Overview
Grove-Temperature & Humidity Sensor Pro is a high accuracy temperature and humidity sensor based on the DHT22 module (also known as AM2302 or RHT03). High-cost performance and high precision make it ideal for temperature and humidity monitoring of Arduino and Raspberry Pi, you can also use it to make a thermometer and hygrometer.
The DHT22 includes a capacitive humidity sensor and a high precision temperature sensor. The range of humidity sensor is 0 to 99.9 %RH with ±2% accuracy while the temperature sensor ranges from -40 to 80℃ with ±0.5℃ accuracy. With the help of a built-in 8-bit microcontroller, the DHT22 converts the analog output of those two sensors to the digital signal, and output both temperature and humidity data via a single pin.
Compared with the DHT11, this product has higher precision and wider measurement range, but the usage and code are almost the same. Simply put, if you need higher measurement accuracy, this product will be a better choice.
Tech specs
|
Item |
Min |
Norm |
Max |
Unit |
|
VCC |
3.3 |
- |
6 |
V |
|
Measuring Current Supply |
1 |
- |
1.5 |
mA |
|
Standby Current Supply |
40 |
- |
50 |
uA |
|
Measuring range (Humidity) |
5% |
- |
99% |
RH |
|
Measuring range (Temperature) |
-40 |
- |
80 |
°C |
|
Accuracy(Humidity) |
- |
- |
±2% |
RH |
|
Accuracy (Temperature) |
- |
- |
±0.5 |
°C |
|
Resolution (Humidity) |
- |
- |
0.1% |
RH |
|
Resolution (Temperature) |
- |
- |
0.1 |
°C |
|
Repeatability(Humidity) |
- |
- |
±0.3% |
RH |
|
Repeatability (Temperature) |
- |
- |
±0.2 |
°C |
|
Long-term Stability |
- |
- |
±0.5% |
RH/year |
|
Signal Collecting Period |
- |
2 |
- |
S |
|
Respond Time 1/e(63%) |
6 |
- |
20 |
S |
Get Inspired
VarSpeedServoRA4M1 is a library for Arduino that enables precise control over servo motors, including speed, position, and movement sequences.
In robotics and several other disciplines, PID (proportional-integral-derivative) control is a way for systems with closed-loop feedback to adjust themselves according to sensor data without overshooting the target. Drones, for example, use PID control to remain stable without wild oscillations caused by over-correction. But implementing PID control can feel overwhelming, so Adam Soileau from element14 Presents built a simple robot for some experimentation. This robot’s only job is to drive forward until it sees a wall, then stop at a specific distance from that wall. That isn’t hard to achieve when a robot is moving at slow pace, because the code can tell the robot to stop moving the moment it reaches the target distance. But when moving fast, the robot has to take braking acceleration into account and that is much harder to predict. PID control is perfect for this situation, because it adjusts motor output in real-time according to the incoming sensor data. In this case, that sensor data comes from an ultrasonic rangefinder mounted to the front of the 3D-printed robot. An Arduino UNO R4 Minima board receives that data and controls the robot’s two motors through H-bridge drivers. That hardware is very straightforward so that Soileau could focus on the PID control. Tuning that is all about balancing the three constant values to get the desired performance. Soileau spent some time working on the Arduino sketch to get the PID control integrated and was eventually able to make the robot act like it should. If you’re interested in using PID control in your next robotics project, then Soileau's video should help you get started.
