The global sales of edge AI is estimated to be worth USD 8,901.9 million in 2024 and anticipated to reach a value of USD 71,131.3 million by 2034. Sales are projected to rise at a CAGR of 23.1% over the forecast period between 2024 and 2034. The revenue generated by emergency lighting in 2023 was USD 3,149.1 million. The application is anticipated to exhibit a Y-o-Y growth of 22.7% in 2024.
Edge AI means direct deployment of AI algorithms directly on the edge, such as smartphones, sensors, cameras, IoT devices, or any other embedded systems instead of relying on centralized cloud servers.
Thus, by processing data locally, Edge AI minimizes constant data transmission to and from the cloud, which allows faster decision-making, improved data privacy, and lower bandwidth usage. It uses compact AI models that are optimized for edge devices and usually use technologies such as machine learning, computer vision, & natural language processing.
The global Edge AI Market is experiencing substantial growth, driven by the increasing need for real-time data processing and the widespread adoption of Internet of Things (IoT) devices across various industries. Edge AI refers to the deployment of artificial intelligence algorithms directly on edge devices, enabling data processing closer to the source and reducing latency.
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Key Drivers:
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Proliferation of IoT Devices: The rapid expansion of IoT devices necessitates efficient data processing at the edge to manage the vast amounts of data generated.
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Advancements in AI Hardware: Innovations in AI-specific hardware, such as specialized chips and processors, enhance the performance and efficiency of edge AI applications.
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Demand for Real-Time Processing: Industries require immediate data analysis and decision-making capabilities, driving the adoption of edge AI solutions.
Growth Opportunities:
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Emerging Economies: Developing regions present significant opportunities due to increasing digitalization and supportive government initiatives.
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Integration with 5G Networks: The rollout of 5G technology enhances edge AI capabilities by providing faster and more reliable connectivity.
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Focus on Data Privacy: Processing data locally at the edge addresses privacy concerns and compliance with data protection regulations.
Key Applications:
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Manufacturing: Predictive maintenance and quality control through real-time data analysis.
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Healthcare: Patient monitoring and diagnostics with immediate data processing.
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Automotive: Enhancing autonomous driving systems with low-latency data processing.
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Retail: Personalized customer experiences and inventory management through real-time analytics.
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Key Players of Edge AI Industry
- Microsoft Corporation
- Google, LLC
- IBM Corporation
- Nvidia Corporation
- Intel Corporation
- Qualcomm
- Samsung Electronics
- Hewlett Packard Enterprise
- NXP Semiconductors
- EdgeQ
- Aaeon Technology
- Samsara
- Kneron
- Adlink Technology
- Greenwave Systems
Key Segments of Edge AI Industry
By Component:
In terms of component, the industry is divided into hardware, software, and services.
By Application:
In terms of application, it is divided video surveillance, remote monitoring, predictive maintenance, and others.
By Industry:
The industry is classified as IT & telecommunications, consumer electronics, healthcare, manufacturing, government, energy & utilities, retail & E-commerce, automotive, and others.
By Region:
Key countries of North America, Latin America, East Asia, South Asia & Pacific, Western Europe, Eastern Europe, and Middle East & Africa (MEA) have been covered in the report.
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