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Using Sensors With Your Raspberry Pi

Using Sensors With Your Raspberry Pi

本课程是 Raspberry Pi Projects 专项课程的一部分

位教师：Drew Wilson

2,307 人已注册

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4个模块

深入了解一个主题并学习基础知识。

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4个模块

深入了解一个主题并学习基础知识。

15 条评论

8 小时完成

灵活的计划

自行安排学习进度

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4 项作业

授课语言：英语（English）

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本课程是 Raspberry Pi Projects 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

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该课程共有4个模块

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.

单元详情

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.

涵盖的内容

8个视频1个作业

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.

涵盖的内容

10个视频1个作业

10个视频总计89分钟

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

1个作业总计30分钟

Module 2 Quiz30分钟

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.

涵盖的内容

9个视频1个作业

9个视频总计118分钟

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

1个作业总计30分钟

Module 3 Quiz30分钟

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.