ICT has led to transformational breakthroughs in the automotive landscape, enabling companies to gain a competitive advantage, creating new ways of generating revenue, and convergence of technologies that has disrupted the status quo. This report outlines the different types of information and communication technologies disrupting the automotive space, the factors driving their adoption, barriers to adoption, the use cases, emerging business models, and new revenue streams.
This report covers disruptive Information and Communication Technologies disrupting the automotive sector, including
- Machine Learning
- Computer Vision
- Advanced Analytics
- Augmented Reality
- Virtual Reality
In brief, this research service provides the following:
- A brief overview of ICT transforming the automotive sector
- Technology overview and driver and challenges
- An overview of how each technology impacts the automotive space
- Who are the major players in each technology area?
- Relevant use cases of industry players
- Convergence Scenarios
- Emerging business models
- Key finding and analyst POV
2.2 IoT Analytics Will Drive Efficiencies in the Automotive Sector
2.3 Usage-based Insurance Models Will Reward Good Driver Behavior
4.2 Security and Lowered Transaction Costs are Key Drivers to Blockchain Adoption
4.3 Lack of Technological Maturity is a Barrier to Blockchain Adoption
4.4 How do Auto Companies Use Blockchain?
4.5 Major Industry Initiatives Enable Innovative Business Models
4.6 Different Blockchain Participants Offer Differing Value Propositions
5.2 Machine Learning Enables Deeper Understanding of the Human Genome
5.3 Big Data, Algorithms, and GPUs Synergize to Accelerate ML Developments
5.4 Unsupervised Learning Will be Used to Detect Parts Failures
5.5 How is Machine Learning Used in Automotive?
5.6 ML Platforms Optimize Decision-making
5.7 Computer Vision can Improve Accuracy and Enable Automation
5.8 Lack of Skills and Security Concerns Hinder Adoption Growth
5.9 How is Computer Vision Transforming the Automotive Space?
5.10 Who are the Frontrunners in CV in the Automotive Space?
6.3 DSRC and C-V2X – A comparison
6.4 5G Will Enable Faster, More Secure Transactions at Ultra Low Levels of Latency
6.5 Cost and Speed will Remain the Key Drivers for 5G Adoption
7.2 The Evolution of Advanced Analytics
7.3 Advanced Analytics Drivers Explained
7.4 Advanced Analytics Challenges Explained
7.5 How Will Advanced Analytics Impact the Automotive Sector?
7.6 Big Data Analytics is Imperative for a Competitive Edge
8.2 Vendors are Increasingly Looking to Build Automated Machine Intelligence
8.3 How is Cybersecurity Important in the Automotive Sector?
8.4 Artificial Intelligence and Cryptography Are the Future of Cybersecurity
8.5 Developing Intelligent Security Systems
9.2 Content Creation is Still in Nascent Stages of Development
9.3 Major Innovations in AR are Focused on Graphical Overlays to Assist with Driving Directions
10.2 IoT Serves as a Catalyst Driving VR Growth
10.3 Major Innovations in VR are Centered Around Creation of Showrooms of the Future
10.4 ICT Innovations for Automotive – The Road Ahead
11.2 Use Case: Robotic Taxi Service a Reality
11.3 Use Case: Computer Vision Video Analytics in Automotive
11.4 Use Case: DSRC in V2V Communication Demonstration for Off-Road
11.5 Use Case: EyeSight’s Eye Tracking Tech in the Automotive Industry
11.6 Use Case: Truck Platooning Will Use V2V to Enable Fuel Efficiency
12.2 Autonomous Drive Correction