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How Machine Learning Is Used In Extreme Precision for Sensor Technology

Very people will talk about trends such as “Internet of Things,” “Big Data,” and “Robots.” I want to say that these trends are actually linked to each other and become a big trend, like “Universal Theory”. In this chain, each ring will have an impact on the next ring, thus generating a positive cycle.
The sensors in the various connected devices generate a lot of data. Massive data makes machine learning possible. The result of machine learning is AI. The AI ​​instructs the robot to perform tasks more accurately, and the robot’s actions trigger the sensor. This whole is a complete cycle.

Let’s look at the working of cycle:

  1. Sensor generates data

By 2014, the number of devices connected to the Internet exceeded the total population of the world. Cisco predicts that by 2020, there will be 50 billion interconnected devices. Most of these devices have sensors, either with Electric Imp embedded sensors or with Estimote external sensors.Sensors in the device produce unprecedented amounts of data.

  1. Data support machine learning

In 2020, 35ZB of data is expected to be generated, which is 44 times the amount of data in 2009. At that time, whether structured or more structured data can be processed by the machine, resulting in a lot of insights.

  1. Machine learning improves AI

Machine learning relies on data processing and pattern recognition so that computers can learn without programming. Today’s massive data and computing power are driving breakthroughs in machine learning.
The full power of machine learning, look at Google to know. Google is using machine learning to map the location of every business in world, every house, every street on the map. The whole process takes only one hour.

  1. Artificial intelligence guides robot action

As computers have done better than humans in chess and road signs, we have reason to expect more from the future. As more sensors collect more and more data, this optimizes more machine learning algorithms, so we can logically infer that the ability of a computer combined with a robot to perform tasks will grow exponentially.

  1. Robots take action

Not only do hundreds of companies make robots that can do all kinds of work, but the robot itself becomes smarter, and with the advancement of AI, it can accomplish many of the tasks we dream of.

  1. Action trigger sensor

The machine takes action to trigger the sensor to collect the data so that the entire cycle is complete.

This is the “universal theory” in the technical field that we have proposed.

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