I’m explaining for information about image/identification sensors in wearable devices. These sensors capture images or videos of the surrounding environment, the user’s body, or clothing being worn and extract information from them. Going beyond simply acquiring visual information, they play a crucial role in implementing various functions such as object recognition, face recognition, motion recognition, and health status analysis, especially when combined with AI technology. Let’s explore the main types and their applications in detail.

1. Camera Sensors:

• These are the most representative image sensors, converting light entering through a lens into images or videos.
• Types:
  • CMOS Image Sensors: These are currently the most commonly used sensors in wearable devices, offering low power consumption and easy miniaturization.
  • RGB Sensors: Measure the intensity of red, green, and blue light to obtain color information.
  • Depth Sensors: Measure the distance to an object to obtain 3D information.
• Applications:
  • Photo and Video Shooting: Equipped in smartwatches, smart glasses, etc., to capture photos or videos.
  • Object Recognition: Used to recognize surrounding objects and provide information or implement AR (Augmented Reality) features.
  • Face Recognition: Used for user identification, unlocking, etc.
  • Motion Recognition: Used to recognize user movements for activity tracking, gesture control, etc.
  • Health Status Analysis: Can be used for skin condition analysis, posture analysis, etc.

2. Biometric Sensors:

• These sensors identify individuals using their biometric information.
• Types:
  • Fingerprint Sensors: Acquire fingerprint patterns in image form to identify users.
  • Iris Recognition Sensors: Acquire the unique patterns of the iris in image form to identify users.
  • Vein Recognition Sensors: Capture vein patterns on the back of the hand or fingers using infrared cameras to identify users.
• Applications:
  • User Authentication and Unlocking: Used to enhance the security of wearable devices.
  • Payments: Can be used as a user authentication method for convenient payments using wearable devices.
  • Access Control: Can be used to manage access rights to specific areas.

3. Other Identification Sensors:

• RFID/NFC Tags: These tags store and transmit information using radio frequency or near-field communication.
• Applications:
  • Item Identification and Tracking: Wearable devices can be used to track the location of items or perform inventory management.
  • Payments and Access Control: Functions such as transportation cards and access cards can be integrated into wearable devices.

Development Directions of Image/Identification Sensors:

• High Resolution and Low Power Consumption: Technology development is underway to obtain clearer images while reducing power consumption.
• Fusion with AI: As deep learning-based image recognition and analysis technologies advance, it is expected that more accurate and diverse information can be extracted.
• Sensor Fusion: Technology is being developed to provide more accurate and richer information by fusing information obtained from various types of sensors. For example, data from camera sensors and IMU (Inertial Measurement Unit) sensors can be fused to perform more accurate motion recognition.

In wearable devices, image/identification sensors go beyond simply acquiring visual information and play a crucial role in innovating the user experience and providing various services. With further advancements in technology, the possibilities for using wearable devices are expected to become even more limitless.

Hello! What is the actual use of image sensors in wearable devices?

I heard there are many other uses besides the camera function, so I’m curious.

Nice to meet you~ Yes, it actually has a variety of uses.

The most interesting thing is gesture recognition.

You can control the device by recognizing hand gestures. It is also used with optical sensors to unlock security with facial recognition or measure heart rates.

Recently, it is also used in healthcare such as skin condition analysis and UV measurement.

I’m a developer, what should I consider to process image sensor data from wearable devices in real time? I’m worried about battery consumption 😅

That’s a good question! Real-time image processing is definitely a battery-consuming task. Here are some tips:

Only activate the sensor when necessary and place it in sleep mode normally.
Use the image resolution as much as you need
It’s good to minimize cloud communication by utilizing Edge AI processing.
If possible, use a low-power processor to process images.
There are also many open-source libraries that can be helpful in actual development, so please refer to them!

How can I improve the accuracy of biometric image sensors on wearables?

Especially when I move, the recognition rate seems to decrease.

Motion correction is important! Wearables use these methods these days:

• Use multiple sensors at the same time to increase the reliability of your data
• Calibrate movement with acceleration sensor and gyro sensor
• It is also important to filter noise with AI algorithms and to guide users to “fix your wrist as much as possible during measurement.” It complements the technical limitations with UI/UX. 😊