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Daniel Bishop, started off as a content consultant for small SEO and web design companies notes, Many of the most exciting high-tech projects nowadays include
bringing together knowledge from two or more well-established and
fast-growing fields.
One of the prominent examples is applying machine
learning in order to filter and analyze the huge amount of data we
obtain from the Internet of Things (IoT). But first, let’s see why IoT
needs help from artificial intelligence in order to reach its full
potential.
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| Photo: Shutterstock / Venomous Vector |
In essence, the IoT universe includes all sorts of sensors and smart devices that are plugged into the internet and capable of exchanging data with each other. This industry is growing at an enormous rate. It is expected that until 2022 we’ll have around 50 billion devices connected to the network, which is a 140 percent increase compared to 2018. And in 2035, this number could reach 1 trillion devices.
This massive upsurge also means a rise in the amount of exchanged data that will make this data impossible to analyze by using traditional methods. With 90 percent of online data being generated only in the last two years, this problem has already emerged, especially having in mind the reported shortage of data analysts worldwide. So how can machine learning help with sorting and analyzing this data?
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Source: JAXenter
