Data Annotation and labellisation on t6 IoT framework
Data classification and annotation is a new implemented module on the t6 Api. This new process provides annotation on any datapoints and/or range of datapoints with ease. Annotation on t6 is the process of classifying datapoints — with a customizable category.
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The following 2 modes are available:
- Hand labeling for a strong and accurate supervision;
- Programmatic labeling for a weak supervision. This automatic process is using the t6 Rules, and so, it can combine multiple criteria before annotating to the correct category.
Categories for Data Annotation
Data annotation in the t6 IoT platform allows Users to assign custom categories (tags) to their data, providing valuable context and insights. Users have the flexibility to define and customize multiple categories based on their specific requirements. For example, imagine you’re monitoring vehicle speed (m/s) within a t6 Flows. With data annotation, you can create rules that automatically label datapoints with categories such as “slow” or “fast” based on predefined speed thresholds inside Rule.
This process using Rules is weak as it involve a programmatic pattern to identify the category.
An alternative process — hand-annotation can be used in parallel to associate categories to datapoints. This association can use a single datapoint or a range of dates.
Hand Labeling vs. Programmatic Labeling
There are two primary modes for data labeling in t6:
- Hand Labeling: This mode involves manual annotation, where users directly associate categories with datapoints. Hand labeling offers strong supervision and accuracy, making it ideal for cases where precise labeling is required.
- Programmatic Labeling: In contrast, programmatic labeling utilizes t6 Rules to automatically assign categories to datapoints. This method relies on predefined criteria within the rules engine to identify and label datapoints. Programmatic labeling provides a form of weak supervision, as it relies on programmatic patterns rather than manual intervention.
Why are we using labellisation on t6 ? A smooth startpoint to progress on the data-first approach.
Labellisation is the initial step to craft AI on t6 platform. As Data is centric on t6, the team expect this new feature to become a real north star and bring new opportunities to the users.
Utilizing Rules for Annotation
When using programmatic labeling, users can leverage t6 Rules to define complex criteria for category assignment. Rules can combine multiple conditions, allowing for sophisticated annotation logic. For example, a rule could trigger category annotation based on various sensor readings, timestamps, or other contextual information.
Api documentation — further reading:
- Technical Doc: https://doc.internetcollaboratif.info/#api-11._Classification
- Functionnal documentation
- Additional documentation about Data-Acquisition Preprocessor & Data Fusion
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