Getting Started with Data Acquisition Systems

August 6, 2020

The purpose of any data acquisition system is to gather useful measurement data for characterization, monitoring, or control. The specific parameters of your application will dictate the resolution, accuracy, channel count, and speed requirements of a data acquisition system. A wide assortment of data acquisition components and solutions is available on the market, including low-cost USB modules, benchtop data loggers, and large channel systems. Before you start your search for a data acquisition solution, carefully analyze your application requirements to understand how much capability and performance you need to purchase.

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Nineleaps

We are enablers of Digital Transformation across industries, helping partner companies become future ready. With our unrelenting focus on problem-solving combined with unique approach to precision engineering, we help develop new as well as improve existing technology products. The agile and iterative practices enable us to accelerate product development and in turn speed-to-market.

OTHER WHITEPAPERS
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Achieving Individual – and Organization- Value with AI

whitePaper | November 3, 2022

At Land O’Lakes, a member-owned cooperative agribusiness, farmers are using data and artificial intelligence to make smarter decisions. Over the past 30 years, corn farmers have used advances in bioengineering, chemicals, and analytics to boost their average yields by 50%, from 120 to 180 bushels per acre. T

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Embedding Generative AI and Advanced Search into your apps with MongoDB Atlas

whitePaper | July 5, 2023

Never before has the launch of a new technology so rapidly fired the imagination of enterprises and consumers alike. The arrival of ChatGPT in November 2022 showcased the potential of Generative AI powered by Large Language Models (LLMs) in addressing a vast array of new use cases. These use cases were previously unimaginable with conventional computing and analytical AI (now sometimes described as “traditional” or “classic” AI).

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Fair Use of AI

whitePaper | June 28, 2022

Questions touching on AI ethics and fairness are becoming more mainstream. In recent years we have seen greater public consciousness of what was once a relatively obscure academic issue. This includes the close attention paid to the use of an algorithm to determine 2020 A-levels by the Office of Qualifications and Examinations Regulation (or “Ofqual”).

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ARTIFICIAL INTELLIGENCE AT THE EDGE OF MANUFACTURING

whitePaper | November 1, 2021

Robotics, automation, Internet of Things (IoT), and data are not new in manufacturing. Manufacturing is one of the most data-rich and first industries piloting artificial intelligence at the edge. It’s been estimated, however, that about 95% of all industrial data goes unused. The reason? Legacy equipment and operational systems that tend to be proprietary and siloed are incapable of communicating with each other.

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China’s Advanced AI Research

whitePaper | July 29, 2022

China is following a national strategy to lead the world in artificial intelligence by 2030, including by pursuing “general AI” that can act autonomously in novel circumstances. Open-source research identifies 30 Chinese institutions engaged in one or more of this project‘s aspects, including machine learning, brain-inspired AI, and brain-computer interfaces. This report previews a CSET pilot program that will track China’s progress and provide timely alerts.

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Nutanix Helps Fullgoal Fund Deliver Data Center Innovation

whitePaper | August 1, 2020

One of the first management funds in China, Fullgoal Fund overcame the need for massive data storage and support for large numbers of virtualized servers with a Nutanix hyperconverged infrastructure and enterprise cloud solution.

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Spotlight

Nineleaps

We are enablers of Digital Transformation across industries, helping partner companies become future ready. With our unrelenting focus on problem-solving combined with unique approach to precision engineering, we help develop new as well as improve existing technology products. The agile and iterative practices enable us to accelerate product development and in turn speed-to-market.

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