C1001 mmWave Human detection Sensor with ESP32, Life, Fall, & Sleep Detection

The C1001 mmWave Human Detection Sensor by DFRobot is a revolutionary technology that outperforms traditional PIR sensors and other human body detection sensors. Operating at a 60GHz millimeter-wave frequency, it brings unparalleled accuracy in detecting human presence, movement, and even static postures. Unlike standard 24GHz millimeter-wave radars, which only measure speed, distance, and presence, the C1001 mmWave sensor offers advanced functionalities such as life detection, fall detection, sleep monitoring, and human posture recognition.

In this article, we will explore how to use the C1001 mmWave sensor with ESP32, its technical capabilities, installation process, interfacing, and real-world applications. Finally, we will provide testing examples to ensure smooth functionality.

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Why C1001 mmWave Sensor is Superior to PIR Sensors

Traditional PIR (Passive Infrared) sensors have significant limitations, especially in applications where human movement is minimal. For instance:

• PIR sensors require movement to detect a human presence. If a person remains still, the sensor fails to detect them.
• Limited range and unreliable detection in spaces such as bathrooms, public restrooms, and outdoor environments.
• Frequent false triggers due to heat variations in the surroundings.

In contrast, the C1001 mmWave Human Detection Sensor solves these issues:

✅ Detects a person even when they are completely still.
✅ Provides accurate sleep monitoring, including breathing and heart rate tracking.
✅ Detects falls with precision.
✅ Works efficiently in enclosed spaces and public areas.

Advanced Features of the C1001 mmWave Sensor

1. Posture Recognition: Uses point cloud imaging algorithm to identify if a person is lying down.
2. Life Detection: Tracks how long a person remains in one place.
3. Fall Detection: Recognizes when a person falls and remains motionless.
4. Human Presence Detection: Works without requiring movement, making it ideal for security and automation.
5. Sleep Monitoring: Records sleep states, breathing rate, and heart rate.
6. Healthcare Applications: Provides sleep scoring and integrates with health monitoring systems.

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Installation Modes: Fall Detection vs. Sleep Monitoring

1. Fall Detection Mode (Top Load Installation)

• Coverage: 100° horizontal and vertical angles (3D sector area).
• Positioning: Mount the sensor 2–3 meters above the ground, tilted downward at 30–45° (see diagram below).
• Use Case: Ideal for living rooms, hospitals, or elderly care facilities to detect falls.

2. Sleep Monitoring Mode

• Coverage: Narrower 40° horizontal and vertical beam.
• Positioning:
  • Place the sensor 1.5 meters away from the subject, facing the chest.
  • Ensure no obstructions between the radar and the person.
• Functionality: Monitors breathing, heartbeat, and generates sleep quality reports.

3. Radar Orientation & Tilt Installation

• The emitting side should face the target area.
• Tilt angle: 30° – 45° downward for best accuracy

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C1001 mmWave Sensor Pinout

Pin	Function
VIN	Power Supply (3.3V-5V)
GND	Ground Connection
RX	Serial Communication Receive
TX	Serial Communication Transmit
IO1	Human Presence Status Output (3.3V)
IO2	Fall Status Output (3.3V)

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Interfacing C1001 mmWave Sensor with ESP32 Circuit Diagram

Connections:

1. VIN (Sensor) to 5V (ESP32)
2. GND (Sensor) to GND (ESP32)
3. RX (Sensor) to GPIO17 (ESP32)
4. TX (Sensor) to GPIO16 (ESP32)

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Programming and Coding C1001 mmWave sensor

First step is to download Arduino IDE and Install it on your PC, You can follow our guide:How to Install Arduino IDE on Your PC

Next we need to download a library named  DFRobot_HumanDetection and install it in the libraries folder of Arduino IDE.

Download link to the library DFRobot_HumanDetection: Here

After Downloading Open ArduinoIDE -> Sketch -> Include Library -> Add .zip Library -> Choose the downloaded zip file to install the library.

Code:

You can check the examples from the library by just following the below image. You can customize them with the pin numbers of ESP32, selecting the modes and more.

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Code explanation of Basic code from the examples

This code configures the C1001 mmWave sensor with an ESP32 to detect human presence, movement, breathing, and heart rate in Sleep Mode. Here’s a breakdown:

1. Setup Phase

• Serial Communication: Starts at 115200 baud. ESP32 uses pins 16 (TX) and 17 (RX) for sensor communication.
• Sensor Initialization:
  • hu.begin(): Initializes the sensor. Retries on failure.
  • hu.configWorkMode(hu.eSleepMode): Sets the sensor to Sleep Mode (for breathing/heart rate tracking).
  • Checks and prints the active mode (Fall/Sleep).

2. LED Configuration

• hu.configLEDLight(hu.eHPLed, 1): Turns ON the “Human Presence” LED when someone is detected.
• hu.sensorRet(): Resets the sensor to apply settings.

3. Loop Phase (Repeating Checks)

• Human Presence:
  hu.smHumanData(hu.eHumanPresence) → Returns 1 (person detected) or 0 (no one).
• Movement Status:
  hu.smHumanData(hu.eHumanMovement) → 0 (no motion), 1 (still), 2 (active).
• Body Movement Range:
  hu.smHumanData(hu.eHumanMovingRange) → Numeric value (0–1000) indicating motion intensity.
• Vital Signs:
  • hu.getBreatheValue() → Respiration rate (breaths per minute).
  • hu.getHeartRate() → Heart rate (beats per minute).

Key Output

The Serial Monitor displays:

Existing information: Someone is present  
Motion information: Still  
Body movement parameters: 150  
Respiration rate: 16  
Heart rate: 72  
-----------------------

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Code explanation of fall code from the examples

This code configures the C1001 sensor with an ESP32 specifically for Fall Detection Mode, optimizing parameters like sensitivity, delays, and installation height. Here’s a breakdown:

1. Setup Phase

A. Serial Communication

• Serial.begin(115200): Starts the debug monitor.
• Serial1.begin(...): For ESP32, configures hardware serial pins D3 (RX) and D2 (TX) at 115200 baud. Other boards use default Serial1.

B. Sensor Initialization

• hu.begin(): Initializes the sensor. Retries every 1 second if it fails.
• hu.configWorkMode(hu.eFallingMode): Switches the sensor to Fall Detection Mode (horizontal coverage: 100°, vertical: 100°).

2. Fall Detection Configuration

• LEDs:

  • hu.configLEDLight(hu.eHPLed, 1): Turns ON the “Human Presence” LED.
  • hu.configLEDLight(hu.eFALLLed, 1): Turns ON the “Fall Detected” LED.

• Installation Settings:

  • hu.dmInstallHeight(270): Sets sensor height to 270 cm (adjust based on ceiling/placement).
  • hu.dmFallTime(5): Triggers a fall alert 5 seconds after detection (avoids false alarms).
  • hu.dmUnmannedTime(1): Waits 1 second after a person leaves to report “no one present.”
  • hu.dmFallConfig(hu.eResidenceTime, 200): Flags “stationary dwell” if a person stays still for 200 seconds.
  • hu.dmFallConfig(hu.eFallSensitivityC, 3): Sets fall sensitivity to maximum (3).

Sensor Reset

• hu.sensorRet(): Applies all settings.

3. Loop Phase (Continuous Monitoring)

The sensor checks and prints these metrics every 1 second:

1. Human Presence:
   hu.smHumanData(hu.eHumanPresence) → 1 (detected) or 0 (not detected).
2. Movement Status:
   hu.smHumanData(hu.eHumanMovement) → 0 (no motion), 1 (still), 2 (active).
3. Body Movement Range:
   hu.smHumanData(hu.eHumanMovingRange) → Motion intensity (0–1000).
4. Fall Status:
   hu.getFallData(hu.eFallState) → 1 (fall detected) or 0 (no fall).
5. Stationary Dwell:
   hu.getFallData(hu.estaticResidencyState) → 1 (person idle for 200+ seconds).

4. Serial Monitor Output

Existing information: Someone is present  
Motion information: Active  
Body movement parameters: 780  
Fall status: Not fallen  
Stationary dwell status: No stationary dwell  
-----------------------

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Code explanation of sleep code from the examples

This code configures the C1001 mmWave sensor with an ESP32 for Sleep Detection Mode, enabling advanced sleep tracking, vital sign monitoring, and sleep quality analysis. Here’s a detailed breakdown:

1. Setup Phase

A. Serial Communication

• Serial.begin(115200): Initializes the debug serial monitor.
• Serial1.begin(...): For ESP32, configures hardware serial pins D3 (RX) and D2 (TX). Other boards use default Serial1.

B. Sensor Initialization

• hu.begin(): Initializes the sensor. Retries every 1 second if initialization fails.
• hu.configWorkMode(hu.eSleepMode): Sets the sensor to Sleep Mode (narrow 40° beam for precise bed monitoring).

C. LED Configuration

• hu.configLEDLight(hu.eHPLed, 1): Turns ON the “Human Presence” LED when someone is detected.
• hu.sensorRet(): Resets the sensor to apply settings.

2. Loop Phase (Continuous Sleep Monitoring)

The sensor collects and prints the following data every 1 second:

A. Basic Sleep Metrics

1. Bed Entry Status:
   hu.smSleepData(hu.eInOrNotInBed) → 0 (out of bed), 1 (in bed).
2. Sleep State:
   hu.smSleepData(hu.eSleepState) →
   • 0: Deep sleep
   • 1: Light sleep
   • 2: Awake
   • 3: No sleep detected
3. Durations:
   • hu.smSleepData(hu.eWakeDuration): Time awake (seconds).
   • hu.smSleepData(hu.eDeepSleepDuration): Time in deep sleep (seconds).
4. Sleep Quality Score:
   hu.smSleepData(hu.eSleepQuality): Score (0–100) based on sleep patterns.

B. Comprehensive Sleep Data

Retrieved via sSleepComposite comprehensiveState = hu.getSleepComposite():

• Average Respiration/Heart Rate:
  comprehensiveState.averageRespiration and averageHeartbeat.
• Body Movements:
  • turnoverNumber: Times the person turned in bed.
  • largeBodyMove/minorBodyMove: Proportion of significant/minor movements.
• Apnea Events:
  apneaEvents: Number of breathing pauses detected.

C. Sleep Abnormalities

• hu.smSleepData(hu.eSleepDisturbances): Flags issues like:
  • 0: Sleep < 4 hours
  • 1: Sleep > 12 hours
  • 2: Prolonged absence
  • 3: No issues

D. Sleep Statistics

Retrieved via sSleepStatistics statistics = hu.getSleepStatistics():

• Sleep Time Distribution:
  shallowSleepPercentage, deepSleepPercentage, timeOutOfBed.
• Vitals:
  averageRespiration, averageHeartbeat.
• Behavior Metrics:
  exitCount (times out of bed), turnOverCount (turns in bed).

E. Sleep Quality Rating

hu.smSleepData(hu.eSleepQualityRating):

• 1: Good
• 2: Average
• 3: Poor

F. Struggle Detection

hu.smSleepData(hu.eAbnormalStruggle):

• 2: Abnormal movements (e.g., seizures, distress).

Example Serial Output:

Bed entry status: In bed  
Sleep status: Deep sleep  
Awake duration: 120  
Deep sleep duration: 3600  
Sleep quality score: 85  
Comprehensive sleep status:{  
    Existence status: Someone is present  
    Sleep status: Deep sleep  
    Average respiration rate: 14  
    Average heart rate: 68  
    Number of turns: 5  
    Proportion of significant body movement: 10%  
    Proportion of minor body movement: 25%  
    Number of apneas: 0  
}  
Sleep abnormalities: None  
Sleep quality rating: Good sleep quality  
Abnormal struggle status: None

Key Use Cases

1. Smart Beds: Automate lighting/AC based on sleep stages.
2. Healthcare: Track sleep apnea, insomnia, or irregular heartbeats.
3. Elderly Monitoring: Detect falls or prolonged bed exits.
4. Fitness: Optimize recovery by analyzing deep sleep duration.

This code transforms the C1001 into a clinical-grade sleep monitor, providing actionable insights for health and automation systems.

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Conclusion

The C1001 mmWave Human Detection Sensor is a groundbreaking technology that surpasses PIR sensors in accuracy and versatility. Whether for home automation, security, healthcare, or sleep monitoring, this sensor provides reliable, real-time human presence detection. With ESP32 integration, it opens up endless possibilities for IoT-based automation and AI-driven applications.