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Pnuemonia Detection using Embedded Machine Learning

Pnuemonia Detection using Embedded Machine Learning

Pneumonia has troubled the world for decades, with deaths mounting when early detection is missed. The World Health Organization estimates that each year the number of people affected by pneumonia is nearly 450 million, with the number of deaths reaching 4,000,000 per year, mostly in the developing world. These numbers represent a lot of pain, lost dreams, and grief for people everywhere, and can be mitigated.
Pneumonia detection can be out of reach for many! sectionPneumonia detection can be out of reach for many!
So far, the detection of pneumonia is achieved by using x-rays, chest scans, or extracting blood serum in extreme cases. BUT this requires time, resources, skilled personnel, and it is expensive!
Solving for cost, location and speed will save lives sectionSolving for cost, location and speed will save lives
Ive been working on a solution that harnesses low-cost hardware and software that can deliver effective detection for people everywhere, regardless of location, skill, and affordability. With the help of Edge Impulse and their hardware partners, I can show you how to effectively detect and alert you of potential pneumonia!


Pnuemonia Detection using Embedded Machine Learning

Arijit Das

Arijit is a 15-year-old from India. He loves to play with AI on hardware. He has been into IoT and AI since 2017. Currently, he is an Ambassador at Edge Impulse and creates wholesome content for the team, and also shares his thought in lots of good talks. He leads the TinyML Aspirants Community, which is amongst the biggest Machine Learning communities in Asia. Earlier this year he even joined the tinyML Foundation as their Co-organizer for tinyML India. In his free time, he is usually found to play his Spanish Guitar and making EDM songs!


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Dati aggiornati il 08/12/2024 - 22.41.48