on 2025-06-27 5:19 AM
Human activity recognition (HAR) is a crucial aspect of wearable technology, enabling the classification of various physical activities such as sitting, standing, running, and walking. STMicroelectronics offers a solution for HAR using the machine learning core (MLC). It's integrated into the smart MEMS sensor LSM6DSV16X, available on the SensorTile.box PRO board kit. For wireless tracking, the ST AIoT Craft mobile app, available both on Google Play Store and Apple Store, can be used.
To begin, click on the human activity recognition project available inside the project examples. A pop-up window appears with a brief description, as shown in Figure 1.
Next, click on the three vertical dots next to the [Try out] button and select [View details].
This reveals that the project uses a single AI model named human_activity_recognition, targeting the SensorTile.box PRO and the IMU LSM6DSV16X with a machine learning core. The model classifies data into four categories: running, walking, standing, and sitting.
You can evaluate the AI model either through the web application or via the mobile app. If you choose the mobile app, QR codes for installation are provided.
Figure 3: Choose your environment: either Web browser or ST AIoT Craft mobile app
For now, let's focus on evaluating the AI model directly on the web application using the SensorTile.box PRO.
Click the [Start] button to begin evaluating the AI model. The SensorTile.box PRO recognizes the following states based on its placement and movement:
To end the evaluation, click the [Stop] button.
You can effectively classify the state of your activity using the human activity recognition project example on the ST AIoT Craft platform: share your experience!
Create your own solution exploring the "My datasets" section and the "My projects" section.
Figure 5: Explore My datasets and My Projects sections
Stay tuned for more insights on how to leverage ST AIoT Craft for your projects!