The Asia Pacific AIoT Platforms Market should witness market growth of 36.5% CAGR during the forecast period (2023-2029).
Increasing IoT device adoption solutions that may assist organizations in making sense of the vast volumes of data generated by these devices are becoming increasingly necessary as IoT devices become more widely used across industries. By utilizing AI algorithms to evaluate data and derive insights, AIoT solutions offer a complete answer to this issue. In addition, predictive maintenance is becoming more popular. Businesses aiming to optimize their operations and cut expenses are becoming increasingly dependent on predictive maintenance.
Businesses can use AIoT systems to analyze data from IoT devices to forecast when maintenance is necessary. This enables them to proactively fix issues before they become serious ones. Machine learning (ML) tasks are difficult, and as the demand for ML applications has increased, so needs ready-made ML techniques that don't require much technical knowledge. This results in the gradual automation of ML, also known as Automated Machine Learning (AutoML), now a common service.
The hardware options for industrial AIoT have improved due to the rapid advancements in embedded hardware AI chips. The key drivers of the market's expansion are the need to effectively analyze enormous amounts of real-time data produced by IoT devices, the rising need for performance management appliances, and the requirement to lower downtime and maintenance expenses.
The medical device industry in the Asia Pacific region is well established and includes everything from glucose monitors for mass consumption to top-of-the-line diagnostic imaging equipment. Among wearable technology, there is a high demand for devices such as heart rate monitors and fitness trackers. Additionally, the Asia-Pacific region has seen a sharp growth in investment in wearable technology over the years. By providing its population with access to digital technologies, the Indian government is also reshaping its policies to reshape the country. As more people invest in wearable skin adhesives to monitor their health due to the government enabling them to go digital, the market for these products will develop.
The China market dominated the Asia Pacific AIoT Platforms Market by Country 2022, and would continue to be a dominant market till 2029; thereby, achieving a market value of $2,460.1 million by 2029. The Japan market is estimated to grow a CAGR of 35.6% during (2023-2029). Additionally, The India market would display a CAGR of 37.3% during (2023-2029).
Based on Component, the market is segmented into Solution (Device Management, Connectivity Management, and Application Management) and Services. Based on Vertical, the market is segmented into BFSI, Manufacturing, Retail, Healthcare, Energy & Utilities, Transportation & Logistics and Others. Based on countries, the market is segmented into China, Japan, India, South Korea, Singapore, Malaysia, and Rest of Asia Pacific.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include IBM Corporation, Microsoft Corporation, Intel Corporation, Oracle Corporation, Hewlett-Packard enterprise Company, Cisco Systems, Inc., Google LLC (Alphabet Inc.), Amazon Web Services, Inc. (Amazon.com, Inc.), NXP Semiconductors N.V. and Sharp Corporation (Hon Hai Precision Industry Co., Ltd.).
Increasing IoT device adoption solutions that may assist organizations in making sense of the vast volumes of data generated by these devices are becoming increasingly necessary as IoT devices become more widely used across industries. By utilizing AI algorithms to evaluate data and derive insights, AIoT solutions offer a complete answer to this issue. In addition, predictive maintenance is becoming more popular. Businesses aiming to optimize their operations and cut expenses are becoming increasingly dependent on predictive maintenance.
Businesses can use AIoT systems to analyze data from IoT devices to forecast when maintenance is necessary. This enables them to proactively fix issues before they become serious ones. Machine learning (ML) tasks are difficult, and as the demand for ML applications has increased, so needs ready-made ML techniques that don't require much technical knowledge. This results in the gradual automation of ML, also known as Automated Machine Learning (AutoML), now a common service.
The hardware options for industrial AIoT have improved due to the rapid advancements in embedded hardware AI chips. The key drivers of the market's expansion are the need to effectively analyze enormous amounts of real-time data produced by IoT devices, the rising need for performance management appliances, and the requirement to lower downtime and maintenance expenses.
The medical device industry in the Asia Pacific region is well established and includes everything from glucose monitors for mass consumption to top-of-the-line diagnostic imaging equipment. Among wearable technology, there is a high demand for devices such as heart rate monitors and fitness trackers. Additionally, the Asia-Pacific region has seen a sharp growth in investment in wearable technology over the years. By providing its population with access to digital technologies, the Indian government is also reshaping its policies to reshape the country. As more people invest in wearable skin adhesives to monitor their health due to the government enabling them to go digital, the market for these products will develop.
The China market dominated the Asia Pacific AIoT Platforms Market by Country 2022, and would continue to be a dominant market till 2029; thereby, achieving a market value of $2,460.1 million by 2029. The Japan market is estimated to grow a CAGR of 35.6% during (2023-2029). Additionally, The India market would display a CAGR of 37.3% during (2023-2029).
Based on Component, the market is segmented into Solution (Device Management, Connectivity Management, and Application Management) and Services. Based on Vertical, the market is segmented into BFSI, Manufacturing, Retail, Healthcare, Energy & Utilities, Transportation & Logistics and Others. Based on countries, the market is segmented into China, Japan, India, South Korea, Singapore, Malaysia, and Rest of Asia Pacific.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include IBM Corporation, Microsoft Corporation, Intel Corporation, Oracle Corporation, Hewlett-Packard enterprise Company, Cisco Systems, Inc., Google LLC (Alphabet Inc.), Amazon Web Services, Inc. (Amazon.com, Inc.), NXP Semiconductors N.V. and Sharp Corporation (Hon Hai Precision Industry Co., Ltd.).
Scope of the Study
By Component
- Solution
- Device Management
- Connectivity Management
- Application Management
- Services
By Vertical
- BFSI
- Manufacturing
- Retail
- Healthcare
- Energy & Utilities
- Transportation & Logistics
- Others
By Country
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
Key Market Players
List of Companies Profiled in the Report:
- IBM Corporation
- Microsoft Corporation
- Intel Corporation
- Oracle Corporation
- Hewlett-Packard enterprise Company
- Cisco Systems, Inc.
- Google LLC (Alphabet Inc.)
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- NXP Semiconductors N.V.
- Sharp Corporation (Hon Hai Precision Industry Co., Ltd.)
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- Exhaustive coverage
- The highest number of Market tables and figures
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Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market Overview
Chapter 3. Competition Analysis - Global
Chapter 4. Asia Pacific AIoT Platforms Market by Component
Chapter 5. Asia Pacific AIoT Platforms Market by Vertical
Chapter 6. Asia Pacific AIoT Platforms Market by Country
Chapter 7. Company Profiles
Companies Mentioned
- IBM Corporation
- Microsoft Corporation
- Intel Corporation
- Oracle Corporation
- Hewlett-Packard enterprise Company
- Cisco Systems, Inc.
- Google LLC (Alphabet Inc.)
- Amazon Web Services, Inc. (Amazon.com, Inc.)
- NXP Semiconductors N.V.
- Sharp Corporation (Hon Hai Precision Industry Co., Ltd.)
Methodology
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