Deep Learning-Based Machine Vision in Smart Cities Image

Deep Learning-Based Machine Vision in Smart Cities

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Actionable Benefits

  • Provide insight into the adoption of AI in smart city video surveillance market now and moving forward.
  • Understand the current challenges in the adoption of AI in smart city surveillance.
  • Identify commercial opportunities with the emergence of 5G and edge computing.

Critical Questions Answered

  • What is the current state of AI adoption for smart city video surveillance solution?
  • Who are the key players in China?
  • Who are the key video management system and video analytics vendors?

Research Highlights

  • Installed base of smart city cameras with edge AI chipsets.
  • Market share of key camera vendors for global market.
  • Analysis of competitive landscape in the Chinese market.

Who Should Read This?

  • Incumbent vendors and system integrators.
  • New AI chipset vendors targeting edge AI gateways and servers.
  • Strategy planners and advisors looking to ascertain new market niches and partnership opportunities.

Table of Contents

1. EXECUTIVE SUMMARY

2. INTRODUCTION TO DL-BASED MACHINE VISION IN SMART CITIES

3. TECHNOLOGY ADVANCEMENTS IN DL-BASED MACHINE VISION

3.1. Proliferation of On-Device and Gateway AI Chipsets
3.2. Continuous Improvement of Cloud AI Capabilities
3.3. Emergence of Next-Generation Connectivity

4. HEADWINDS

4.1. Lack of Common Standard
4.2. Concerns over AI Ethics
4.3. Technology Decoupling of the United States and China

5. COMPETITIVE LANDSCAPE

5.1. List of Key Vendors
5.2. Key Vendor Profile

6. MARKET SIZE, MARKET SHARE, AND FORECASTS

6.1. China as the Growth Engine

7. FUTURE OF DL-BASED MACHINE VISION IN SMART CITIES

7.1. Multimodal and Multi-task
7.2. Federated Learning
7.3. More Efficient Video Processing
7.4. Beyond Conventional Images and Video Streams