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Edge-based AI Market Share, Size, Trends, Industry Analysis Report, By Application (Autonomous Vehicles,Access Management,Video Surveillance,Others), By Type (Platform and Software ools,Edge AI Services) and Forecast 2024 - 2031
Edge-based AI Introduction
The Global Market Overview of "Edge-based AI Market" offers a unique insight into key market trends shaping the industry world-wide and in the largest markets. Written by some of our most experienced analysts, the Global Industrial Reports are designed to provide key industry performance trends, demand drivers, trade, leading companies and future trends. The Edge-based AI market is expected to grow annually by 11% (CAGR 2024 - 2031).
Edge-based AI refers to artificial intelligence algorithms and models that are deployed directly on edge devices, such as smartphones, IoT devices, and edge servers, allowing them to process data locally without needing to send it to the cloud.
The primary purpose of Edge-based AI is to enable real-time decision-making, reduce latency, save bandwidth, and enhance privacy and security by keeping sensitive data on the device itself. By performing computations on the edge device, rather than in the cloud, Edge-based AI can provide faster and more efficient processing of data, making it ideal for applications that require rapid response times.
Advantages of Edge-based AI include improved performance, reduced network congestion, increased reliability, enhanced data privacy, and cost savings. These benefits make Edge-based AI a key technology for industries such as healthcare, manufacturing, transportation, and retail. The increasing adoption of Edge-based AI is expected to drive the growth of the Edge-based AI market in the coming years.
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Market Trends in the Edge-based AI Market
- Integration of 5G technology: With the rollout of 5G networks, Edge-based AI applications can access low-latency, high-speed connectivity, enabling real-time data processing.
- Edge computing devices with AI capabilities: Edge devices are becoming increasingly intelligent, incorporating machine learning algorithms for more advanced processing at the edge.
- Customized Edge-based AI solutions: Companies are developing tailored Edge-based AI solutions to meet specific business needs, leading to increased adoption in various industries.
- Growth in IoT devices: The proliferation of Internet of Things (IoT) devices is driving the demand for Edge-based AI solutions to process the vast amount of data generated by these devices.
- Enhanced privacy and security measures: As data processing moves closer to the edge, there is a focus on implementing robust privacy and security measures to protect sensitive information.
Overall, these trends are propelling the Edge-based AI market forward, with a projected growth rate of % between 2021-2026, according to Market Research Future.
Market Segmentation
The Edge-based AI Market Analysis by types is segmented into:
- Platform and Software ools
- Edge AI Services
There are various types of edge-based AI tools and services that are driving the demand in the market. Edge AI platforms and software tools offer developers the capability to deploy AI models directly on edge devices, enabling real-time data processing. Edge AI services provide pre-built AI functionalities that can be easily integrated into edge devices. These tools and services allow for increased efficiency, reduced latency, improved privacy, and enhanced security in AI applications, making them increasingly popular and in demand in various industries.
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The Edge-based AI Market Industry Research by Application is segmented into:
- Autonomous Vehicles
- Access Management
- Video Surveillance
- Others
Edge-based AI is applied in autonomous vehicles for real-time decision making, access management for enhanced security, video surveillance for threat detection, and various other applications. In these applications, Edge-based AI processes data locally on the device, reducing latency and improving efficiency. The fastest growing application segment in terms of revenue is autonomous vehicles, with the integration of Edge-based AI enabling these vehicles to make split-second decisions based on real-time data gathered from sensors and cameras. This results in safer and more efficient transportation systems.
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Geographical Spread and Market Dynamics of the Edge-based AI Market
North America:
- United States
- Canada
Europe:
- Germany
- France
- U.K.
- Italy
- Russia
Asia-Pacific:
- China
- Japan
- South Korea
- India
- Australia
- China Taiwan
- Indonesia
- Thailand
- Malaysia
Latin America:
- Mexico
- Brazil
- Argentina Korea
- Colombia
Middle East & Africa:
- Turkey
- Saudi
- Arabia
- UAE
- Korea
The Edge-based AI market in North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa is witnessing significant growth due to increasing adoption of IoT devices, rising demand for real-time data processing, and the development of advanced AI algorithms. Key players such as IBM, Microsoft, Intel, Google, TIBCO, Cloudera, Nutanix, Foghorn Systems, , Anagog, Tact.ai, Bragi, XNOR.AI, Octonion, Veea Inc, and Imagimob are driving market growth through strategic partnerships, product innovation, and expansion into new regions. Factors such as increasing investments in AI technology, growing demand for edge computing solutions, and the proliferation of 5G networks are driving market opportunities in these regions.
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Edge-based AI Market Growth Prospects and Market Forecast
The expected CAGR for the Edge-based AI Market during the forecasted period is projected to be around 25%. The growth of this market is driven by the increasing demand for real-time data processing, the rise in the number of AI applications for IoT devices, and the need for low-latency AI algorithms at the network edge.
Innovative growth drivers for the Edge-based AI Market include the development of edge computing platforms that can support AI workloads, the integration of AI chips into edge devices, and the adoption of machine learning models optimized for edge deployment. Moreover, the emergence of 5G technology is expected to further fuel the growth of the market by enabling faster data transmission and lower latency.
To increase growth prospects, companies can focus on deploying AI models closer to the edge devices, leveraging cloud-edge hybrid architectures for AI processing, and investing in edge AI security solutions to protect sensitive data. Additionally, trends such as federated learning, autonomous edge computing, and edge-native AI algorithms can help in accelerating the adoption of Edge-based AI solutions and drive market growth.
Edge-based AI Market: Competitive Intelligence
- IBM
- Microsoft
- Intel
- TIBCO
- Cloudera
- Nutanix
- Foghorn Systems
- SWIM.AI
- Anagog
- Tact.ai
- Bragi
- XNOR.AI
- Octonion
- Veea Inc
- Imagimob
1. IBM: IBM has a strong market presence in AI with innovative solutions like Watson AI. The company has a history of successful acquisitions to expand its AI capabilities. IBM's revenue for 2020 was $ billion.
2. Microsoft: Microsoft is a key player in AI with products like Azure Machine Learning and cognitive services. The company focuses on AI research and development to stay ahead in the market. Microsoft's revenue for 2020 was $143 billion.
3. Intel: Intel is known for its AI hardware solutions like CPUs and GPUs, driving innovation in AI technology. The company collaborates with AI startups to stay competitive in the market. Intel's revenue for 2020 was $77.87 billion.
4. Google: Google is a frontrunner in AI with platforms like TensorFlow and Google Cloud AI. The company invests heavily in AI research and development for cutting-edge solutions. Google's revenue for 2020 was $182.5 billion.
5. TIBCO: TIBCO offers AI solutions for businesses through its analytics and data visualization tools. The company focuses on AI-driven insights to help organizations make informed decisions. TIBCO's revenue for 2020 was $1.14 billion.
6. Cloudera: Cloudera specializes in AI and machine learning technologies for data analytics and management. The company has a strong foothold in the market for big data solutions. Cloudera's revenue for 2020 was $794.7 million.
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