Chapter 1: Introduction to Data Science in the ClassroomChapter Goal: After reading this chapter, readers will understand the importance of measurement - they will able to measure air temperature using a thermometer and they will understand how it works. We will introduce a number of core data science concepts and how to apply them to build an experiment. We'll cover some basic how-to skills for gathering and tabulating data, and we will undertake some analysis on our results. The reader will get an overview of a complete and meaningful example of applied data science, and they will be ready to explore more deeply.
- Data is everywhere: Why do we measure things and what does 'measuring things' even mean? How is this related to data science?
- Using Temperature: How is temperature used in the world?
- Measuring temperature: What does a thermometer do and how does it work?
- Designing an experiment: We will begin to design an experiment using our thermometers to measure the temperature at different locations. We will look at factors that might have a negative impact on our experiment and we'll look at controlling them. We we will see the importance of validity and reliability.
- Data capturing: Before our experiment commences, we will introduce the reader to the concept of data capturing - recording (tabulating) data.
- Experimenting with temperature: Here we will outline the classroom activity (experiment) to collect and analyse data. We will introduce the concept of experimental design and see how it can help address issues of reliability and validity.
- Analysing our results: We will introduce the concept of 'interrogating' the data by listing a series of questions that the data set might provide insights into. In a later chapter we will look at more sophisticated analysis, for now we show how to extract some meaning / insights from the data we just collected.
- Summary: Brings together all the new concepts introduced in this chapter and sets the stage for the next chapter.
Chapter 2: Data Science Goes DigitalChapter Goal: After reading this chapter, readers will understand why there is a tendency to 'go digital' and what it means to read data digitally. We will introduce technology and coding to replicate our experiment and we will begin to explore ways that the digital approach can expand our capabilities and potential as data scientists. We'll use a BBC micro:bit (or any similar device) to measure temperature, all the while looking at our experimental design and how to improve it. By the end of the chapter we will have identified the sort of hardware we need in our data science toolkit.
- Making it digital: Why is everything digital? What are the types of thermometers? Explain about digital thermometers and show how they are different to analogue. How can introducing digital improve our temperature experiment from Chapter 1
- Using a microprocessor to measure temperature digitally: We will use micro:bit - brief intro to microbit, including sensors that can be used for measure things causing GW (only the ambient temperature sensor).
- Using the BBC micro:bit as a thermometer: Programming the micro:bit for reading the air temperature of the classroom. Use MakeCode (or MicroPython) for programming.
- Analogue and digital thermometers: Reading temperature simultaneously from a micro:bit and a thermometer. Discuss differences between methods. In particular the difficulties of manual reading, need to read two things same time (thermometer or micro:bit and the clock)
- Limitations of micro:bit as a standalone tool: We've seen some limitations with microbit. By itself it provides us with too few tools. What are -ons and how are add-ons used with microprocessors, and what about micro:bit? Discuss variety of options available to educators.
- Identifying the digital tools we need for data science: We have identified weaknesses in micro:bit. We also review what we need to be accomplished data scientists.
- Selecting our tool kit: Introduce the configuration (microbit + XinaBox) that we will use for main thread of examples. Explain why. Offer tips to adapt for other platforms throughout.
- Chapter summary
Chapter 3: Building a Weather StationChapter Goal: After this chapter the reader will be able to build a digital weather station in the backyard, or classroom! We'll show the reader how to build one using a micro:bit and the XinaBox SW01 &, BM01 and we'll explain how other kit could be used. The reader will record temperature, humidity, and pressure by programming the micro:bit to display the sensor readings on the led screen. The reader will be reminded of the limitations of the micro:bit LED screen and an alternative screen to display all the sensor data will be introduced. We'll show the reader how to connect the OD01 OLED display to show the output, and we'll explain other options. The reader finishes the chapter with a working weather station, and the realisation that writing values down all the time is a real limiting factor.What we need for the circuit - brain, power, weather sensor and visual display unit. We show what we are using - micro:bit, xChip SW01, BM01 & xBUS connectors and show how to connect. We make it clear other components can be used - show some examples (e.g. Adafruit, Monk Makes, RPi).
- Programming the micro:bit (MakeCode Weatherbit package/MicroPython) to read sensor values (temperature, humidity, and pressure) and display them on the LED screen.
- Test the program - the display is just not adequate. We need to introduce a more suitable display. So, we add the OD01 OLED display and program it. NB - readers do not need the OLED at all - they can continue to chapter with the 5x5.
- Now we measure the weather over a period of time. Classes may have some with OLED and some with 5x5. Write down the sensor data in a table by looking at the display (OLED or 5x5). Making a few copies of the data capturing sheet (we will provide the format of the sheet). Distributing them among some students in different locations and ask them to write down the sensor values at the same time (maybe every 1 minute at 10 minute intervals). The exercise is likely to be flawed in many ways - recording error will occur. Discuss causes of errors by recording the sensor values manually, with either display.
- Data Analysis. We introduce charts and talk about time - how each set of points is implicitly time-stamped. Talk about correlations. Nothing too heavy yet - no statistical significance. We are encouraging the curious mind to ask questions, like in earlier chapters.
- Discuss how alternate data could be substituted in. Talk about sensors in general, how other sensors could be used in place of weather. Weather station code here can be adapted for all sorts of uses. We introduce a few examples we'll use in our GW experiments later.
- Discussing the limits of the experiment - use the example of taking readings over a 24 hour period. How can that be accomplished with our circuit? How do we take the human out of the equation?
Chapter 4: Storing and retrieving dataChapter Goal: In this chapter We will build further on our experiment and enhance our data science tool set introducing the use of computer memory for data capturing - the reader will be able store and retrieve data digitally for further analysis. The reader will be able to use the micro:bit's tiny persistent file system to store the data captured by the weather station then move that data onto their laptop and perform analysis. The reader will understand the limitations of the micro:bit storage by running an overnight test and counting the data points. Introduction to file storage on the micro:bit storage: We recap on why we want to save files and provide a non-technical overview of persistent memory on the micro:bit!
- Save Hello World to file: Briefly demonstrate the most simple code to write to and save a file. Include a brief and simple overview of how to extract the file after.
- Working with files: Explain key elements of the process - storing data (writing) on the micro:bit file system - creating, writing, closing files. Ensure every line of code in (2) is explained.
- Incorporating files into our experimental design: What impact does access to computer memory have on our experimental design? How do we amend the design to accommodate our new capabilities.
- Measuring memory size: how many data points we can record until the memory gets full? What is the maximum file size? Write some code to test this quickly. How many readings can we take in a 24 hour period?
- Replicating the weather station experiment with file storage: Now we set up an overnight experiment with the weather station to record data at the interval we have calculated. We will analyse the data in detail, in the next chapter.
- Addressing memory limitations: micro:bit provides us with some file storage, but not much. We introduce options to address that - ways to expand the available memory. We offer suggestions for why this would be useful
- Summary
Chapter 5: The basics of analysing the dataChapter Goal: The reader now has the capacity to generate files containing data tables. In previous chapters we have undertaken analysis using our eyes and logic; here we look at developing some basic skills using common software (Excel, libra, GSheet). The reader will be able to import their table into a multi column spreadsheet and ensure it is formatted OK. We will find values such as max and min, as well as averages (mean, median, mode). We will discuss trends, data significance and we'll look more formally at the concept of confidence. By the end of this chapter we will have provided the reader with all the analysis tools we will use in this book - later chapters will look at how to apply these.
- The workflow of data science: We review the process we have been learning about - gathering, Importing, analysing. Summarise what we know so far and introduce the goal of this chapter.
- The workflow of analysis: Break down the analysis process into constituents. Show the steps needed to undertake analysis and describe the tools we use at each step.
- Data rigour: Checking the data and ensuring it is formatted OK. Encourage data discipline - spot checks, logic checks. We remind readers that the human eye remains the most powerful too.
- Using spreadsheets: Introduce aggregation measures, explain them and show how to find them using a spreadsheet-
- Charts and visualisations: Show how to generate charts in a few software platforms. Show lots of examples to demonstrate how patterns can be seen in charts that are hard to see in tables. Use real work GW examples and a broad variety of chart types.
- Visualising acceleration: Write a program with just the micro:bit that saves 200 or so values of accelerometer to file. Run the program, wave the micro:bit round, extract that data and then chart it. Repeat and wave differently to get a different data profile - discuss.
- Summary - Guidelines for analysis: Draw together all the advise / info we have provided so far into a checklist people can use when undertaking analysis.
Chapter 6: Wireless CommunicationChapter Goal: In this chapter we will introduce the reader to a variety of wireless communication options. They will understand the differences between Bluetooth, Wi-fi and LoRa (maybe Sigfox too) and they will have any idea of their strengths and weaknesses. The reader will be able to make an informed decision about which method to use in which context.
- Communicating data wirelessly has a lot of advantages, such as real time updates, less human hassly / error.
- Introduction to wireless communications. Explain the generic model of wireless communications showing the key components (e.g. base, ota waves, receiver) that are common to all.
- Show how Bluetooth implements the generic model
- Show how Wi-Fi implements the generic model
- Show how LoRa implements the generic model
- Table showing strengths and weaknesses of all 3 methods, with guidelines on when each is appropriate.
Chapter 7: Sending data via BluetoothChapter Goal: At the end of this chapter, the reader will able to send the sensor data to a mobile app through the Bluetooth, and understand how Bluetooth can be used to send data over a short distance.
- Programming the micro:bit to send data over Bluetooth UART (MakeCode is easy).
- Installing Bitty app.
- Pairing micro:bit with the Bitty app.
- Receiving data (only for visualize).
- Bitty - Show weather station sharing data with bitty.
Chapter 8: Sending data through WiFi using MQTTChapter Goal: After reading this chapter, the reader will be able to send the sensor data to the Ubidots dashboard through WiFi using MQTT, a lightweight messaging protocol. The reader will learn how to program the CW01 with MakeCode/MicroPython, Setting up the Ubidots dashboard to visualize data, triggering events with the Ubidots, and analyzing the relationship with temperature and humidity with a simple graph.
- What is WiFi?
- Explain difference with WiFi and Bluetooth on micro:bit - strengths and weaknesses of both.
- Explaining MQTT in simple terms
- Connecting micro:bit, BM11, IP01, and CW01 together using uBus connectors (can use the same setup used in the previous chapter).
- Preparing MakeCode with required packages that support CW01.
- Setting up Ubidots (creating an account, configuring the dashboard, etc.)
- Setting up HiveMQ, creating topics, etc.
- Programming and flashing micro:bit.
- Programming and flashing CW01
- Visualizing data with Ubidots
- Plotting temp with humidity (Can you see a relationship?).
- Triggering (sending an e-mail if the temperature is too high)
Chapter 9: Sending Data via LoRaChapter Goal: After completing this chapter, the reader will be able to build a simple LoRa network and use it to send the data collected by the weather station to the Ubidots IoT platform, visualizing, and analyzing data.
- Overview of XinaBox hardware for LoRa / may be others
- Connecting the micro:bit, RL0x, and BM01 together.
- Setting up the LoRa gateway
- Connecting the LoRa gateway with a WiFi/Cellular/LAN
- Programming with MakeCode / MicroPython, using any provides libraries
- Setting up Ubidots and creating a dashboard to visualizing data (if not, use The Things Network - TTN with any supported app to visualize the data.)
Chapter 10: Now we are ready to be data scientistsChapter Goal: We've spent a lot of time developing skills that are key to a data scientist, and this chapter will highlight those skills and give ideas about how they can / are used in everyday life. We'll also list the tools we've learned above and begin to talk about how they can be applied to useful projects that will address global warming.
- List out the skills that we have learned, measuring data, recording it, tabulating, charting and analysing.
- List out the tools we now have at our disposal - we know how to use sensors, how to store data and how to get it off the device into a tool we can use to tabulate, chart and perform actions on.
- We talk about limits of micro:bit - that it won't be able to handle a lot of stuff at once. That will be a constraint we'll have to work with.
- Identify real world examples of where similar tech to ours is used, break each down into the simple components we know: Weather forecasting, automatic street lamps, credit card transactions, GPS positioning, etc.
Chapter 11: Measuring the power consumption of a light bulbChapter Goal: The consumption of electricity is strongly related to GW. By following this chapter, the reader will be able to build a tool to measure the kilowatt-hours (power consumption) used by a light bulb. The reader will use micro:bit and SL01 to detect the presence of the light. The reader will write the code to calculate and display the kilowatts used by the light bulb with the wattage of the lamp and the elapsed time for lighting.
- Basics of power consumption/watts/ watt-hour, etc.
- Building the unit with micro:bit and SL01
- Creating the code with MakeCode (using running time block to calculate the elapsed time)
- Displaying the usage of kilowatt-hours on the OLED display or sending data to a cloud (will consider later)
- We can go deep by analyzing the peak time of the power consumption.
Chapter 12: Monitor Air Pollution LevelsChapter Goal: By following this chapter, the reader will be able to build a digital instrument to monitor the air quality which includes eCO2 (equivalent calculated carbon-dioxide), and TVOC (Total Volatile Organic Compound), alcohols, aldehydes, ketones, organic acids, amines, aliphatic and aromatic hydrocarbons. Then the reader will be able to identify the level of pollution in the air based on the air quality index (good, moderate, unhealthy for sensitive groups, unhealthy, very unhealthy, hazardous). No of pages: 20Sub - Topics:
- Introducing the air quality index.
- Building the project with XinaBox SG33 - VOC & eCO2 (CCS811).
- Programming the core
- Displaying useful information on the OLED display
- Optional (add buzzer or vibrator to indicate unhealthy or hazardous environments)
Chapter 13: Geotagging your Weather StationChapter Goal: Sensor data by itself is bland stuff. Associating it with a time and place gives more life to it, and your sensor data could become more socialized. By following this chapter, the reader will be able to add the geotagging feature to the weather station (Prerequisite: The weather station should have the ability to connect to the Internet with WiFi or through LoRa) using SN01 or similar GPS module. Then the reader will be able to send sensor data along with the time and location (lat/lon), and other useful GPS data to an IoT dashboard like Ubidots. Finally, the reader will view and analyze some interesting patterns of weather data with the locations.
- Introduction to the geotagging and explaining how important it is/trends, etc.
- Adding SN01 to an existing weather station project (in chapter 8 or 9).
- Programming the cores for getting GPS data too.
- Sending data to an IoT dashboard
- Viewing and analyzing data/ asking questions, etc.
Chapter 14: Measuring Noise Pollution on Your Way Chapter Goal: Measuring the sound level is an exciting topic today. Sounds above 85 dB are harmful, depending on how long and how often you are exposed to them. By following this chapter, the reader will be able to measure the sound level in different locations. The reader will be able to collect data, analyze, and identify the areas with a harmful level of sound pollution.
- Identifying the harmful areas
- Introduction to sound pollution and different sound levels
- Building the circuit with the SparkFun sound detector or similar thing: https://www.sparkfun.com/products/14262
- Programming the cores
- Gathering data
- Analyzing
Chapter 15: Beyond the micro:bitChapter Goal: By following this chapter, the reader will be able to rebuild the weather station by replacing the micro:bit with other microcontrollers that commonly available.
- Building the weather station with CC01 / maker.makecode, programming, sending data to an IoT dashboard.
- Building the weather station with CC01 / Arduino, programming, sending data to an IoT dashboard.
- Building the weather station with CC01 / Zerynth, programming, sending data to an IoT dashboard. Note - we'd want to use CW02 for this as it has a license on board.
- Building the weather station with Raspberry Pi, programming, sending data to an IoT dashboard.
Appendix AWe will also include following if we have enough time to complete this book on time.
- Sending micro:bit weather station into high altitude / low earth orbit.
- Sending a weather station to high altitude using a helium balloon.
- Sending a weather station to low earth orbit.
- Choosing a long-range communication technology (say LoRa)
- Setting up the ground station.
- Receiving, visualizing, comparing, analyzing sensor data
Using the Blynk to replace the UART terminal app (requires Arduino IDE and nRF5 support package for Arduino).
- Using a PIR sensor with micro:bit to turn on/off lights by detecting the presence of a human. Also when natural light is bright enough. Show how it can be used for a table lamp and consider completely novel applications (turn off music, lock a door).
- A project for monitoring water pollution.
