Accelerating Computer Vision Application Development

Modular mobile carts & pre-trained learning models save months in bringing products to market

By Roger Lam, MBX Systems

The rise of artificial intelligence and edge computing has paved the way for computer vision applications such as fall detection, virtual patient interactions and remote surgery viewing designed for deployment near hospital beds, in operating rooms and in other edge environments. Until recently, however, most initiatives in this area have been stymied by lengthy and expensive development cycles.

Independent software vendors (ISVs) aiming to develop these kinds of smart hospital solutions had to spend up to two years and $100,000+ for custom medical cart design, engineering and mold injection, and nearly that long to build machine learning models from scratch. By the time the finished solution was ready for market, technology advances such as CPU and GPU performance gains likely made it obsolete, leaving vendors with unsellable prod…

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Value analysis/value engineering can equal cost improvements

Value analysis/value engineering (VAVE) is about boosting performance, efficiency and cost-effectiveness by improving the design of a finished product.

Roger Lam, MBX Systems

[Image from Pixabay]

Most medical device manufacturers are familiar with the principles of design for manufacturing (DFM), a process utilized in the initial hardware development process to optimize product components and performance before production. But after launch, there’s another critical step that can trim the total cost of ownership by 5–10% annually by fine-tuning design elements that usually get short shrift in the rush to get to market.

Value analysis/value engineering (VAVE) involves engaging an engineering team to identify design improvements in the finished product and related processes that can increase performance, efficiency and cost-effectiveness. VAVE requires a comprehensive audit of areas ranging from the embedde…

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