Global Realtime Edge AI based Camera Market 2024 by Manufacturers, Regions, Type and Application, Forecast to 2030

Global Realtime Edge AI based Camera Market 2024 by Manufacturers, Regions, Type and Application, Forecast to 2030

A real-time edge AI-based camera refers to a smart camera system equipped with embedded artificial intelligence (AI) capabilities that enable it to perform advanced image processing and analysis tasks directly at the edge of the network, without the need for cloud connectivity or external processing resources. These cameras are designed to capture and process video data in real-time, utilizing onboard AI algorithms to detect, recognize, classify, and track objects or events of interest within the camera's field of view. Real-time edge AI-based cameras typically feature powerful processors, dedicated AI accelerators, and machine learning models optimized for edge computing, allowing them to perform complex inference tasks such as object detection, facial recognition, gesture recognition, and activity monitoring with low latency and high accuracy. By processing data locally at the edge, these cameras can reduce bandwidth usage, minimize latency, and ensure privacy and security by keeping sensitive information within the local network. Real-time edge AI-based cameras find applications in various industries, including retail, manufacturing, transportation, security, and healthcare, where real-time insights and actionable intelligence are critical for decision-making, automation, and optimization of operations. Overall, real-time edge AI-based cameras represent a powerful convergence of AI and edge computing technologies, enabling intelligent video analytics and smart surveillance solutions that are capable of processing and interpreting visual data in real-time at the edge of the network.

According to our (Global Info Research) latest study, the global Realtime Edge AI based Camera market size was valued at US$ million in 2023 and is forecast to a readjusted size of USD million by 2030 with a CAGR of %during review period.

The current market for real-time edge AI-based cameras is experiencing rapid growth, driven by the increasing demand for intelligent video analytics and surveillance solutions across various industries. With the proliferation of IoT devices, smart sensors, and connected cameras, there is a growing need for edge-based AI solutions that can analyze and interpret visual data in real-time to enable proactive decision-making and automation of processes. Real-time edge AI-based cameras offer significant advantages over traditional surveillance systems by performing advanced image processing and analysis directly at the edge of the network, allowing for faster response times, reduced bandwidth requirements, and improved privacy and security. Moreover, advancements in AI algorithms, edge computing technologies, and hardware accelerators are driving innovation in real-time edge AI-based cameras, enabling them to perform increasingly complex tasks such as object detection, facial recognition, behavior analysis, and anomaly detection with higher accuracy and efficiency. Looking ahead, the future development trends of the real-time edge AI-based camera market are expected to focus on several key areas. These include the integration of multi-modal sensing capabilities such as thermal imaging, depth sensing, and LiDAR to enhance situational awareness and enable more accurate and robust object detection and tracking in challenging environments. Additionally, there is a growing emphasis on edge-to-cloud integration, enabling seamless data sharing and collaboration between edge devices and cloud-based AI platforms for more comprehensive and scalable AI solutions. Furthermore, advancements in AI hardware such as neuromorphic processors and edge AI chips are expected to enable even more efficient and powerful AI inference at the edge, paving the way for new applications and use cases in smart cities, industrial automation, autonomous vehicles, and beyond. Overall, the real-time edge AI-based camera market is poised for continued growth and innovation as organizations seek to leverage AI and edge computing technologies to unlock new levels of intelligence and efficiency in visual data analysis and surveillance applications.

This report is a detailed and comprehensive analysis for global Realtime Edge AI based Camera market. Both quantitative and qualitative analyses are presented by manufacturers, by region & country, by Type and by Application. As the market is constantly changing, this report explores the competition, supply and demand trends, as well as key factors that contribute to its changing demands across many markets. Company profiles and product examples of selected competitors, along with market share estimates of some of the selected leaders for the year 2024, are provided.

Key Features:

Global Realtime Edge AI based Camera market size and forecasts, in consumption value ($ Million), sales quantity (K Units), and average selling prices (US$/Unit), 2019-2030

Global Realtime Edge AI based Camera market size and forecasts by region and country, in consumption value ($ Million), sales quantity (K Units), and average selling prices (US$/Unit), 2019-2030

Global Realtime Edge AI based Camera market size and forecasts, by Type and by Application, in consumption value ($ Million), sales quantity (K Units), and average selling prices (US$/Unit), 2019-2030

Global Realtime Edge AI based Camera market shares of main players, shipments in revenue ($ Million), sales quantity (K Units), and ASP (US$/Unit), 2019-2024

The Primary Objectives in This Report Are:

To determine the size of the total market opportunity of global and key countries

To assess the growth potential for Realtime Edge AI based Camera

To forecast future growth in each product and end-use market

To assess competitive factors affecting the marketplace

This report profiles key players in the global Realtime Edge AI based Camera market based on the following parameters - company overview, sales quantity, revenue, price, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include Hailo, Avinton, i-PRO, Ambicam, Adiance Solutions, LUIS Technology, Teksun, ACETECH, Videology, IDIS, etc.

This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.

Market Segmentation

Realtime Edge AI based Camera market is split by Type and by Application. For the period 2019-2030, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of volume and value. This analysis can help you expand your business by targeting qualified niche markets.

Market segment by Type
Single-Camera Edge System
Multi-Camera Edge System

Market segment by Application
Bank
Business
Educational Institution
Medical Institution
Others

Major players covered
Hailo
Avinton
i-PRO
Ambicam
Adiance Solutions
LUIS Technology
Teksun
ACETECH
Videology
IDIS
VMukti
Ability
3DiVi
Detect
IDS
Hanwha Vision

Market segment by region, regional analysis covers

North America (United States, Canada, and Mexico)

Europe (Germany, France, United Kingdom, Russia, Italy, and Rest of Europe)

Asia-Pacific (China, Japan, Korea, India, Southeast Asia, and Australia)

South America (Brazil, Argentina, Colombia, and Rest of South America)

Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa, and Rest of Middle East & Africa)

The content of the study subjects, includes a total of 15 chapters:

Chapter 1, to describe Realtime Edge AI based Camera product scope, market overview, market estimation caveats and base year.

Chapter 2, to profile the top manufacturers of Realtime Edge AI based Camera, with price, sales quantity, revenue, and global market share of Realtime Edge AI based Camera from 2019 to 2024.

Chapter 3, the Realtime Edge AI based Camera competitive situation, sales quantity, revenue, and global market share of top manufacturers are analyzed emphatically by landscape contrast.

Chapter 4, the Realtime Edge AI based Camera breakdown data are shown at the regional level, to show the sales quantity, consumption value, and growth by regions, from 2019 to 2030.

Chapter 5 and 6, to segment the sales by Type and by Application, with sales market share and growth rate by Type, by Application, from 2019 to 2030.

Chapter 7, 8, 9, 10 and 11, to break the sales data at the country level, with sales quantity, consumption value, and market share for key countries in the world, from 2019 to 2024.and Realtime Edge AI based Camera market forecast, by regions, by Type, and by Application, with sales and revenue, from 2025 to 2030.

Chapter 12, market dynamics, drivers, restraints, trends, and Porters Five Forces analysis.

Chapter 13, the key raw materials and key suppliers, and industry chain of Realtime Edge AI based Camera.

Chapter 14 and 15, to describe Realtime Edge AI based Camera sales channel, distributors, customers, research findings and conclusion.