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市场调查报告书
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1559941

影像识别人工智慧相机市场报告：2030 年趋势、预测与竞争分析

Image Recognition AI Camera Market Report: Trends, Forecast and Competitive Analysis to 2030
出版日期: | 出版商: Lucintel | 英文 150 Pages | 商品交期: 3个工作天内

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简介目录

影像识别AI相机趋势与预测

至2030年，全球影像识别AI相机市场预计将达到26亿美元，2024年至2030年的复合年增长率为21.4%。该市场的关键驱动因素是该技术在自动驾驶汽车中的使用不断增加、对基于人工智慧的诊断图像的需求不断增长以及工业 4.0 的日益普及。全球影像识别人工智慧相机市场的未来前景广阔，在扫描和成像、安全和监控、影像搜寻和扩增实境应用方面都存在机会。

Lucintel 预计，由于电脑图形、自动驾驶汽车、医学影像处理和影像编辑等各个领域对这种基于组件的影像处理的需求不断增长，该软体将在预测期内实现最高增长。

由于商业、工业和政府等各个领域的安全和监控系统对基于人工智慧的摄影机的需求不断增加，预计安全和监控仍将是最大的细分市场。

由于该地区製造、医疗保健和零售等各种最终用途行业的主要企业以及影像识别技术的快速采用，预计亚太地区将在预测期内实现最高增长。

影像识别AI相机市场新趋势

随着许多新兴趋势再形成市场，用于影像识别的人工智慧相机市场正在发生变化和发展。本文介绍了其中一些趋势。

  • 改进人工智慧演算法人工智慧演算法的发展使得影像识别的准确性和速度逐年提高。深度学习和神经网路正在实现更先进的识别功能，提高各种应用的效能。
  • 与边缘运算合作：边缘运算与人工智慧摄影机的结合不仅可以减少延迟，还可以实现更好的即时处理。在设备上而不是在云端处理资料还可以提高效率和安全性，使其适合需要即时回应的应用程式。
  • 零售使用案例不断增长零售商越来越多地采用人工智慧摄影机进行库存管理、客户行为分析和个人化行销目的。因此，正在开发更先进的影像识别技术，以适应零售业的特定要求。
  • 自动驾驶汽车市场成长：人工智慧摄影机市场的成长主要由汽车产业推动。这是因为自动驾驶汽车中使用的导航系统依赖先进的影像识别系统，该系统有助于物体检测和安全功能，从而推动了该领域的创新。

这些力量共同推动影像识别技术远远超出先前的想像，扩大其应用范围并解决隐私和资料安全问题。

影像识别AI相机市场的最新趋势

由于技术进步和不断变化的市场需求，近年来影像识别人工智慧相机市场出现了许多重要趋势：

  • 效能改进的深度学习模型近年来，先进的深度学习模型显着提高了影像识别的准确性。变压器和高级卷积类神经网路等新架构描述了更准确、更可靠的影像分析。
  • 与物联网整合：物联网 (IoT) 系统越来越多地整合人工智慧摄影机。此功能可实现连网型设备之间的无缝资料共用和分析，以改善智慧家庭和工业应用。
  • 更好的脸部辨识技术：脸部辨识技术变得更快、更准确。开发的演算法降低了错误率并提高了生物识别安全和认证系统的有效性。
  • 扩展到医疗保健领域：人工智慧相机的其他用途包括测试患者状况并协助医生诊断医疗机构内发现的疾病。这一趋势是由医疗专业人员对复杂影像处理技术的需求所推动的。

新兴市场透过技术创新、使用量增加和隐私道德问题受到市场开拓的影响。

影像识别AI相机市场的策略性成长机会

影像识别人工智慧相机市场在各种应用中呈现多种策略成长机会，包括：

  • 智慧城市：智慧城市：智慧城市基础发展是人工智慧相机成长的关键部分。透过先进的监控和分析，这些可用于改善公共、监控道路交通和设计城市。
  • 零售：在零售业，公司正在使用人工智慧摄影机进行库存管理、了解消费者和个人化购物体验。希望获得相对于竞争对手的优势的公司将这个市场视为不可忽视的潜在扩张市场。
  • 医疗保健：在医疗保健领域，人工智慧摄影机越来越多地应用于病患监测、影像诊断、远端医疗等。此细分市场的扩张是由于患者治疗效果和业务效率的改善。
  • 汽车产业：例如，自动驾驶汽车在道路上变得越来越普遍，导致汽车领域影像识别人工智慧摄影机的部署快速成长。导航安全和驾驶辅助技术需要 ADAS（高级驾驶辅助系统）。

这样的机会展示了影像识别影像识别相机的应用有多么广泛，以及它们如何促进各行业的创新和进步。

影像识别AI相机市场推广因素及挑战

用于影像识别的人工智慧相机的需求变化有多种因素。其中包括技术进步、经济和政治议题：

推动影像识别AI相机市场的因素如下：

1.人工智慧和机器学习技术的不断改进正在推动市场。增强的演算法和处理能力使影像识别更加准确和高效。

2. 对安全和监控的日益关注正在推动对人工智慧摄影机的需求。先进的影像识别功能对于有效的监控和威胁侦测仍然很重要。

3. 智慧型设备的激增及其与物联网的整合正在扩大人工智慧相机的应用范围。这些设备需要改进的功能以及透过进阶影像识别提供更好的使用者体验。

4. 医疗保健、零售和汽车等越来越多的使用案例将为人工智慧相机打开新市场。这导致了透过创新扩大市场。

影像识别AI相机市场挑战如下：

1. 隐私问题：监视和资料收集有重大隐私挑战。因此，我们可以透过透明度和强有力的资料保护措施来解决社会问题。

2. 实施成本高：有些公司可能无力安装先进的人工智慧摄影系统。这表明高昂的初始投资和维护成本可能会阻碍中小企业采用这些技术。

市场动态是由这些驱动因素和挑战决定的，它们影响影像识别人工智慧相机产业的成长机会和策略决策。

影像识别AI相机分部

该研究包括按组件、技术、应用、最终用途行业和地区对全球影像识别人工智慧相机的预测。

各国影像识别AI相机市场前景

由于技术进步和各领域应用的激增，影像识别人工智慧相机市场正在快速成长。介绍一些国家的最新趋势：

  • 美国：美国市场正在对人工智慧驱动的安全和监控系统进行大量投资。亚马逊和谷歌等一些公司正在开发影像识别技术，将其与云端基础的平台整合以进行即时资料处理。
  • 中国：在中国，政府正在大力投资人工智慧技术，以确保公共并实现智慧城市。海康威视和大华是采用尖端人工智慧技术的主要企业，专注于将人工智慧系统与主要用于脸部辨识技术和监控的先进影像识别系统整合。
  • 德国：德国是推动影像识别技术取得重大进展的领先国家之一，特别关注工业自动化和品管。例如，博世和西门子正在将人工智慧相机引入其製造流程，以提高准确性和效率。
  • 印度：印度的影像识别技术正被用于安全和零售目的。新兴企业正在利用人工智慧摄影机的概念来提高客户满意度，同时改进安全措施。
  • 日本：将日本人工智慧影像识别融入机器人和家用电子电器产品是日本的主要关注点。索尼和松下等公司正在开发用于机器人、自动驾驶汽车和智慧家庭设备的先进人工智慧相机，反映出多功能用途的倾向。

常问问题

Q.1影像识别AI相机的市场规模有多大？

答：到2030年，全球影像识别AI相机市场规模预计将达到26亿美元。

Q.2影像识别AI相机市场的成长预测如何？

答：2024年至2030年，全球影像识别AI相机市场预计将以21.4%的复合年增长率成长。

Q.3 影响影像识别人工智慧相机市场成长的关键驱动因素有哪些？

答：该市场的关键驱动因素是该技术在自动驾驶汽车中的使用越来越多、对基于人工智慧的诊断图像的需求不断增长以及工业4.0的日益普及。

Q4.市场的主要细分市场有哪些？

答：影像识别人工智慧相机市场的未来前景广阔，在扫描和成像、安全和监控、影像搜寻和扩增实境应用方面都有机会。

Q5.市场上主要企业有哪些？

答：影像识别AI相机的主要企业有：

  • Apple
  • Canon
  • Hanvon Technology
  • Hewlett Packard Enterprise Development
  • Moleskine
  • NeoLab Convergence
  • Toshiba
  • Wacom
  • XCALLIBRE

Q6.未来最大的细分市场是什么？

答：Lucintel 预计，由于电脑图形、自动驾驶汽车、医学影像处理和影像编辑等各领域对基于组件的影像处理的需求不断增长，Lucintel 预计软体在预测期内将出现最高增长。

Q7. 预计未来五年哪个地区将成为最大的市场？

答：由于主要企业的存在以及影像识别技术在製造、医疗保健和零售等各种最终用途行业的快速采用，亚太地区预计将在预测期内实现最高增长。

Q8. 可以客製化报告吗？

答：是的，Lucintel 列出了 10% 的客製化服务，无需额外费用。

目录

第一章执行摘要

第二章全球影像识别AI相机市场：市场动态

  • 简介、背景、分类
  • 供应链
  • 产业驱动因素与挑战

第三章 2018-2030年市场趋势及预测分析

  • 宏观经济趋势（2018-2023）与预测（2024-2030）
  • 全球影像识别AI相机市场趋势（2018-2023）及预测（2024-2030）
  • 按组件分類的全球影像识别AI 相机市场
    • 硬体
    • 软体
    • 服务
  • 按技术分類的全球影像识别AI 相机市场
    • 条码识别
    • 脸部辨识
    • 物体辨识
    • 模式识别
  • 按应用分類的全球影像识别AI 相机市场
    • 扫描和成像
    • 安全和监视
    • 图片搜寻
    • 扩增实境
    • 其他的
  • 按最终用途产业分類的全球影像识别AI 相机市场
    • BFSI
    • 媒体
    • 娱乐

第四章 2018-2030年区域市场趋势及预测分析

  • 影像识别AI相机市场按地区划分
  • 北美影像识别AI相机市场
  • 欧洲影像识别AI相机市场
  • 亚太影像识别AI相机市场
  • 其他地区影像识别AI相机市场

第五章 竞争分析

  • 产品系列分析
  • 业务整合
  • 波特五力分析

第六章 成长机会与策略分析

  • 成长机会分析
    • 全球影像识别人工智慧相机市场成长机会（按组件）
    • 全球影像识别人工智慧相机市场成长机会（按技术）
    • 全球影像识别人工智慧相机市场成长机会（按应用）
    • 全球影像识别人工智慧相机市场最终用途产业的成长机会
    • 全球影像识别人工智慧相机市场成长机会（按地区）
  • 全球影像识别AI相机市场新趋势
  • 战略分析
    • 新产品开发
    • 全球影像识别AI相机市场产能扩张
    • 全球影像识别AI相机市场併购及合资
    • 认证和许可

第七章主要企业概况

  • Apple
  • Canon
  • Hanvon Technology
  • Hewlett Packard Enterprise Development
  • Moleskine
  • NeoLab Convergence
  • Toshiba
  • Wacom
  • XCALLIBRE
简介目录

Image Recognition AI Camera Trends and Forecast

The future of the global image recognition AI camera market looks promising with opportunities in the scanning and imaging, security and surveillance, image search, and augmented reality applications. The global image recognition AI camera market is expected to reach an estimated $2.6 billion by 2030 with a CAGR of 21.4% from 2024 to 2030. The major drivers for this market are increasing use of this technology in self-driving vehicles, rising demand for AI based diagnostic imaging, and growing popularity towards industry 4.0.

Lucintel forecast that software is expected to witness highest growth over the forecast period due to increasing need for this component-based image processing in a variety of fields, such as computer graphics, autonomous cars, medical imaging, and picture editing.

Security and surveillance will remain the largest segment due to rising need for AI based cameras in security and surveillance systems across a range of sectors, including business, industry, and government.

APAC is expected to witness highest growth over the forecast period due to presence of key players and rapid adoption of image recognition technologies in various end use industries, such as manufacturing, healthcare, and retail of the region.

Emerging Trends in the Image Recognition AI Camera Market

The AI camera marketplace for image recognition is changing and evolving, as there are many up-and-coming trends that are reshaping the market. This article will discuss some of these trends.

  • Improved AI algorithms: Developments in artificial intelligence algorithms have improved image recognition precision and speed over time. Deep learning and neural networks have enabled more advanced recognition abilities which improve performance across various applications.
  • Partnering with Edge Computing: The combination of edge computing and AI cameras has led to reduced latencies as well as better real-time processing. In addition, processing data on the device instead of in the cloud improves efficiency and security, thus making it suitable for applications needing immediate response times.
  • Retail Use Cases Are Expanding: In retail, AI cameras are increasingly being deployed for inventory management, customer behavior analysis, and personalized marketing purposes. Consequently, more sophisticated image recognition technologies tailored to the specific requirements of retail businesses are being developed.
  • Autonomous Vehicle Market Is Growing: The growth of AI camera market is mainly driven by automobile industry. This is because navigation systems used by autonomous vehicles depend on advanced image recognition systems that facilitate object detection alongside safety features; hence driving innovation within this sector.

All of these combined forces are taking image recognition technology far beyond what was thought possible before, expanding applications for it and tackling privacy and data security issues.

Recent Developments in the Image Recognition AI Camera Market

Recently, there have been a number of significant developments in the image recognition AI camera market due to advancements in technology and shifts in market requirements:

  • Deep Learning Models with Enhanced Performance: Recently, advanced deep learning models have significantly increased the accuracy of image recognition. New architectures like Transformers and advanced Convolutional Neural Networks provide more precise and reliable image analysis.
  • Integration with IoT: Internet of Things (IoT) systems are incorporating AI cameras even more. This feature allows for seamless data sharing and analytics among connected devices improving smart homes as well as industrial applications.
  • Better Facial Recognition Technology: Improvement has been witnessed in the speed and precision of facial recognition technology. There is a reduction in mistake rate by developed algorithms which leads to improved effectiveness of biometric security and authentication systems.
  • Expansion into Healthcare: Other uses for AI cameras include examination of patient's conditions or helping doctors diagnose diseases found within healthcare facilities. This trend is fueled by demand for sophisticated imaging technologies that can be used by medical professionals.

The market is being influenced by these developments through innovation, increased usage, and ethical issues of privacy.

Strategic Growth Opportunities for Image Recognition AI Camera Market

The image recognition AI camera market presents several strategic growth opportunities in various applications, amongst which include:

  • Smart Cities: The coming up with of smart city infrastructure is a major area for the growth of AI cameras. These can be used to improve public security, monitoring road traffic and city designing through sophisticated surveillance and analytics.
  • Retail Sector: In retail, companies are using AI cameras for stock management, consumer understandings and personalized shopping experiences. Companies that want to have an upper hand over their competitors regard this as a potentially expanding market that should not be left unattended.
  • Healthcare: Increasingly, healthcare is adopting AI cameras for patient monitoring, diagnostic imaging as well as telemedicine among other uses. The expansion in this area is attributed to likely patient outcomes improvement and more efficient operations.
  • Automotive Industry: For instance, autonomous vehicles are becoming common on roads leading to rapid growth of image recognition AI cameras deployment in the automotive sector. Navigation safety and driver assistance technologies necessitate advanced IR systems.

These opportunities demonstrate how versatile the applications of image recognition AI cameras can be and how they can spur innovation and advancement across diverse industries

Image Recognition AI Camera Market Driver and Challenges

Various factors are responsible for the change in demand of AI cameras used in image recognition. They include technological advancements, economic and political issues:

The factors responsible for driving the image recognition ai camera market include:

1. Ongoing improvements in AI and machine learning technologies are driving the market. Enhanced algorithms and processing capabilities are enabling more accurate and efficient image recognition.

2. Rising concerns about security and surveillance are boosting demand for AI cameras. For effective monitoring and threat detection, advanced image recognition capabilities remain crucial.

3. The proliferation of smart devices coupled with integration into IoT is widening the application of AI cameras. These devices need an improvement in functionality as well as user experience through advanced image recognition.

4. Increasingly, the field has got more use cases which drive new markets for them like healthcare, retailing or automotive among others. This has led to market expansion through innovativeness.

Challenges in the image recognition ai camera market are:

1. Privacy Concerns: There is a significant challenge posed by privacy associated with surveillance and data collection. The public concern, therefore, can be addressed through transparency and strong data protection measures.

2. High Implementation Costs: Some businesses may not be able to afford advanced AI camera systems for their operations. This implies that high costs of initial investments and maintaining them may hinder smaller firms from adopting these technologies.

Market dynamics are shaped by these drivers and challenges, which influence growth opportunities as well as strategic decisions within the image recognition AI camera industry.

List of Image Recognition AI Camera Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. With these strategies image recognition AI camera companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the image recognition AI camera companies profiled in this report include-

  • Apple
  • Canon
  • Hanvon Technology
  • Hewlett Packard Enterprise Development
  • Moleskine
  • Neolab Convergence
  • Toshiba
  • Wacom
  • XCALLIBRE

Image Recognition AI Camera by Segment

The study includes a forecast for the global image recognition AI camera by component, technology, application, end use industry, and region

Image Recognition AI Camera Market by Component [Analysis by Value from 2018 to 2030]:

  • Hardware
  • Software
  • Services

Image Recognition AI Camera Market by Technology [Analysis by Value from 2018 to 2030]:

  • Barcode Recognition
  • Facial Recognition
  • Object Recognition
  • Pattern Recognition

Image Recognition AI Camera Market by Application [Analysis by Value from 2018 to 2030]:

  • Scanning and Imaging
  • Security and Surveillance
  • Image Search
  • Augmented Reality
  • Others

Image Recognition AI Camera Market by End Use Industry [Analysis by Value from 2018 to 2030]:

  • BFSI (Banking, Financial Services and Insurance)
  • Media
  • Entertainment

Image Recognition AI Camera Market by Region [Analysis by Value from 2018 to 2030]:

  • North America
  • Europe
  • Asia Pacific
  • The Rest of the World

Country Wise Outlook for the Image Recognition AI Camera Market

Technological progressions and a surge in their application across different sectors has led to rapid growth of the market for AI cameras that recognize images. These are recent developments in some countries:

  • United States: The U.S. market is absorbing massive investments in AI-driven systems of security and surveillance. Some companies, such as Amazon and Google, are developing image recognition technology by integrating it with cloud-based platforms aimed at real-time data processing.
  • China: In China, the government is investing heavily on AI technology to ensure public safety and implement smart cities. Hikvision and Dahua are some key firms that have adopted cutting-edge AI technologies while focusing on integrating artificial intelligence systems with advanced image recognition ones primarily designed for face recognition technologies and surveillance.
  • Germany: Germany is among the leading nations making significant strides towards advancing image recognition technology with a particular emphasis on industrial automation plus quality control. For instance, Bosch as well as Siemens have deployed artificial intelligence cameras into manufacturing processes which improve accuracy as well as efficiency.
  • India: Image Recognition technologies in India have been adopted for both security and retail purposes. Startups exploit ideas of AI-cameras to boost customer satisfaction when at the same time improving their security measures whereas the administration investigates its use for smart city schemes.
  • Japan: Integrating AI image recognition into robotics and consumer electronics is a major focus for Japan. Advanced AI cameras are being developed by companies such as Sony and Panasonic for use in robotics, autonomous vehicles, and smart home devices, which reflects an inclination toward multifunctional use.

Features of the Global Image Recognition AI Camera Market

Market Size Estimates: Image recognition AI camera market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2018 to 2023) and forecast (2024 to 2030) by various segments and regions.

Segmentation Analysis: Image recognition AI camera market size by various segments, such as by component, technology, application, end use industry, and region in terms of value ($B).

Regional Analysis: Image recognition AI camera market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different components, technologies, applications, end use industries, and regions for the image recognition AI camera market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the image recognition AI camera market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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FAQ

Q.1 What is the image recognition AI camera market size?

Answer: The global image recognition AI camera market is expected to reach an estimated $2.6 billion by 2030.

Q.2 What is the growth forecast for image recognition AI camera market?

Answer: The global image recognition AI camera market is expected to grow with a CAGR of 21.4% from 2024 to 2030.

Q.3 What are the major drivers influencing the growth of the image recognition AI camera market?

Answer: The major drivers for this market are increasing use of this technology in self-driving vehicles, rising demand for AI based diagnostic imaging, and growing popularity towards industry 4.0.

Q4. What are the major segments for image recognition AI camera market?

Answer: The future of the image recognition AI camera market looks promising with opportunities in the scanning and imaging, security and surveillance, image search, and augmented reality applications.

Q5. Who are the key image recognition AI camera market companies?

Answer: Some of the key image recognition AI camera companies are as follows:

  • Apple
  • Canon
  • Hanvon Technology
  • Hewlett Packard Enterprise Development
  • Moleskine
  • NeoLab Convergence
  • Toshiba
  • Wacom
  • XCALLIBRE

Q6. Which image recognition AI camera market segment will be the largest in future?

Answer: Lucintel forecast that software is expected to witness highest growth over the forecast period due to increasing need for this component-based image processing in a variety of fields, such as computer graphics, autonomous cars, medical imaging, and picture editing.

Q7. In image recognition AI camera market, which region is expected to be the largest in next 5 years?

Answer: APAC is expected to witness highest growth over the forecast period due to presence of key players and rapid adoption of image recognition technologies in various end use industries, such as manufacturing, healthcare, and retail of the region.

Q.8 Do we receive customization in this report?

Answer: Yes, Lucintel provides 10% customization without any additional cost.

This report answers following 11 key questions:

  • Q.1. What are some of the most promising, high-growth opportunities for the image recognition AI camera market by component (hardware, software, and services), technology (barcode recognition, facial recognition, object recognition, and pattern recognition), application (scanning and imaging, security and surveillance, image search, augmented reality, and others), end use industry (BFSI, media, and entertainment), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
  • Q.2. Which segments will grow at a faster pace and why?
  • Q.3. Which region will grow at a faster pace and why?
  • Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
  • Q.5. What are the business risks and competitive threats in this market?
  • Q.6. What are the emerging trends in this market and the reasons behind them?
  • Q.7. What are some of the changing demands of customers in the market?
  • Q.8. What are the new developments in the market? Which companies are leading these developments?
  • Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
  • Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
  • Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?
  • Market Report

Table of Contents

1. Executive Summary

2. Global Image Recognition AI Camera Market: Market Dynamics

  • 2.1: Introduction, Background, and Classifications
  • 2.2: Supply Chain
  • 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2018 to 2030

  • 3.1. Macroeconomic Trends (2018-2023) and Forecast (2024-2030)
  • 3.2. Global Image Recognition AI Camera Market Trends (2018-2023) and Forecast (2024-2030)
  • 3.3: Global Image Recognition AI Camera Market by Component
    • 3.3.1: Hardware
    • 3.3.2: Software
    • 3.3.3: Services
  • 3.4: Global Image Recognition AI Camera Market by Technology
    • 3.4.1: Barcode Recognition
    • 3.4.2: Facial Recognition
    • 3.4.3: Object Recognition
    • 3.4.4: Pattern Recognition
  • 3.5: Global Image Recognition AI Camera Market by Application
    • 3.5.1: Scanning and Imaging
    • 3.5.2: Security and Surveillance
    • 3.5.3: Image Search
    • 3.5.4: Augmented Reality
    • 3.5.5: Others
  • 3.6: Global Image Recognition AI Camera Market by End Use Industry
    • 3.6.1: BFSI
    • 3.6.2: Media
    • 3.6.3: Entertainment

4. Market Trends and Forecast Analysis by Region from 2018 to 2030

  • 4.1: Global Image Recognition AI Camera Market by Region
  • 4.2: North American Image Recognition AI Camera Market
    • 4.2.1: North American Image Recognition AI Camera Market by Component: Hardware, Software, and Services
    • 4.2.2: North American Image Recognition AI Camera Market by Application: Scanning and Imaging, Security and Surveillance, Image Search, Augmented Reality, and Others
  • 4.3: European Image Recognition AI Camera Market
    • 4.3.1: European Image Recognition AI Camera Market by Component: Hardware, Software, and Services
    • 4.3.2: European Image Recognition AI Camera Market by Application: Scanning and Imaging, Security and Surveillance, Image Search, Augmented Reality, and Others
  • 4.4: APAC Image Recognition AI Camera Market
    • 4.4.1: APAC Image Recognition AI Camera Market by Component: Hardware, Software, and Services
    • 4.4.2: APAC Image Recognition AI Camera Market by Application: Scanning and Imaging, Security and Surveillance, Image Search, Augmented Reality, and Others
  • 4.5: ROW Image Recognition AI Camera Market
    • 4.5.1: ROW Image Recognition AI Camera Market by Component: Hardware, Software, and Services
    • 4.5.2: ROW Image Recognition AI Camera Market by Application: Scanning and Imaging, Security and Surveillance, Image Search, Augmented Reality, and Others

5. Competitor Analysis

  • 5.1: Product Portfolio Analysis
  • 5.2: Operational Integration
  • 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

  • 6.1: Growth Opportunity Analysis
    • 6.1.1: Growth Opportunities for the Global Image Recognition AI Camera Market by Component
    • 6.1.2: Growth Opportunities for the Global Image Recognition AI Camera Market by Technology
    • 6.1.3: Growth Opportunities for the Global Image Recognition AI Camera Market by Application
    • 6.1.4: Growth Opportunities for the Global Image Recognition AI Camera Market by End Use Industry
    • 6.1.5: Growth Opportunities for the Global Image Recognition AI Camera Market by Region
  • 6.2: Emerging Trends in the Global Image Recognition AI Camera Market
  • 6.3: Strategic Analysis
    • 6.3.1: New Product Development
    • 6.3.2: Capacity Expansion of the Global Image Recognition AI Camera Market
    • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global Image Recognition AI Camera Market
    • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

  • 7.1: Apple
  • 7.2: Canon
  • 7.3: Hanvon Technology
  • 7.4: Hewlett Packard Enterprise Development
  • 7.5: Moleskine
  • 7.6: NeoLab Convergence
  • 7.7: Toshiba
  • 7.8: Wacom
  • 7.9: XCALLIBRE