Overview
It can detect combustible Carbon Monoxide, Coal Gas and Liquefied Gas. The sensitivity can be adjusted by the potentiometer.
Hardware Overview
This is an Analog output sensor. It needs to be connected to any one Analog socket in Grove Base Shield. It is possible to connect the Grove module to Arduino directly by using jumper wires. When doing so, please refer to the connection table below:
|
Arduino |
Gas Sensor |
|
5V |
VCC |
|
GND |
GND |
|
NC |
NC |
|
Analog A0 |
SIG |
The output voltage from the Gas sensor increases when the concentration of gas. Sensitivity can be adjusted by rotating the potentiometer.
Please note that the best preheat time for the sensor is 24 hours and above.
Note: Hot-swapping the grove may lead to IC burnout, please turn off the power of main board before swapping grove.
Tech specs
Specification
|
Item |
Parameter |
Min |
Typical |
Max |
Unit |
|
VCC |
Working Voltage |
4.9 |
5 |
5.1 |
V |
|
PH |
Heating consumption |
0.5 |
- |
340 |
mW |
|
RL |
Load resistance |
adjustable |
|||
|
RH |
Heater resistance |
- |
33Ω±5% |
- |
Ω |
|
Rs |
Sensing Resistance |
2 |
- |
20000 |
Ω |
|
CO/CH4/LPG Scope |
Detecting Concentration |
200 |
- |
1000/10000/10000 |
ppm |
Technical Details
|
Dimensions |
130mm x 90mm x 23mm |
|
Weight |
G.W 15g |
Get Inspired
As Jallson Suryo discusses in his project, adding voice controls to our appliances typically involves an internet connection and a smart assistant device such as Amazon Alexa or Google Assistant. This means extra latency, security concerns, and increased expenses due to the additional hardware and bandwidth requirements. This is why he created a prototype based on an Arduino Nicla Voice that can provide power for up to four outlets using just a voice command. Suryo gathered a dataset by repeating the words “one," “two," “three," “four," “on," and “off” into his phone and then uploaded the recordings to an Edge Impulse project. From here, he split the files into individual words before rebalancing his dataset to ensure each label was equally represented. The classifier model was trained for keyword spotting and used Syntiant NDP120-optimal settings for voice to yield an accuracy of around 80%. Apart from the Nicla Voice, Suryo incorporated a Pro Micro board to handle switching the bank of relays on or off. When the Nicla Voice detects the relay number, such as “one” or “three," it then waits until the follow-up “on” or “off” keyword is detected. With both the number and state now known, it sends an I2C transmission to the accompanying Pro Micro which decodes the command and switches the correct relay. To see more about this voice-controlled power strip, be sure to check out Suryo’s Edge Impulse tutorial.
