Arduino flow rate sensor | Arduino: induction light | magnetic flow meter

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1.dht11、 How to do experiments with air sensors and heart rate sensors together? DHT11 temperature and humidity sensor, air sensor (taking MQ-135 as an example), and heart rate sensor (taking Pulse Sensor as an example) can be combined to build a comprehensive human and environmental health monitoring experimental platform. 1. Experimental core design: The combination of multi parameter health and environmental monitoring station can synchronously collect human physiological data (heart rate) and environmental data (temperature and humidity, air quality), suitable for studying the potential impact of environmental factors on human physiological indicators. 2. Hardware connection scheme (taking Arduino Uno as an example) All sensors need to be connected to the main control board. The recommended wiring method is as follows: | Sensor | Power pin | Signal pin | Arduino pin||----------------|----------|----------|-------------|| DHT11 | VCC (3.3V/5V) | DATA | D2 || MQ-135 | VCC (5V) | AOUT | A0 || Pulse Sensor | VCC (3.3V/5V) | SIGNAL | A1 || Public Ground Wire | GND | GND | GND | 3. Key Experimental Content 3.1 Basic Data Acquisition Experiment • Write separate programs to verify that each sensor works independently and obtain raw data: - DHT11: Temperature (℃), Humidity (% RH) - MQ-135: Analog Voltage Value (0-1023), which needs to be converted into specific gas concentration reference values (such as CO ₂ NH ∝, benzene) - Pulse Sensor: Simulate voltage waveforms and calculate real-time heart rate (BPM) through algorithms. 3.2 Environmental and physiological correlation analysis experiment • Synchronize monitoring and recording: When MQ-135 detects sudden changes in air quality (such as alcohol evaporation and smoke), observe whether there are corresponding changes in heart rate data • Analyze the potential impact of temperature and humidity changes (DHT11 data) on heart rate variability. 3.3 Threshold alarm system development • Set environmental parameter thresholds (such as temperature>30 ℃, MQ-135 value>300) or heart rate abnormality thresholds (100 BPM) • Trigger sound and light alarms or IoT module push warning messages. 4 Key points of data processing: MQ-135 needs to be preheated for about 5 minutes for stable readings and needs to be calibrated according to the target gas. Heart rate data needs to be processed with filtering algorithms (such as median filtering) to deal with signal noise and calculate BPM through peak detection algorithms. It is recommended to use Python or Node RED for multi-channel data visualization display Safety precautions • MQ-135 sensor generates heat during operation, avoid touching to avoid burns • Heart rate sensor should be correctly attached to the skin (usually finger cots or ear clips), avoiding direct sunlight to prevent interference with photoelectric volume measurement • The entire system is recommended to use an isolated power module to avoid direct contact with the circuit by the human body. 6 Expanding application directions • Smart home health monitoring system: integrated display of real-time environmental and health data • Athlete training environment monitoring: analyzing the heart rate response under different temperature, humidity, and air quality conditions • Elderly health care: monitoring heart rate trends for a long time and combining them with environmental abnormalities for timely alarm. Example code and specific calibration methods can be further pr

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