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Using Sensors With Your Raspberry Pi
  • Level Foundation
  • المدة 9 ساعات hours
  • الطبع بواسطة Johns Hopkins University
  • Offered by

عن

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.

الوحدات

Introduction to Module 1

    • 1 Videos
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1 Videos

  • Introduction to Module 1

Sensor Design Concepts

    • 3 Videos
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3 Videos

  • Sensor Design Concepts 1 of 3
  • Sensor Design Concepts 2 of 2
  • Sensor Design Concepts 3 of 2

Quantifying Sensor Error

    • 3 Videos
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3 Videos

  • Sensor Accuracy
  • Sensor Precision
  • Sensor Uncertainty

When Do You Need Real-Time Processing?

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Module 1 Quiz

1 Videos

  • Sensors and Real-Time Processing

Introduction to Module 2

    • 1 Videos
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1 Videos

  • Introduction to Module 2

Sensor Calibration Concepts

    • 2 Videos
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2 Videos

  • Calibration Terminology
  • Sensor Transfer Functions

Implementing and Analyzing the Look-Up Table Method in Python

    • 1 Videos
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1 Videos

  • Analyzing Look-Up Tables in Python

Improving on Look-Up Tables with Piece-Wise Interpolation

    • 2 Videos
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2 Videos

  • Piece-Wise Interpolated Calibration Data 1 of 2
  • Piece-Wise Interpolated Calibration Data 2 of 2

Polynomial Fit as a Universal Solution

    • 3 Videos
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3 Videos

  • Calibration with Polynomial Fit 1 of 3
  • Calibration with Polynomial Fit 2 of 3
  • Calibration with Polynomial Fit 3 of 3

Summary of Module 2

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Module 2 Quiz

1 Videos

  • Summary of Module 2

Introduction to Module 3

    • 1 Videos
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1 Videos

  • Introduction to Module 3

The Steps of Sensor Processing

    • 2 Videos
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2 Videos

  • Integrated Sensors
  • Sensor Signal Flow

Amplifiers for Sensor Interfacing

    • 3 Videos
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3 Videos

  • Sensor Interface Amplifiers 1 of 3
  • Sensor Interface Amplifiers 2 of 3
  • Sensor Interface Amplifiers 3 of 3

Reducing Noise with Filtering

    • 2 Videos
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2 Videos

  • Reducing Noise with Filters 1 of 2
  • Reducing Noise with Filters 2 of 2

Summary of Module 3

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Module 3 Quiz

1 Videos

  • Summary of Module 3

Introduction to Module 4

    • 1 Videos
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1 Videos

  • Introduction to Module 4

Smoothing and Filtering Data in Python

    • 3 Videos
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3 Videos

  • Time-Domain Sliding Window Filter
  • Noise Removal with Spectral Filtering
  • Noise Reduction by Averaging

Improving on Averaging with Weighted Taps

    • 1 Videos
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1 Videos

  • Revisit Time-Domain Sliding Window Filter

Summary of Module 4

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Module 4 Quiz

1 Videos

  • Summary of Module 4

Auto Summary

Enhance your Raspberry Pi projects with the "Using Sensors With Your Raspberry Pi" course, part of a Coursera Specialization. Ideal for beginners, this foundational course delves into sensor integration, covering calibration, accuracy, precision, and post-processing data with Python. With a focus on core concepts over specific examples, learners can apply these techniques to create custom sensor applications. The course spans 540 minutes and is available via Starter or Professional subscriptions. Perfect for those interested in science and engineering, guided by expert instructors from Coursera.

Drew Wilson
Instructor

Drew Wilson