Clean Sensor Data with Filters

by Ashraf Said AlMadhoun

Read any Noisy Sensor Data and use different types of filters to reduce the noise and convert RAW data to useable data

$9.99

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img Duration

1h 41m

Course Details

What you'll learn

  • Read Analog Sensors Data using Arduino

  • Filter noise using Low Pass Filter

  • Analyze, Filter and Convert Sensor Readings

  • Filter noise using High Pass Filter

  • Filter noise using Band Pass Filter

  • Filter noise using Stop Pass Filter

  • Filter noise using Moving Average Filter

  • Filter noise using Normal Average Filter

  • Learn the difference between different filters and which to use and when

  • Learn how to code each filter in Arduino C Coding

  • Use sensor data to achieve project goals

 

Requirements

  • An Internet Connection

  • Basic knowledge in Programming

 

Description

Sensors and microcontrollers allow us to turn real-life phenomena into simple numerical signals that we can learn from. However, the raw output from the sensor may not be sufficient to extract desired information from. Real hardware is subject to interference and noise from the environment.

Filtering is a simple technique that you can use to smooth out the signal, removing noise and making it easier to learn from the sensor output. This course introduces the concept of filters in different types and how to incorporate them into your design.

Measurements from the real world often contain noise. Loosely speaking, noise is just the part of the signal you didn’t want. Maybe it comes from electrical noise: the random variations you see when calling analogRead on a sensor that should be stable. Noise also arises from real effects on the sensor. Vibration from the engine adds noise, etc.

Filtering is a method to remove some of the unwanted signals to leave a smoother result.

Why you should take this course?

  • Since many sensors produce noisy data, this course will show you how to filter and clean the data so that it can be used for more accurate measurements.

  • You will learn practical ways on how to reduce sensor noise and can perform some of these filters using MATLAB.

  • Nowhere else will you find the information in this course because it is a comprehensive guide.

  • The videos not only teach you about filters but also give exercises that can be done to gain hands-on experience.

  • This course will give you the confidence to know that you can perform different types of filters which are already specified by MATLAB.

  • A wide variety of lessons are available such as signal preprocessing, filtering algorithms, and error models.

You Will Learn:

  • Why we need to clean noise data

  • What are Filters

  • How to implement Filters using Microcontrollers like Arduino

  • Moving Average Filter

  • Averaging filter

  • Running average filter

  • Exponential filter

  • Turning Filtering equations into actual code

  • Compare results before and after filtering

You will learn as you practice with real-world examples in this course.

User Testimonials and Social Proof

"This course provided me with the practical skills to clean sensor data efficiently. Highly recommended!" - Sarah J.

"A comprehensive and easy-to-follow guide on using filters for sensor data. Excellent for beginners and professionals alike!" - Michael T.

An Author Bio Showing Off Credentials

Educational Engineering Team

Team of skilled Engineers Sharing Knowledge with the World

Educational Engineering Team is a Leading Team in the Microcontroller Industry, with over 13 Years of Experience in Teaching and Doing Practical Projects.

We strive to put all our hands-on experience in these courses. Instead of superficial knowledge - we go into the depth of the topic and give you the exact - step by step blueprint on how to tame simple as well as complex topics in easy and digestible bite-sized videos.

This real-world knowledge enables you to grasp knowledge easily, and you can apply this learning immediately to your life and projects.

Educational Engineering Team has been in the Programming and Microcontroller business since 2007. We have been part of many projects. Over the course of these years - we have gained a good insight into students’ and educators’ needs. We are passionate about sharing all our collective knowledge with you. As of 2018, we have already taught over 250k-THOUSAND students and counting.

Currently, we have more than 100+ Courses on Coursetakers.

Educator and Author of "Educational Engineering".

Ashraf is an educator, Mechatronics engineer, electronics and programming hobbyist, and Maker. He creates online video courses on the EduEng YouTube Channel (More Than 4 Million View, 20k + Subscriber) and author of four Microcontroller books.

As a Chief Educational Engineer since 2007 at Educational Engineering Team, the company he founded, Ashraf’s mission is to explore new trends and technology and help educate the world and make it a better place.

Educational Engineering offers educational courses and Bootcamps, articles, lessons, and online support for electronics hobbyists, Programming hobbyists, Microcontroller hobbyists, STEM students, and STEM teachers.

That team also works as freelancer engineers, helping many students in their graduation projects, and providing guidance and consulting for many students over the years to help them kick-start their career.

Ashraf’s core skill is explaining difficult concepts in a step-by-step, easy-to-understand manner using video and text. With over 11 years of tertiary teaching experience, Ashraf has developed a simple yet comprehensive and informative teaching style that students from all around the world appreciate.

His passion for Microcontrollers and Programming, and in particular for the world of Arduino, PIC Microcontroller, Raspberry Pi, has guided his personal development and his work through Educational Engineering.

Ashraf’s online courses have helped over 250,000 people from around the world to be better and to make a great career in the industry.

Educational Engineering Team offers Courses on

  • Circuit Design, Simulation, and PCB Fabrication

  • Arduino, PIC Microcontroller, and Raspberry Pi

  • Programming in C, Python, and other programming languages

  • PLC Industrial Programming and Automation

  • 3D Design and Simulation

  • ESP and IoT World

A Single Powerful CTA

Enroll now and start your journey to mastering sensor data cleaning with filters today!

FAQ Section

Q: Do I need any prior knowledge to take this course?

A: No prior knowledge or skills are required. This course is designed for complete beginners.

Q: How long will it take to see results?

A: Results can vary, but many students start seeing results within the first few weeks of applying the strategies taught in the course.

Q: Is there a money-back guarantee?

A: Yes, Coursetakers offers a 30-day money-back guarantee if you are not satisfied with the course.

What You Will Learn

  • Why we need to clean noise data

  • What are Filters

  • How to implement Filters using Microcontrollers like Arduino

  • Moving Average Filter

  • Averaging filter

  • Running average filter

  • Exponential filter

  • Turning Filtering equations into actual code

  • Compare results before and after filtering

Who Is This Course For

  • Anyone interested in sensor data processing

  • Beginners with no prior experience in filtering techniques

  • Makers and hobbyists wanting to enhance their data accuracy

  • Students and professionals looking to improve their skills in data processing

Requirements

  • A computer with internet access

  • Basic understanding of the internet and web browsing

  • Willingness to learn and implement the strategies taught

 

Who this course is for:

  • Anyone Interested in Filtering Noise from different Sensors using Microcontrollers like Arduino

  • Anyone Interested in Learning how to code filters using Arduino C Programming

  • Anyone Interested in Learning New Things about Arduino

  • Anyone with slight interest in making great things

  • Arduino Geeks

  • Electronics Geeks

  • Hardware developers

  • Online Branch

    Online, Online, Online

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