The industry evaluation report offers a snapshot of the technology trends in the AI-based Sensors industry for the forecast period, 2020 – 2027. Projected data on intangible aspects such an import and export status, supply chain management, distribution channel, consumption capability and production capacity are explained through resources including tables, charts, and graphic images. Analysis of both the strengths and weaknesses of the key market players help business owners understand the strategies they should avoid and endorse.
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Key Highlights From The Report
The neural network, in the type segment, is forecasted to grow with a significant CAGR of 37.9% during the forecast period. Consistent development in artificial intelligence is increasing the application of neural networks in sensors. It helps in the assistance of fraud detection in the BFSI and e-commerce sectors.
Artificial intelligence for the analysis of sensors enables predictions and classifications by using sensor signals as compared to other physics-based models. This latest innovation can be witnessed in the application of medical diagnosis and predictive management.
Artificial intelligence, along with machine learning algorithms, is used in different construction workflows such as quality check, scheduling, issue tracking, safety management, resource, and design management. With the infiltration of COVID-19, AI-based sensors demand is growing in these sectors for remote usage.
North America held the largest market share of 31.6% in the year 2019, owing to the rapid technological advancements and increasing government investments into the development of artificial intelligence-based sensors. Moreover, the presence of some of the leading players of the market in the region will also drive the growth of the market in the region.
Key participants include Augury Systems, Glassbeam, Siemens AG, PointGrab, Maana, Tellmeplus, Sentenai, Versos Systems, Tachyus, and United Technology, among others.
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Examine the size of the global AI-based Sensors market based on the parameters of value and volume.
Accurately calculate the market shares, consumption, and other essential aspects of different segments of the global AI-based Sensors market.
Explore the underlying dynamics of the global AI-based Sensors market.
Highlight significant trends of the global AI-based Sensors market based on factors including, production, revenue, and sales.
Extensively profile top players of the global AI-based Sensors market and showing how they compete in the industry.
Study manufacturing processes and the costs, product pricing, and various trends associated with them.
Analyze the performance of different regions and countries in the global AI-based Sensors market.
Forecast the market size and share of all segments and regions in the global landscape.
Type Outlook (Revenue, USD Billion; 2017-2027)
Application Outlook (Revenue, USD Billion; 2017-2027)
Maintenance and Inspection
Technology Outlook (Revenue, USD Billion; 2017-2027)
Natural Language Processing
Table of Content
Chapter 1. Methodology & Sources
1.1. Market Definition
1.2. Research Scope
1.4. Research Sources
1.4.3. Paid Sources
1.5. Market Estimation Technique
Chapter 2. Executive Summary
2.1. Summary Snapshot, 2019-2027
Chapter 3. Key Insights
Chapter 4. AI-based Sensors Market Segmentation & Impact Analysis
4.1. AI-based Sensors Market Material Segmentation Analysis
4.2. Industrial Outlook
4.2.1. Market indicators analysis
4.2.2. Market drivers analysis
18.104.22.168. Increasing incidence of sports and facial fractures
22.214.171.124. Rising demand for minimally invasive surgeries
126.96.36.199. Technological advancement
4.3. Market restraints analysis
188.8.131.52. Lack of reimbursement policies
4.4. Technological Insights
4.5. Regulatory Framework
4.6. Porter’s Five Forces Analysis
4.7. Competitive Metric Space Analysis
4.8. Price trend Analysis
4.9. Covid-19 Impact Analysis