Computer Vision in Navigation Market by Component, Product, Application

Description

List of Tables

[188 Pages Report] The Computer Vision in Navigation Market size was estimated at USD 1.13 billion in 2023 and expected to reach USD 1.28 billion in 2024, at a CAGR 13.27% to reach USD 2.71 billion by 2030.

Computer vision in navigation involves integrating advanced image processing and AI algorithms into navigation systems to interpret and analyze visual data, aiding in route planning, obstacle detection, and autonomous navigation. In the automotive sector, it powers self-driving cars and Advanced driver assistance systems (ADAS), while in aerospace, it enhances the capabilities of autonomous drones and satellite navigation. For maritime applications, it aids in the navigation of autonomous ships. Consumer electronics benefit from AR navigation apps and smart wearables, and the healthcare sector utilizes this technology in robotic surgical systems and navigation aids for visually impaired individuals. Technological advances, including AI, machine learning, sensor improvements, increased demand for autonomous vehicles, and robust safety regulations drive market growth. However, challenges include high computational requirements, R&D costs, regulatory hurdles, and privacy concerns. Nevertheless, smart city initiatives for urban mobility, fleet management in logistics, sophisticated navigation aids in healthcare, and innovative uses of drones in commercial delivery create growth opportunities. Promising areas for further research include edge computing for real-time data processing, more efficient machine learning algorithms, sensor fusion, human-machine interfaces, and energy-efficient solutions. This ongoing innovation will undoubtedly shape future applications and market dynamics.

KEY MARKET STATISTICS
Base Year [2023]	USD 1.13 billion
Estimated Year [2024]	USD 1.28 billion
Forecast Year [2030]	USD 2.71 billion
CAGR (%)	13.27%

Regional Insights

The Americas region spearheads advancements in the automotive sector through significant players focusing on advanced driver assistance systems and autonomous vehicles. Furthermore, this region supports innovation with policies to improve navigation in challenging conditions. The EU countries are pioneers in research for autonomous vehicles and smart cities, with Germany, France, and the UK heavily invested. The Middle East, led by the UAE and Saudi Arabia, leverages computer vision for smart city initiatives, while Africa slowly adopts these technologies due to infrastructural challenges. Consumer behavior in APAC shows a preference for intelligent navigation systems due to rapid urbanization, while in the Americas, there is a high demand for advanced automotive technologies prioritizing safety. European consumers in EMEA value sustainable and cutting-edge transportation solutions, with the Middle East trending towards luxury technology. In the Asia-Pacific region, computer vision in navigation showcases growth due to significant government and private sector investments in AI applications for autonomous vehicles and augmented reality maps. Furthermore, the APAC region excels in integrating computer vision with transportation to enhance safety and the emergence of startup activities and governmental support focusing on traffic management.

Market Insights

Market Dynamics

The market dynamics represent an ever-changing landscape of the Computer Vision in Navigation Market by providing actionable insights into factors, including supply and demand levels. Accounting for these factors helps design strategies, make investments, and formulate developments to capitalize on future opportunities. In addition, these factors assist in avoiding potential pitfalls related to political, geographical, technical, social, and economic conditions, highlighting consumer behaviors and influencing manufacturing costs and purchasing decisions.

Market Drivers
- Increasing demand for highly autonomous vehicles and the need for road safety
- Growing use of drones in commercial delivery and disaster management
- Supportive government policies in smart infrastructure development for connected and autonomous vehicle

Market Restraints
- High computational requirements coupled with continuous improvements in algorithms and hardware

Market Opportunities
- Enhancing capabilities in AI and machine learning, along with improvements in sensor technologies
- Development of navigation aids for surgical robots and visually impaired individuals

Market Challenges
- Issues related to data collection, storage, and use, along with the risk of cyber attacks

Market Segmentation Analysis
- Component: Burgeoning adoption of the software to analyze and interpret vehicle data
- Application: Evolving utilization of computer vision in autonomous vehicles, enabling the creation of accurate and high-resolution maps

Market Disruption Analysis
Porter's Five Forces Analysis
Value Chain & Critical Path Analysis
Pricing Analysis
Technology Analysis
Patent Analysis
Trade Analysis
Regulatory Framework Analysis

FPNV Positioning Matrix

The FPNV positioning matrix is essential in evaluating the market positioning of the vendors in the Computer Vision in Navigation Market. This matrix offers a comprehensive assessment of vendors, examining critical metrics related to business strategy and product satisfaction. This in-depth assessment empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success, namely Forefront (F), Pathfinder (P), Niche (N), or Vital (V).

Market Share Analysis

The market share analysis is a comprehensive tool that provides an insightful and in-depth assessment of the current state of vendors in the Computer Vision in Navigation Market. By meticulously comparing and analyzing vendor contributions, companies are offered a greater understanding of their performance and the challenges they face when competing for market share. These contributions include overall revenue, customer base, and other vital metrics. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With these illustrative details, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.

Recent Developments

ABB Expands Autonomous Mobile Robot Capabilities with Sevensense Acquisition, Driving Innovation in AI-Enabled 3D Vision Navigation

ABB has acquired Swiss start-up Sevensense, an AI-powered 3D vision navigation technology provider for autonomous mobile robots (AMRs). Sevensense, founded in 2018 as a spin-off from ETH Zurich, is set to enhance ABB's robotic capabilities by integrating advanced Visual Simultaneous Localization and Mapping (Visual SLAM) technology. [Published On: 2024-01-16]

Introduction of Orca AI's SeaPod with Advanced Computer Vision and AI

Orca AI has introduced SeaPod, an advanced situational awareness system for ships, integrated with eight sensitive cameras to assist the crew on the bridge comprehensively. This fully automated navigation platform leverages artificial intelligence (AI) and computer vision to enhance target detection and provide an unparalleled field of view. Installed on the compass deck, SeaPod offers 225° field-of-view coverage with its standard cameras and 100° thermal coverage using forward-looking infrared (FLIR) thermographic imaging, allowing the detection of small objects up to four nautical miles away in diverse weather conditions. [Published On: 2024-01-11]

Strategy Analysis & Recommendation

The strategic analysis is essential for organizations seeking a solid foothold in the global marketplace. Companies are better positioned to make informed decisions that align with their long-term aspirations by thoroughly evaluating their current standing in the Computer Vision in Navigation Market. This critical assessment involves a thorough analysis of the organization's resources, capabilities, and overall performance to identify its core strengths and areas for improvement.

Key Company Profiles

The report delves into recent significant developments in the Computer Vision in Navigation Market, highlighting leading vendors and their innovative profiles. These include ABB Ltd., Allied Vision Technologies GmbH, Amazon Web Services, Inc., Beeline, Blippar Group Limited, Furuno Electric Co., Ltd., instinctools GmbH, Intel Corporation, Konecranes, Northrop Grumman Corporation, Orca AI, Qualcomm Technologies, Inc., STRONG ANALYTICS LLC, Tangar Technologies AB, and UAV Navigation S.L..

Market Segmentation & Coverage

This research report categorizes the Computer Vision in Navigation Market to forecast the revenues and analyze trends in each of the following sub-markets:

Component
- Hardware
  - Camera
  - Memory Devices
  - Sensors & Processors

Services
- Consulting Services
- Installation
- Maintenance

Software

Product
- PC-Based Computer Vision System
- Smart Camera-Based Computer Vision System

Application
- Aerial Mapping & Surveying
- Autonomous Vehicles
- Public Transportation Systems
- Robotics
- Smart City Traffic Management

Region
- Americas
  - Argentina
  - Brazil
  - Canada
  - Mexico
  - United States
    - California
    - Florida
    - Illinois
    - New York
    - Ohio
    - Pennsylvania
    - Texas
- Asia-Pacific
  - Australia
  - China
  - India
  - Indonesia
  - Japan
  - Malaysia
  - Philippines
  - Singapore
  - South Korea
  - Taiwan
  - Thailand
  - Vietnam

Europe, Middle East & Africa
- Denmark
- Egypt
- Finland
- France
- Germany
- Israel
- Italy
- Netherlands
- Nigeria
- Norway
- Poland
- Qatar
- Russia
- Saudi Arabia
- South Africa
- Spain
- Sweden
- Switzerland
- Turkey
- United Arab Emirates
- United Kingdom

Product Code: MRR-43470FC60829

1. Preface

1.1. Objectives of the Study
1.2. Market Segmentation & Coverage
1.3. Years Considered for the Study
1.4. Currency & Pricing
1.5. Language
1.6. Stakeholders

2. Research Methodology

2.1. Define: Research Objective
2.2. Determine: Research Design
2.3. Prepare: Research Instrument
2.4. Collect: Data Source
2.5. Analyze: Data Interpretation
2.6. Formulate: Data Verification
2.7. Publish: Research Report
2.8. Repeat: Report Update

3. Executive Summary

4. Market Overview

5. Market Insights

5.1. Market Dynamics
- 5.1.1. Drivers
  - 5.1.1.1. Increasing demand for highly autonomous vehicles and the need for road safety
  - 5.1.1.2. Growing use of drones in commercial delivery and disaster management
  - 5.1.1.3. Supportive government policies in smart infrastructure development for connected and autonomous vehicle
- 5.1.2. Restraints
  - 5.1.2.1. High computational requirements coupled with continuous improvements in algorithms and hardware
- 5.1.3. Opportunities
  - 5.1.3.1. Enhancing capabilities in AI and machine learning, along with improvements in sensor technologies
  - 5.1.3.2. Development of navigation aids for surgical robots and visually impaired individuals
- 5.1.4. Challenges
  - 5.1.4.1. Issues related to data collection, storage, and use, along with the risk of cyber attacks
5.2. Market Segmentation Analysis
- 5.2.1. Component: Burgeoning adoption of the software to analyze and interpret vehicle data
- 5.2.2. Application: Evolving utilization of computer vision in autonomous vehicles, enabling the creation of accurate and high-resolution maps
5.3. Market Disruption Analysis
5.4. Porter's Five Forces Analysis
- 5.4.1. Threat of New Entrants
- 5.4.2. Threat of Substitutes
- 5.4.3. Bargaining Power of Customers
- 5.4.4. Bargaining Power of Suppliers
- 5.4.5. Industry Rivalry
5.5. Value Chain & Critical Path Analysis
5.6. Pricing Analysis
5.7. Technology Analysis
5.8. Patent Analysis
5.9. Trade Analysis
5.10. Regulatory Framework Analysis

6. Computer Vision in Navigation Market, by Component

6.1. Introduction
6.2. Hardware
6.3. Services
6.4. Software

7. Computer Vision in Navigation Market, by Product

7.1. Introduction
7.2. PC-Based Computer Vision System
7.3. Smart Camera-Based Computer Vision System

8. Computer Vision in Navigation Market, by Application

8.1. Introduction
8.2. Aerial Mapping & Surveying
8.3. Autonomous Vehicles
8.4. Public Transportation Systems
8.5. Robotics
8.6. Smart City Traffic Management

9. Americas Computer Vision in Navigation Market

9.1. Introduction
9.2. Argentina
9.3. Brazil
9.4. Canada
9.5. Mexico
9.6. United States

10. Asia-Pacific Computer Vision in Navigation Market

10.1. Introduction
10.2. Australia
10.3. China
10.4. India
10.5. Indonesia
10.6. Japan
10.7. Malaysia
10.8. Philippines
10.9. Singapore
10.10. South Korea
10.11. Taiwan
10.12. Thailand
10.13. Vietnam

11. Europe, Middle East & Africa Computer Vision in Navigation Market

11.1. Introduction
11.2. Denmark
11.3. Egypt
11.4. Finland
11.5. France
11.6. Germany
11.7. Israel
11.8. Italy
11.9. Netherlands
11.10. Nigeria
11.11. Norway
11.12. Poland
11.13. Qatar
11.14. Russia
11.15. Saudi Arabia
11.16. South Africa
11.17. Spain
11.18. Sweden
11.19. Switzerland
11.20. Turkey
11.21. United Arab Emirates
11.22. United Kingdom

12. Competitive Landscape

12.1. Market Share Analysis, 2023
12.2. FPNV Positioning Matrix, 2023
12.3. Competitive Scenario Analysis
- 12.3.1. ABB Expands Autonomous Mobile Robot Capabilities with Sevensense Acquisition, Driving Innovation in AI-Enabled 3D Vision Navigation
- 12.3.2. Introduction of Orca AI's SeaPod with Advanced Computer Vision and AI
12.4. Strategy Analysis & Recommendation

13. Competitive Portfolio

13.1. Key Company Profiles
13.2. Key Product Portfolio