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Last Updated: Apr 25, 2025 | Study Period: 2024-2030
In order to achieve the best results in demanding applications like engine piston bowl, weld seam, glue bead, and medical packaging inspection, you should use a vision accelerator that is small, fanless, and simple to use. This will increase data processing power in real-time, reduce cycle times, and boost overall inspection performance.
An emerging answer to the rising processing needs in sophisticated quality control applications based on 3D scanning and inspection is the use of vision accelerators. When the built-in processing from smart sensors is unable to keep up, the engineer now has a new method to get improved performance, with little to no work.
A smart vision accelerator can handle continuous 3D data flows over Ethernet with dedicated, multi-core data processing.
On the other hand, the requirements for managing a constant Gigabit data stream from a single or several sensor connections may compromise the functionality of the primary inspection application operating on an industrial PC by using up too much CPU or memory resources.
Global smart vision accelerator market accounted for $XX Billion in 2022 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2024 to 2030.
GoMax, for example, is a smart visual accelerator that uses only 15W of power, has DIN rail mounting, and offers over 1 TOPS (1 Trillion Tera Operations Per Second) of computing capability.
Without the hassle of creating an application that works across several industrial PCs or the necessity for multiple keyboard/monitor hookups, one or more GoMax units can easily be used to build a solution to demanding inspection applications.
The GoMax smart vision accelerator is built on a distributed, peer-to-peer networking approach that divides the data processing effort between a dedicated multi-GPU processor and a Gocator sensor (see NVIDIA Jetson TX2).
The smart sensor enters an accelerated mode when the vision accelerator connects to it, sending pre-processed, semi-compressed 3D scan data over Gigabit Ethernet for ultimate processing.
By using many GPU cores for the labor-intensive 3D point cloud building and measurement, this reduces network traffic and promotes faster cycles.
Sl no | Topic |
1 | Market Segmentation |
2 | Scope of the report |
3 | Abbreviations |
4 | Research Methodology |
5 | Executive Summary |
6 | Introduction |
7 | Insights from Industry stakeholders |
8 | Cost breakdown of Product by sub-components and average profit margin |
9 | Disruptive innovation in the Industry |
10 | Technology trends in the Industry |
11 | Consumer trends in the industry |
12 | Recent Production Milestones |
13 | Component Manufacturing in US, EU and China |
14 | COVID-19 impact on overall market |
15 | COVID-19 impact on Production of components |
16 | COVID-19 impact on Point of sale |
17 | Market Segmentation, Dynamics and Forecast by Geography, 2024-2030 |
18 | Market Segmentation, Dynamics and Forecast by Product Type, 2024-2030 |
19 | Market Segmentation, Dynamics and Forecast by Application, 2024-2030 |
20 | Market Segmentation, Dynamics and Forecast by End use, 2024-2030 |
21 | Product installation rate by OEM, 2023 |
22 | Incline/Decline in Average B-2-B selling price in past 5 years |
23 | Competition from substitute products |
24 | Gross margin and average profitability of suppliers |
25 | New product development in past 12 months |
26 | M&A in past 12 months |
27 | Growth strategy of leading players |
28 | Market share of vendors, 2023 |
29 | Company Profiles |
30 | Unmet needs and opportunity for new suppliers |
31 | Conclusion |
32 | Appendix |