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Drew Wilson
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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/12jkjm/using
What's inside
Syllabus
Designing Sensors
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.
Read more
Syllabus
Designing Sensors
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.
Read more
Calibration Methods
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.
Interface Circuits
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.
Introduction to Signal Processing
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.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Useful for individuals with an interest in hardware and electronics
Specialization is available for computer science students
Builds on concepts from two previous Specialization courses
Geared towards learners with a background in Python
Requires access to a Raspberry Pi or similar platform
Save this course
Save Using Sensors With Your Raspberry Pi to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Using Sensors With Your Raspberry Pi with these
activities:
Attend meetups or conferences on sensor technology
Show steps
Provides opportunities to connect with experts in the field, learn about the latest trends, and stay updated on advancements.
Show steps
-
Identify meetups or conferences related to sensor technology.
-
Attend the events and participate in discussions.
-
Connect with speakers, attendees, and industry professionals.
Read Getting Started with Raspberry Pi Sensors
Show steps
Provides a comprehensive overview of Raspberry Pi sensors and how to use them.
View
Getting Started With Raspberry Pi: Getting to...
on Amazon
Show steps
-
Read through the book's chapters on sensor basics, interfacing sensors with the Raspberry Pi, and using sensors for data collection.
-
Complete the hands-on exercises in the book to reinforce your understanding of the material.
Practice data processing and visualization with Python
Show steps
Strengthens your ability to manipulate and visualize data, which is crucial for working with sensor data.
Browse courses on
Python
Show steps
-
Use Python to read data from a sensor.
-
Clean and process the data using Python.
-
Visualize the data using Python libraries such as matplotlib and seaborn.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore the Raspberry Pi's built-in sensors
Show steps
Develops your understanding of Raspberry Pi sensors by exploring the different sensors directly on your Raspberry Pi.
Browse courses on
Raspberry Pi
Show steps
-
Follow tutorials to set up and use the Raspberry Pi's temperature sensor.
-
Use the Raspberry Pi's camera module to capture images and videos.
-
Connect an external sensor to your Raspberry Pi and read its data.
Simulate sensor data pipeline
Show steps
Simulate a simple sensor data pipeline to demonstrate how to structure your project and apply your knowledge.
Browse courses on
Python
Show steps
-
Start with a simple sensor model that generates realistic simulated sensor readings.
-
Add noise to the simulated data to make it more realistic.
-
Process the simulated data using the techniques you learned in the course.
-
Visualize the results of your processing.
Build a sensor-based project from scratch
Show steps
Builds on and tests your knowledge by allowing you to apply what you've learned in the course to a real-world scenario.
Browse courses on
Hardware
Show steps
-
Identify a problem that can be solved using a sensor-based system.
-
Design and build the hardware for your sensor-based system.
-
Write the software to process the data from your sensor and control your system.
-
Test and evaluate your sensor-based system.
Summarize and integrate notes and materials
Show steps
Aids in retention and comprehension by encouraging the organization and integration of learning materials.
Show steps
-
Review and summarize notes from the course modules.
-
Organize and integrate notes with additional materials such as handouts and articles.
-
Create a study guide or cheat sheet for easy reference.
Contribute to open-source sensor projects
Show steps
Fosters collaboration, deepens understanding, and allows you to apply your knowledge to real-world projects.
Show steps
-
Find open-source sensor projects on platforms like GitHub.
-
Review the project documentation and code.
-
Identify an area where you can contribute, such as adding a new feature or fixing a bug.
-
Submit a pull request with your changes.
Attend meetups or conferences on sensor technology
Show steps
Provides opportunities to connect with experts in the field, learn about the latest trends, and stay updated on advancements.
Show steps
Show steps
Show steps
- Identify meetups or conferences related to sensor technology.
- Attend the events and participate in discussions.
- Connect with speakers, attendees, and industry professionals.
Read Getting Started with Raspberry Pi Sensors
Show steps
Provides a comprehensive overview of Raspberry Pi sensors and how to use them.
View
Getting Started With Raspberry Pi: Getting to...
on Amazon
Show steps
Show steps
Show steps
- Read through the book's chapters on sensor basics, interfacing sensors with the Raspberry Pi, and using sensors for data collection.
- Complete the hands-on exercises in the book to reinforce your understanding of the material.
Practice data processing and visualization with Python
Show steps
Strengthens your ability to manipulate and visualize data, which is crucial for working with sensor data.
Browse courses on
Python
Show steps
Show steps
Show steps
- Use Python to read data from a sensor.
- Clean and process the data using Python.
- Visualize the data using Python libraries such as matplotlib and seaborn.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore the Raspberry Pi's built-in sensors
Show steps
Develops your understanding of Raspberry Pi sensors by exploring the different sensors directly on your Raspberry Pi.
Browse courses on
Raspberry Pi
Show steps
Show steps
Show steps
- Follow tutorials to set up and use the Raspberry Pi's temperature sensor.
- Use the Raspberry Pi's camera module to capture images and videos.
- Connect an external sensor to your Raspberry Pi and read its data.
Simulate sensor data pipeline
Show steps
Simulate a simple sensor data pipeline to demonstrate how to structure your project and apply your knowledge.
Browse courses on
Python
Show steps
Show steps
Show steps
- Start with a simple sensor model that generates realistic simulated sensor readings.
- Add noise to the simulated data to make it more realistic.
- Process the simulated data using the techniques you learned in the course.
- Visualize the results of your processing.
Build a sensor-based project from scratch
Show steps
Builds on and tests your knowledge by allowing you to apply what you've learned in the course to a real-world scenario.
Browse courses on
Hardware
Show steps
Show steps
Show steps
- Identify a problem that can be solved using a sensor-based system.
- Design and build the hardware for your sensor-based system.
- Write the software to process the data from your sensor and control your system.
- Test and evaluate your sensor-based system.
Summarize and integrate notes and materials
Show steps
Aids in retention and comprehension by encouraging the organization and integration of learning materials.
Show steps
Show steps
Show steps
- Review and summarize notes from the course modules.
- Organize and integrate notes with additional materials such as handouts and articles.
- Create a study guide or cheat sheet for easy reference.
Contribute to open-source sensor projects
Show steps
Fosters collaboration, deepens understanding, and allows you to apply your knowledge to real-world projects.
Show steps
Show steps
Show steps
- Find open-source sensor projects on platforms like GitHub.
- Review the project documentation and code.
- Identify an area where you can contribute, such as adding a new feature or fixing a bug.
- Submit a pull request with your changes.
Career center
Learners who complete Using Sensors With Your Raspberry Pi will develop knowledge and skills
that may be useful to these careers:
Sensor Engineer
Sensor Engineer
A Sensor Engineer designs, develops, and tests sensors. They work in a variety of industries, including automotive, aerospace, and medical devices. This course provides a strong foundation in sensor engineering principles, such as sensor types, signal conditioning, and data acquisition.
Electronics Engineer
Electronics Engineer
An Electronics Engineer designs, develops, tests, and manufactures electronic devices and systems. They work in a variety of industries, including consumer electronics, medical devices, and telecommunications. This course may be useful in providing a foundation in electronics engineering principles, such as digital logic, analog circuits, and embedded systems.
Mechanical Engineer
Mechanical Engineer
A Mechanical Engineer designs, develops, and tests mechanical systems. They work in a variety of industries, including automotive, aerospace, and manufacturing. This course may be useful in providing a foundation in mechanical engineering principles, such as mechanics of materials, thermodynamics, and fluid dynamics.
Electrical Engineer
Electrical Engineer
An Electrical Engineer designs, develops, tests, and supervises the installation of electrical systems. They work in a variety of industries, including automotive, aerospace, manufacturing, and telecommunications. This course may be useful in providing a foundation in electrical engineering principles, such as circuit analysis, digital signal processing, and control systems.
Robotics Engineer
Robotics Engineer
A Robotics Engineer designs, develops, and tests robots. They work in a variety of industries, including manufacturing, healthcare, and defense. This course may be useful in providing a foundation in robotics engineering principles, such as kinematics, dynamics, and control systems.
Mechatronics Engineer
Mechatronics Engineer
A Mechatronics Engineer designs, develops, and maintains systems that integrate mechanical, electrical, and computer engineering principles. They work in a variety of industries, including robotics, automation, and manufacturing. This course may be useful in providing a foundation in mechatronics engineering principles, such as control systems, sensors, and actuators.
Manufacturing Engineer
Manufacturing Engineer
A Manufacturing Engineer plans, designs, and oversees the production of goods. They work in a variety of industries, including automotive, aerospace, and medical devices. This course may be useful in providing a foundation in manufacturing engineering principles, such as process planning, quality control, and materials science.
Quality Engineer
Quality Engineer
A Quality Engineer develops and implements quality assurance and quality control procedures to ensure that products meet customer requirements. They work in a variety of industries, including manufacturing, software, and healthcare. This course may be useful in providing a foundation in quality engineering principles, such as quality management, statistical process control, and risk management.
Industrial Engineer
Industrial Engineer
An Industrial Engineer designs, improves, and installs integrated systems of people, materials, and equipment. They work in a variety of industries, including manufacturing, healthcare, and logistics. This course may be useful in providing a foundation in industrial engineering principles, such as process improvement, systems analysis, and data analysis.
Data Scientist
Data Scientist
A Data Scientist is a professional who uses their knowledge of data analysis, statistics, and computer science to solve business problems. They develop and implement data-driven solutions to improve business outcomes. This course may be helpful in providing a foundation in data analysis and data processing techniques, which can be applied in a variety of industries.
Data Analyst
Data Analyst
A Data Analyst is a business professional who analyzes data to uncover trends, patterns, and insights. They use their findings to make recommendations to businesses on how to improve their operations, marketing, and customer service. This course may be useful in providing a foundation in data analysis techniques, such as statistical analysis, data visualization, and data mining, which can be applied in a variety of industries.
Product Manager
Product Manager
A Product Manager is responsible for the development, launch, and marketing of a product. They work closely with engineering, design, and marketing teams to ensure that the product meets customer needs. This course may be useful in providing a foundation in product management principles, such as market research, product planning, and customer feedback.
Systems Engineer
Systems Engineer
A Systems Engineer designs, develops, and tests complex systems. They work in a variety of industries, including aerospace, defense, and telecommunications. This course may be useful in providing a foundation in systems engineering principles, such as system architecture, requirements analysis, and risk management.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They work in a variety of industries, including technology, finance, and healthcare. This course may be useful in providing a foundation in software engineering principles, such as object-oriented programming, data structures, and algorithms.
Test Engineer
Test Engineer
A Test Engineer designs, develops, and executes tests to ensure that products meet specifications. They work in a variety of industries, including manufacturing, software, and healthcare. This course may be useful in providing a foundation in test engineering principles, such as test planning, test execution, and data analysis.
For more career information including salaries, visit:
OpenCourser.com/course/12jkjm/using
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Using Sensors With Your Raspberry Pi.
This classic textbook provides a comprehensive overview of digital signal processing. It covers topics such as Fourier analysis, filter design, and adaptive filtering, which are useful for understanding the processing of sensor data.
Provides a comprehensive overview of real-time digital signal processing. It covers topics such as real-time filtering, adaptive filtering, and fast Fourier transforms, which are useful for understanding the processing of sensor data in real-time.
This official guide to the Raspberry Pi provides a comprehensive overview of the hardware and software platform. It useful reference for understanding the capabilities and limitations of the Raspberry Pi when working with sensors.
This textbook presents a comprehensive overview of sensor system technologies, covering topics such as sensor types, signal processing, and data fusion. It provides a solid foundation for understanding the design and implementation of sensor systems.
Provides a comprehensive overview of analog circuit design for signal processing. It covers topics such as operational amplifiers, filters, and data converters, which are essential for interfacing sensors.
Provides a comprehensive introduction to data analysis using Python. It covers the basics of data manipulation, visualization, and statistical analysis.
Presents a concise and accessible overview of sensor and actuator technologies. It covers the fundamentals of sensor design, operation, and applications, providing a practical guide for engineers and students.
Provides a gentle introduction to data science concepts and techniques. It useful resource for understanding the basics of data analysis and machine learning, which are applicable to sensor data processing.
Save
Provides a practical guide to data acquisition techniques, including sensor selection, signal conditioning, and data analysis. It valuable resource for engineers and students involved in data acquisition projects.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/12jkjm/using
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Via
Coursera
Institution
Johns Hopkins University
Instructor
Drew Wilson
Language
English
This course belongs to a
collection
called
Powering your Home Projects with Raspberry Pi. It's comprised of four courses:
- Designing Hardware for Raspberry Pi Projects
- Communications and High-Speed Signals with Raspberry Pi
- Using Sensors With Your Raspberry Pi (viewing)
- Beginning Custom Projects with Raspberry Pi
Good to know
Useful for individuals with an interest in hardware and electronics
Specialization is available for computer science students
Builds on concepts from two previous Specialization courses
Geared towards learners with a background in Python
Requires access to a Raspberry Pi or similar platform
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