Information
Table Of Contents
- A. Overview
- 1. Getting started
- 1.1 The BME688 Gas Sensor
- 1.2 Example: Coffee vs. Normal Air
- 1.3 A Few Things To Keep In Mind
- 1.4 Step 1: Record Normal Air
- 1.5 Step 2: Record Espresso Coffee
- 1.6 Step 3: Record Normal Air Again
- 1.7 Step 4: Record Filter Coffee
- 1.8 Step 5: Import & Label The Data
- 1.9 Step 6: Create New Algorithm and Classes
- 1.10 Step 7: Train And Evaluate The Algorithm
- 1.11 Step 8: Export The Algorithm
- 1.12 Conclusion
- 2. Introduction
- 2.1 What is it about? – An analogy
- 2.2 Why the BME688?
- 2.3 What is a use case for a gas sensor?
- 2.4 What is special about the BME688 gas sensor?
- 2.5 How can I evaluate BME688 performance for a specific use case?
- 2.6 How can I use the results for my product development?
- 3. Glossary
- 3.1 Sensor Board
- 3.2 Measurement Session
- 3.3 Algorithm
- B. Process Steps
- 1. Configure Board
- 1.1 Overview
- 1.2 Board Type
- 1.3 Board Mode
- 1.4 Heater Profile
- 1.5 Duty Cycle
- 1.6 Board Layout
- 2. Record Data
- 2.1 Overview
- 2.2 Start recording
- 2.3 During recording
- 2.4 End recording
- 3. Import Data
- 3.1 Overview
- 3.2 Data Overview
- 3.3 Board ID
- 3.4 Board Type
- 3.5 Board Mode
- 3.6 Session Name
- 3.7 Session Date
- 3.8 Specimen Data
- 4. Collect Specimens
- 4.1 Overview
- 4.2 Label
- 4.3 Comment
- 4.4 Session
- 4.5 Start & End Time
- 4.6 Duration
- 4.7 Cycles Total
- 4.8 Cycles Dropped
- 4.9 Remaining Cycles
- 4.10 Board Configuration
- 4.11 Board ID
- 4.12 Board Type
- 4.13 Board Mode
- 4.14 Show Configuration
- 5. Train Algorithms
- 5.1 Overview
- 5.2 Name
- 5.3 Created
- 5.4 Classes
- 5.5 Class Name & Color
- 5.6 Common Data
- 5.7 Data Balance
- 5.8 Data Channels
- 5.9 Neural Net
- 5.10 Training Method
- 5.11 Max. Training Rounds
- 5.12 Data Splitting
- 6. Evaluate Algorithms
- 6.1 Overview
- 6.2 Confusion Matrix
- 6.3 Accuracy
- 6.4 Macro-averaged F1 Score
- 6.5 Macro-averaged False Positive Rate
- 6.6 Training Data
- 6.7 Test Data
- 6.8 Additional Testing
- 2.1
Bosch Sensortec | BME AI-Studio Documentation 32 | 49
Modifications reserved | Data subject to change
without notice Document number: BST-BME688-AN001-00
3.3 Board ID
This indicates which BME board has been used to record the data. Each board has a unique ID that is permanently
stored on the board itself, which makes it uniquely identifiable.
3.4 Board Type
This indicates the type of BME board used to record the data.
3.5 Board Mode
This indicates the board mode in which the BME board was configured in when used to record the data.
3.6 Session Name
Give your measurement session a name – this could be a topic, a specific location or special occasion. Choose your
session name in a way that helps you identify and distinguish your measurement session later on.
3.7 Session Date
This indicates the date and time the measurement session has been recorded. Within the raw data, the time information
is stored in Coordinated Universal Time (UTC) and is here automatically displayed in your respective local time zone.
You can manually overwrite the time information if needed.
Start date
The time the BME board was powered on.
End date
The time the BME board was powered off.
Please note
If your BME board lost its time information (e.g. if you disconnected the battery of BME board x8), the date and time of
the measurement session will always be January 1, 1970 by default. In this case, please overwrite the date and time
with the actual correct date and time of your measurement.
3.8 Specimen Data
This section gives you a visual representation (data plot) of the measurement raw data and an overview of the specimens
in this session.
Specimens within a measurement session reflect what you have measured during that session. This can be an object,
a specific situation, a smell, gas, etc. – or in other words: one specific gas composition the sensors on the BME board
were exposed to during the measurement.
Defined specimens are shown in the data plot as well as a list below.