Pocket AI and IoT: Turn Your Phone Into a Smart Fitness Tracker
Pocket AI and IoT: Turn Your Phone Into a Smart Fitness Tracker


Want to learn more about trends like AI, IoT and wearable tech? In this workshop, we will cut through the hype by building a “smart” fitness tracker using your own mobile device. We’ll do hands-on exercises: you’ll acquire data from sensors, design a step counter and train a human activity classifier. You will leave motivated and ready to use machine learning and sensors in your own projects!  
The goal for this session is twofold: show our participants how easy it is to get started with Machine Learning and wearables and set them up for success to take on challenging projects in this domain. A clear instruction sheet will guide the participants through exercises ranging from beginner to intermediate level. This workshop is highly interactive with hands-on exercises in which the participants will create a “smart” wearable device and test it out. We aim to demonstrate how powerful applications can be built when we combine machine learning, sensor analytics, and IoT. Participants will use the free MATLAB Mobile App to access built-in sensors and analyze data on their mobile devices.

● MATLAB Online;
● MATLAB Mobile;
● MATLAB Drive;
● mobile devices such as a phone or tablet;



Louvere Walker-Hannon is a MathWorks Application Engineer, who provides direction and recommendations on technical workflows for various applications. Specifically, she assists with the following topics image processing, computer vision, machine learning, deep learning, geospatial analysis, and data analytics when discussing technical workflows. Louvere has worked in three different engineering roles throughout her 20 year career while at MathWorks. A prominent theme in her career is communication of technical concepts to various audiences and being involved with STEM education. She was also a Program Presenter, in this role she was the lead educator of STEM topics for Cahners ComputerPlace within the Boston Museum of Science. Louvere is a member of the Society of Women Engineers (SWE) and the National Society of Black Engineers (NSBE). She has a long history of serving as a STEM mentor. Louvere volunteers with Black Girls Code and the Society of Women Engineers. She has a bachelor’s degree in Biomedical Engineering and a master’s degree in Geographic Information Technology with a specialization in Remote Sensing. Louvere has presented and continues to present at several STEM related conferences on various topics. She recently presented her work on a Natural Language Processing application at the 100th American Meteorological Society in January 2020.

Open Data Science




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