快速命中：
- According to the环保局, data centers now account for 1.5% of all electricity consumption in the U.S.
- 通过培训机器学习模型，比任何一家公司也可以访问更大的数据，云服务器可以提供优化，如果仅使用本地资源，则不可能。
- 当被问及“您期望在未来三年内对工厂中的以下申请产生什么影响？”45％的受访者Yokogawasurvey stated that autonomy would have a significant impact on environmental sustainability.
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Read the transcript below: |
Hello and welcome to与自动化世界相提并论五. I’m David Miller, Senior Technical Writer for自动化世界. Today, I’m going to be talking about cloud computing, industrial autonomy, and how they can further corporate sustainability initiatives. So, first it’s important to define our terms. I think cloud is easy enough – When we say that we’re taking about using a large, centralized server that streams to many locations simultaneously, as opposed to many smaller, local servers. But the term industrial autonomy perhaps requires a bit more explication.
So, whereas industrial automation typically refers to machines with the ability to perform highly-structured, pre-programmed tasks in lieu of human labor, the term industrial autonomy describes systems that are capable of adapting independently to diverse challenges with minimal human intervention. In this case, we’d be talking about things like AI or machine learning, which might do something like allowing a robot or machine vision system to train itself on new items and objects rather than requiring a human operator to do so for it.
Now, finally, we come to sustainability. Again, simple: Waste reduction, emissions reduction, and energy management. We’re talking about doing more, or the same amount with less waste, less energy consumption, and fewer emissions.
But how do the Cloud and Industrial autonomy further sustainability goals? Well, first of all, when it comes to the cloud its noteworthy that, according to the Environmental Protection Agency, data centers now account for 1.5% of all electricity consumption in the U.S., which is obviously going to have sizeable impact on overall emissions, since energy production, generally, is going to have a carbon footprint. So, by eliminating these local servers, you’re using less electricity, energy consumption is slashed, and so emissions are slashed.
现在，这相当简单，但另一种方式使云实现可持续性仅仅是通过实现具有自己独立的可持续性利益的工业自治。
因此，云通过大大扩展了可以培训AI和机器学习算法的数据池来实现工业自主权。基本上，通过比任何一家公司也可以访问更多的数据训练这些模型，云服务器可以提供优化，如果仅使用本地，现场资源，则不可能。这些优化在做什么？他们提供了更多的智能 - 可以使工业自主权能够提高生产效率。因此，当操作变得更加高效时，它不仅变得越来越有利可图，因为它使用较少的投入来产生相同的输出，而且它也变得更加环保，因为它使用的能量更少，材料较少，等等。
And it turns out that many in industry actually agree. Recently,Yokogawa进行了一项调查，以评估受访者之间的工业自治。他们发现，可持续性是预计工业自主权将产生最大影响的领域之一。
So, when asked “what level of impact are you expecting industrial autonomy will have on the following applications in your plant in the next three years?” 45% of respondents stated that autonomy would have a significant impact on environmental sustainability, including dynamic energy optimization, water management, and emissions reduction, making it the most selected category, above robotic surveillance and inspection, AI-enhanced process optimization, and supply chain optimization.
More specifically, autonomy was most expected most of all to aid in waste reduction, with 38% of respondents anticipating it would have a high impact. After that, 35% of respondents anticipated autonomy having a high impact on greenhouse gas reduction, and 34% on energy management.
因此，如果您对可持续性感兴趣和一些使它的新兴技术趋势感兴趣，那么这是值得关注的事情，并且可以在此视频下面的链接中找到更多信息。
