BANGALORE, India, Nov. 23, 2021 /PRNewswire/ -- Edge AI Hardware Market By Component (Processor, Memory, Sensor, and Others), Device Type (Smartphones, Cameras, Robots, Wearables, Smart Speaker, and Others), Process (Training and Inference), and End User (Consumer Electronics, Smart Home, Automotive, Government, Aerospace & Defense, Healthcare, Industrial, Construction, and Others): Global Opportunity Analysis and Industry Forecast, 2021-2030. It is published in Valuates Reports under the Computer Hardware Category.
The global Edge AI Hardware Market size was valued at USD 6.88 billion in 2020, and is projected to reach USD 38.87 billion by 2030, registering a CAGR of 18.8% from 2021 to 2030.
Major Factors Driving The Growth Of The Edge Ai Hardware Market Are
Increased demand for low latency and real-time processing on edge devices, the emergence of AI coprocessors for edge computing, reduction in data storage and operations costs, increase in enterprise workloads on the cloud, and rapid growth in the number of intelligent applications are all factors driving the growth of the edge AI hardware market.
Factors such as the development in IoT applications by various end-user sectors such as automotive and consumer electronics, among others, are expected to propel the worldwide edge AI hardware market forward.
Furthermore, the edge AI hardware market is likely to benefit from an increase in demand and adoption of artificial intelligence products and services.
TRENDS INFLUENCING THE GROWTH OF THE EDGE AI HARDWARE MARKET
The surge in investments in AI startups and the desire for smart homes and smart cities are two major factors influencing the growth of the edge AI hardware market. Furthermore, the rise of the edge AI hardware market is fueled by an increase in the demand for automation and security in companies. However, SMEs' lack of awareness limits market expansion. On the contrary, the market is likely to benefit from the increased usage of robots technology in emerging countries.
Growth in demand for low latency and real-time processing on edge devices is expected to drive the growth of the edge AI hardware market. Machine learning methods in edge AI employ device-generated data and process it on the device. This decreases latency and allows for automatic decision-making in real-time. Edge AI enables real-time processes such as data production, learning, and inference, which will assist applications that require real-time data processing. Autonomous vehicles (AVs) have a very short time between identifying a potential accident and making steering and braking adjustments. A vast amount of data collected by an IoT device is sent to the cloud, where machine learning (ML) models are run and the processed data is sent back to the device, causing a delay in response.
Dedicated AI processors for on-device image analytics are expected to provide lucrative growth opportunities for the edge AI hardware market. Drones, wearable gadgets, robotics, surveillance cameras, and autonomous vehicles all use AI mobile CPUs for computational imaging. AI-based vision processing units (VPU) can assist drones in making better decisions and reducing the risk of accidents, which will contribute to the growing demand for drones for industrial and personal use.
However, the worldwide edge AI hardware market is constrained by power consumption and size constraints.
In 2020, the United States was the largest shareholder in the North American edge AI hardware market, with a 55 percent share. However, due to significant investment in the automotive sector, the Edge AI Hardware market in Asia-Pacific is predicted to develop at the fastest rate over the forecast period. Furthermore, edge AI hardware devices have a high penetration rate in the healthcare, industrial, and consumer electronics sectors in economically developed countries, which is expected to contribute significantly to market growth.
Based on end-user, the consumer electronics segment is expected to be the most lucrative segment. This is because consumer spending and demand for consumer gadgets are increasing. Smartphones, smart wearables, and other electronic devices are in high demand. Furthermore, the emergence of new edge AI use cases could lead to a significant increase in consumer electronics in the edge AI hardware industry.
Based on components, the processor segment is expected to be the most lucrative.
Based on the processor, the Inference segment will dominate the market with the highest CAGR of 19.5% during 2021 - 2030
Based on device type, the smartphone segment is expected to dominate the market during the forecast period.
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