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Using Sensors With Your Raspberry Pi

Using Sensors With Your Raspberry Pi

Name: Using Sensors With Your Raspberry Pi
Rating: 4.866666666666666 (15 reviews)

This course is part of Raspberry Pi Projects Specialization

Instructor: Drew Wilson

2,306 already enrolled

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4 modules

Gain insight into a topic and learn the fundamentals.

15 reviews

8 hours to complete

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

15 reviews

8 hours to complete

Flexible schedule

Learn at your own pace

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

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This course is part of the Raspberry Pi Projects Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

This course on integrating sensors with your Raspberry Pi is course 3 of a Coursera Specialization and can be taken separately or as part of the specialization. Although some material and explanations from the prior two courses are used, this course largely assumes no prior experience with sensors or data processing other than ideas about your own projects and an interest in building projects with sensors.

This course focuses on core concepts and techniques in designing and integrating any sensor, rather than overly specific examples to copy. This method allows you to use these concepts in your projects to build highly customized sensors for your applications. Some of the ideas covered include calibrating sensors and the trade-offs between different mathematical methods of storing and applying calibration curves to your sensors. We also discuss accuracy, precision, and how to understand uncertainty in your measurements. We study methods of interfacing analog sensors with your Raspberry Pi (or other platform) with amplifiers and the theory and technique involved in reducing noise with spectral filters. Lastly, we borrow from the fields of data science, statistics, and digital signal processing, to post-process our data in Python.

Module details

This first module gets us all on the same page, no matter how much experience you have with sensors or measurement technology. We'll start by describing a straightforward sensor flow model to help us understand the myriad of sensors available in the world, and which you may later build. Then we'll move into the concepts of accuracy, precision, and uncertainty, which are necessary for understanding the inherent error in any measurement system. This module lays the groundwork for the circuits and examples in later modules.

What's included

8 videos1 assignment

In this module, we'll look at examples of three common methods to store calibration data and apply that data to your sensor measurements. These examples range from simple to sophisticated, but none are complicated. We'll use Python and advanced open-source libraries to do the heavy math, just like you can implement in your Raspberry Pi projects.

What's included

10 videos1 assignment

10 videosTotal 89 minutes

Introduction to Module 24 minutes
Calibration Terminology10 minutes
Sensor Transfer Functions18 minutes
Analyzing Look-Up Tables in Python13 minutes
Piece-Wise Interpolated Calibration Data 1 of 210 minutes
Piece-Wise Interpolated Calibration Data 2 of 25 minutes
Calibration with Polynomial Fit 1 of 37 minutes
Calibration with Polynomial Fit 2 of 312 minutes
Calibration with Polynomial Fit 3 of 38 minutes
Summary of Module 21 minute

1 assignmentTotal 30 minutes

Module 2 Quiz30 minutes

Once you have a sensor, and have a Raspberry Pi, there is often a need for circuitry in the middle to interface the two. In this module, we'll show how simple amplifier and filter circuits can be used to adapt voltage levels and reduce noise from your sensor data.

What's included

9 videos1 assignment

9 videosTotal 118 minutes

Introduction to Module 31 minute
Integrated Sensors17 minutes
Sensor Signal Flow6 minutes
Sensor Interface Amplifiers 1 of 320 minutes
Sensor Interface Amplifiers 2 of 314 minutes
Sensor Interface Amplifiers 3 of 38 minutes
Reducing Noise with Filters 1 of 224 minutes
Reducing Noise with Filters 2 of 223 minutes
Summary of Module 34 minutes

1 assignmentTotal 30 minutes

Module 3 Quiz30 minutes

The great thing about using a Raspberry Pi for your sensor projects is that you have access to great open-source software libraries and lots of processing power to manipulate your sensor data. This module looks at a few techniques for using statistical and digital signal processing methods to clean up your sensor data.