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Keynote: The Rise of AI in the Internet of Things

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Juthika Khargharia
Global IoT Evangelist at SAS
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Juthika Khargharia
Global IoT Evangelist at SAS

Juthika Khargharia, Ph.D is a Principal Solutions Architect working for SAS’ Internet of Things Division specializing in machine learning, deep learning and artificial intelligence. In her role, she assists customers in defining their business problems and uses SAS advanced analytics solutions to help them reach their business goals and objectives. Juthika holds a Ph.D. in Astrophysics from the University of Colorado. Her Ph.D. research work consisted of designing observations, collecting and analyzing low signal-to-noise image data obtained from ground based telescopes to determine black hole masses in our Galaxy.

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Topic: IoT

The amount of data being generated in the Internet of Things from sensors, devices, equipment, and infrastructure is on a very rapid incline. Thus, there is an ever-increasing need for the use of advanced analytics methodologies and embedded AI to understand and process IoT data for meaningful business insights. This confluence of AI and IoT, also known as AIoT will run the entire gamut from personalization in healthcare for the connected patient to the prediction of component failures in large industrial assets. In this session, we will cover a variety of AIoT applications across multiple industries and discuss how this leads to transformative business growth. These applications will continue to improve with faster processors, more advanced machine learning algorithms, and deeper integration to edge devices.

03:32 The AIoT Lifecycle

05:34 AI for the IoT

07:03 AIoT use cases

12:42 Power anomaly detection

16:00 Queue monitoring and control

19:07 Computer vision pipeline

23:15 Simulation model

25:17 Reinforcement learning

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Thank you, Kevin. Thanks for the nice introduction. So let's get started with with my presentation gear. So, you know the excitement that is there today around and around internet of things and how a I please a big value around use cases in the internet of things. You've probably have seen lots of predictions around the market and you know the value of this market and some of those things are listed out here which is an estimate of about 55 billion connected iot devices by the year 2025 and and you can imagine the amount of data that's going to generate

Adderalls estimate around how AI is going to impact coyote related projects. So for example, we have an estimate of about greater than 80% iot projects that will include a I buy 2022 Which is at about a 10% today, so it's going to see a big shift in that area. The other area also is how we're going to see almost at 38% Lyft and profitability just from the usage of a i l we didn't iot by the year 2035. So all of this predictions and from what we are seeing today at the role that AI plays in the world of iot is just increasing our

over and over again and I cannot stress the importance the value that a I will bring to the table in terms of iot related projects as well. So, you know, he is definitely a very hot topic right now. You know, we are all talking about Ai and because of which there also exists a ton of different definitions are on a ISO in this particular slide. I'm just trying to level set what's ass means when we talk about AI right so Longest slide you'll see that I have two different sections write the bottom half of the slide is really talking about the core areas that

constitute a I so those can include areas such as statistics machine learning deep learning computer vision natural language processing forecasting

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December 11, 2020
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