyst Review
7.4.10 Industry Expert Reviews
7.5 PTV Group
7.5.1 Products landscape
7.5.2 Products reviews
7.5.3 Products benefits
7.5.4 Products Analysis
7.5.5 SWOT Analysis
7.5.6 Analysis methods
7.5.7 M&A Analysis
7.5.8 Clients’ Review
7.5.9 Analyst Review
7.5.10 Industry Expert Reviews
7.6 Hitachi
7.6.1 Products landscape
7.6.2 Products reviews
7.6.3 Products benefits
7.6.4 Products Analysis
7.6.5 SWOT Analysis
7.6.6 Analysis methods
7.6.7 M&A Analysis
7.6.8 Clients’ Review
7.6.9 Analyst Review
7.6.10 Industry Expert Reviews
7.7 TomTom
7.7.1 Products landscape
7.7.2 Products reviews
7.7.3 Products benefits
7.7.4 Products Analysis
7.7.5 SWOT Analysis
7.7.6 Analysis methods
7.7.7 M&A Analysis
7.7.8 Clients’ Review
7.7.9 Analyst Review
7.7.10 Industry Expert Reviews
7.8 Denso
7.8.1 Products landscape
7.8.2 Products reviews
7.8.3 Products benefits
7.8.4 Products Analysis
7.8.5 SWOT Analysis
7.8.6 Analysis methods
7.8.7 M&A Analysis
7.8.8 Clients’ Review
7.8.9 Analyst Review
7.8.10 Industry Expert Reviews
7.9 Bosch
7.9.1 Products landscape
7.9.2 Products reviews
7.9.3 Products benefits
7.9.4 Products Analysis
7.9.5 SWOT Analysis
7.9.6 Analysis methods
7.9.7 M&A Analysis
7.9.8 Clients’ Review
7.9.9 Analyst Review
7.9.10 Industry Expert Reviews
7.10 Continental
7.10.1 Products landscape
7.10.2 Products reviews
7.10.3 Products benefits
7.10.4 Products Analysis
7.10.5 SWOT Analysis
7.10.6 Analysis methods
7.10.7 M&A Analysis
7.10.8 Clients’ Review
7.10.9 Analyst Review
7.10.10 Industry Expert Reviews
7.11 IBM
7.11.1 Products landscape
7.11.2 Products reviews
7.11.3 Products benefits
7.11.4 Products Analysis
7.11.5 SWOT Analysis
7.11.6 Analysis methods
7.11.7 M&A Analysis
7.11.8 Clients’ Review
7.11.9 Analyst Review
7.11.10 Industry Expert Reviews
7.12 Cisco
7.12.1 Products landscape
7.12.2 Products reviews
7.12.3 Products benefits
7.12.4 Products Analysis
7.12.5 SWOT Analysis
7.12.6 Analysis methods
7.12.7 M&A Analysis
7.12.8 Clients’ Review
7.12.9 Analyst Review
7.12.10 Industry Expert Reviews
7.13 Logica
7.13.1 Products landscape
7.13.2 Products reviews
7.13.3 Products benefits
7.13.4 Products Analysis
7.13.5 SWOT Analysis
7.13.6 Analysis methods
7.13.7 M&A Analysis
7.13.8 Clients’ Review
7.13.9 Analyst Review
7.13.10 Industry Expert Reviews
7.14 Xerox
7.14.1 Products landscape
7.14.2 Products reviews
7.14.3 Products benefits
7.14.4 Products Analysis
7.14.5 SWOT Analysis
7.14.6 Analysis methods
7.14.7 M&A Analysis
7.14.8 Clients’ Review
7.14.9 Analyst Review
7.14.10 Industry Expert Reviews
1.1 Executive Summary
1.2 Target Audience
1.3 Companies Mentioned
2 BIG DATA APPLICATIONS IN INDUSTRY VERTICALS OVERVIEW
2.1 Big Data
2.2 Big Data Applications
2.2.1 Analytics
2.3 Big Data Impact on industry Verticals
2.3.1 Big Data in Telecommunications
2.3.2 Big Data in Media
2.3.3 Big Data Manufacturing
2.3.4 Big Data in Logistics
2.3.5 Big Data in Data Centers
2.4 Big Data Impact on the ICT Industry
2.4.1 Big Data and Decision Making
2.4.2 Big Data Techniques
2.4.3 MapReduce
2.4.4 Hadoop
2.4.5 Cascalog
2.4.6 MemCache
2.4.7 AppEngine
2.4.8 Java and Python Based
2.4.9 Persistent Storage via API in GFS II and BigTable
2.4.10 SSL encryption
2.4.11 SQL Database Support
2.4.12 Developer and Technical Support
3 BIG DATA AND ANALYTICS FOR THE INTELLIGENT TRANSPORT SYSTEMS (ITS)
3.1 ITS Architecture
3.1.1 Cloud Applications for ITS
3.1.2 Communications
3.1.3 Operators Role in the ITS Value Chain
3.1.4 Sensors
3.1.5 Traffic Information
3.2 Big Data Applications for ITS
3.2.1 Here and Now Data Approach
3.2.2 Time Series Analysis
3.2.3 Cluster Analysis
3.2.4 Classification
3.2.5 Change-Point Analysis
3.3 Cloud and Data Analytics
3.3.1 Public Cloud VS Private Clouds
3.3.2 Big Data in the Cloud
3.3.3 Data as a Service
3.3.4 Challenges
3.4 Artificial Networks
3.4.1 Clustering Traffic States
3.4.2 Traffic Routing Problem
3.5 Big Data Improvements to the ITS
3.5.1 Traffic Management with Big Data Analytics
3.5.2 The Improvement of the Transport Industry
3.5.3 Decision Making
3.5.4 Safety Improvement
3.6 Data Analysis for Traffic Management
3.7 Data for Traffic Routes and Decision Making
3.7.1 Platform Management
3.7.2 Journey Planning
3.8 Accident Preventions
3.8.1 Smart Lighting and Energy Efficiency
3.9 Online Ticket Booking and Real-Time Information
3.9.1 Smart Payment Systems
4 AUTONOMOUS SMART PUBLIC TRANSPORTATION
4.1 Electric Buses
4.1.1 Current Progress
4.1.2 Challenges
4.1.3 Battery Life Issues
4.1.4 Tesla gigafactory
4.2 Big Data Models for Smart Public Transport
4.2.1 Smart Navigation
4.2.2 GPS Tracking
4.2.3 Sensors and Communications
4.2.4 Big Data Analytics and Future Direction
5 INTERNET OF THINGS (IOT) AND ITS
5.1 Technologies
5.1.1 Communication Protocols
5.1.2 Sensory Inputs
5.2 Challenges
5.2.1 Security
5.3 Market Analysis
6 BIG DATA, ANALYTICS, AND IOT IN ITS MARKET ANALYSIS
6.1 Analysis
6.2 Market Overview
6.3 Challenges
6.4 Market Trends
6.5 Forecasts
6.5.1 By Infrastructure (Platforms, Hardware, and Software)
6.5.2 By Region
7 VENDOR LANDSCAPE (ITS SERVICE PROVIDERS)
7.1 Kapsch
7.1.1 Products landscape
7.1.2 Products reviews
7.1.3 Products benefits
7.1.4 Products Analysis
7.1.5 SWOT Analysis
7.1.6 Analysis methods
7.1.7 M&A Analysis
7.1.8 Clients’ Review
7.1.9 Analyst Review
7.1.10 Industry Expert Reviews
7.2 SWARCO
7.2.1 Products landscape
7.2.2 Products reviews
7.2.3 Products benefits
7.2.4 Products Analysis
7.2.5 SWOT Analysis
7.2.6 Analysis methods
7.2.7 M&A Analysis
7.2.8 Clients’ Review
7.2.9 Analyst Review
7.2.10 Industry Expert Reviews
7.3 Q-Free
7.3.1 Products landscape
7.3.2 Products reviews
7.3.3 Products benefits
7.3.4 Products Analysis
7.3.5 SWOT Analysis
7.3.6 Analysis methods
7.3.7 M&A Analysis
7.3.8 Clients’ Review
7.3.9 Analyst Review
7.3.10 Industry Expert Reviews
7.4 Siemens
7.4.1 Products Landscape
7.4.2 Products Reviews
7.4.3 Products Benefits
7.4.4 Products Analysis
7.4.5 SWOT Analysis
7.4.6 Analysis methods
7.4.7 M&A Analysis
7.4.8 Clients’ Review
7.4.9 Analyst Review
7.4.10 Industry Expert Reviews
7.5 PTV Group
7.5.1 Products landscape
7.5.2 Products reviews
7.5.3 Products benefits
7.5.4 Products Analysis
7.5.5 SWOT Analysis
7.5.6 Analysis methods
7.5.7 M&A Analysis
7.5.8 Clients’ Review
7.5.9 Analyst Review
7.5.10 Industry Expert Reviews
7.6 Hitachi
7.6.1 Products landscape
7.6.2 Products reviews
7.6.3 Products benefits
7.6.4 Products Analysis
7.6.5 SWOT Analysis
7.6.6 Analysis methods
7.6.7 M&A Analysis
7.6.8 Clients’ Review
7.6.9 Analyst Review
7.6.10 Industry Expert Reviews
7.7 TomTom
7.7.1 Products landscape
7.7.2 Products reviews
7.7.3 Products benefits
7.7.4 Products Analysis
7.7.5 SWOT Analysis
7.7.6 Analysis methods
7.7.7 M&A Analysis
7.7.8 Clients’ Review
7.7.9 Analyst Review
7.7.10 Industry Expert Reviews
7.8 Denso
7.8.1 Products landscape
7.8.2 Products reviews
7.8.3 Products benefits
7.8.4 Products Analysis
7.8.5 SWOT Analysis
7.8.6 Analysis methods
7.8.7 M&A Analysis
7.8.8 Clients’ Review
7.8.9 Analyst Review
7.8.10 Industry Expert Reviews
7.9 Bosch
7.9.1 Products landscape
7.9.2 Products reviews
7.9.3 Products benefits
7.9.4 Products Analysis
7.9.5 SWOT Analysis
7.9.6 Analysis methods
7.9.7 M&A Analysis
7.9.8 Clients’ Review
7.9.9 Analyst Review
7.9.10 Industry Expert Reviews
7.10 Continental
7.10.1 Products landscape
7.10.2 Products reviews
7.10.3 Products benefits
7.10.4 Products Analysis
7.10.5 SWOT Analysis
7.10.6 Analysis methods
7.10.7 M&A Analysis
7.10.8 Clients’ Review
7.10.9 Analyst Review
7.10.10 Industry Expert Reviews
7.11 IBM
7.11.1 Products landscape
7.11.2 Products reviews
7.11.3 Products benefits
7.11.4 Products Analysis
7.11.5 SWOT Analysis
7.11.6 Analysis methods
7.11.7 M&A Analysis
7.11.8 Clients’ Review
7.11.9 Analyst Review
7.11.10 Industry Expert Reviews
7.12 Cisco
7.12.1 Products landscape
7.12.2 Products reviews
7.12.3 Products benefits
7.12.4 Products Analysis
7.12.5 SWOT Analysis
7.12.6 Analysis methods
7.12.7 M&A Analysis
7.12.8 Clients’ Review
7.12.9 Analyst Review
7.12.10 Industry Expert Reviews
7.13 Logica
7.13.1 Products landscape
7.13.2 Products reviews
7.13.3 Products benefits
7.13.4 Products Analysis
7.13.5 SWOT Analysis
7.13.6 Analysis methods
7.13.7 M&A Analysis
7.13.8 Clients’ Review
7.13.9 Analyst Review
7.13.10 Industry Expert Reviews
7.14 Xerox
7.14.1 Products landscape
7.14.2 Products reviews
7.14.3 Products benefits
7.14.4 Products Analysis
7.14.5 SWOT Analysis
7.14.6 Analysis methods
7.14.7 M&A Analysis
7.14.8 Clients’ Review
7.14.9 Analyst Review
7.14.10 Industry Expert Reviews
