Advance Human presence and fall detection using ESP32

In the world of human detection technology, traditional sensors like Passive Infrared (PIR) and 24GHz millimeter-wave (mmWave) sensors have long been used to detect movement, speed, and distance. However, these conventional solutions have limitations, particularly when detecting human presence without motion. Enter the dfrobot C1001 mmWave Human Detection Sensor, a cutting-edge 60GHz millimeter-wave radar sensor designed to revolutionize human monitoring.

Beyond Traditional Detection: The Power of 60GHz mmWave

Unlike its 24GHz predecessors, which primarily detect basic movement parameters, the C1001 sensor goes several steps further. Leveraging high-precision mmWave technology, it provides advanced capabilities such as:

• Presence Detection: Identifies human presence even when a person remains completely still.

• Fall Detection: Monitors postures to detect whether someone has fallen, which is critical for elderly care and medical applications.

• Sleep Monitoring: Tracks sleep patterns and body postures using point cloud imaging algorithms.

• Life Sign Monitoring: Detects minor body movements, including breathing and micro-movements, for accurate physiological monitoring.

Why C1001 Outperforms PIR Sensors

One of the major drawbacks of Passive Infrared (PIR) sensors is their reliance on motion. PIR sensors cannot detect static individuals, making them ineffective for applications like elderly monitoring, security, or smart home automation where motionless detection is crucial. The C1001 mmWave sensor, on the other hand, ensures accurate detection even when a person remains still, providing uninterrupted monitoring and improved security.

ESP32 Implementation: Web-Based Human Detection

To demonstrate the capabilities of the C1001 mmWave sensor, an ESP32-based web server has been developed using the Arduino platform. This webserver allows real-time monitoring of human presence and fall detection directly through a browser. The ESP32 fetches sensor data and updates the web interface, displaying:

• Live presence detection status

• Fall alerts

The webserver runs on ESP32, processing data from the C1001 sensor and presenting it in an intuitive interface accessible via Wi-Fi. The Arduino code for this implementation reads sensor values, processes them, and serves the results through an embedded web application.

Source Code

 

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