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Machine learning - OpenCV based IOT using Raspberry pi
Rating: 3.8 out of 5(34 ratings)
339 students

Machine learning - OpenCV based IOT using Raspberry pi

Learn about Supervised Learning (computer vision) with Internet of things. A unique course with growing industry demand.
Created byGuha Rajan M., B.Engg, MBA
Last updated 9/2022
English
English [Auto],

What you'll learn

  • Supervised learning using OPEN CV
  • Internet of things using Raspberry Pi
  • Configuring and acquiring data from sensor(s) by interfacing with Raspberry Pi
  • Developing voice control interface for IOT application
  • How Supervised learning can be used in IOT applications

Course content

15 sections • 45 lectures • 4h 13m total length

  • Prerequisite1:05

    Gain essential programming and hardware skills for Raspberry Pi IoT projects, including Python basics, electronics like resistors and capacitors, Linux command line, interfacing LCDs and sensors, and jumper cables.

  • Course coverage3:18

    Explore supervised machine learning and Internet of Things with a Raspberry Pi 3. Set up OpenCV, connect sensors, and implement Python-based face detection via a smartphone app.

Requirements

  • Basic Programming knowledge particularly Python & Linux command line commands
  • Basic understanding of Electronic component , circuits
  • Raspberry Pi 3 board, 220 ohm resistors, 1 Uf capacitor, LDR sensor, LED, some jumper cables.

Description

You will find course in Supervised machine learning course - OPEN CV generally for computer. But, hardly you will find an integrated course which covers Internet of things  based on supervised machine learning output. In really, for machine learning in real time has no meaning when it works with simulated data. Getting real time data be in from Sensor or an Application, poses it own challenges and this is generally over looked while learning about machine learning.


This unique covers covers both Supervised machine learning and  Internet of things using Raspberry pi.


There is a growing demand for these kind of application, For example:

  1. Building automation - Switch on Electrical device such as lighting and temperature control instrument when human being in present.

  2. Attendance marking based on automatically identification of an employee.

  3. Identify parking free parking lots.

  4. Identify number plate in car.

  5. Prevent Crime - Identify a person with criminal record.

  6. And many more.

All these operate on combination of supervised learning technique coupled with IOT.

Hence this course covers supervised learning coupled with IOT from a building building automation perspective. Once participants are clear about the concept they can then develop /extend it for other applications listed above or on the other machine learning algorithms.

Additionally, voice control IOT application is also growing at a rapid pace. This course also covers topic related to building voice based IOT application using Raspberry pi and other open source software and platforms like OPEN CV, Google assistant, Adafruit IO platform, IFTTT.


Happy learning!!!

Who this course is for:

  • Beginner interested to understand Machine Learning particularly Supervised Machine learning.
  • Interested to learn Internet of things
  • Those interested to know as how Supervisory machine learning can be used IOT application
  • Students with background in Computer Science and Electronics

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