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A biometric sensor is a transducer that changes a biometric treat of a person into an electrical signal. It is an automated method of identifying a person or verifying the identity of a person based on a physiological or behavioral characteristic.
Description: Fingerprint scanners are awesome. Why use a key when you have one right at the tip of your finger? Unfortunately, they’re usually unreliable or difficult to implement. Well not anymore! We’ve found this great fingerprint module from ADH-Tech that communicates over TTL Serial so you can easily embed it into your next project.
A Color-Coded Cable, with a standard male header connectors. Plug it straight into an Arduino or a Breadboard. No soldering is required. The Pulse Sensor has 3 holes around the outside edge which make it easy to sew it into almost anything. Visualization software (made in Processing) to instantly see the output of the sensor and for troubleshooting....
Low current consumption (typical 30 mA) CW or pulse operation Flat profile Long detection range (20 m) Supply voltage: 4.75V to 5.25V X-Band Frequency: 10.525 GHz Minimum Power Output: 13 dBm EIRP. RoboticsBD
Features: Built-in Red, IR, and Green LEDs 5V operation (3.3V is allowed, but green LED is not guaranteed to operate) Applications include presence detection, distance sensing (18" max), pulse oximetry, blood oxygen saturation level (SpO2), smoke and particle detection Documents: Schematic Eagle Files Hookup Guide Datasheet (MAX30105) MAX3010x Sensor...
Supply Voltage: 4.5 – 5.5 V. Current : <40 mA. Digital Interface : 5V TTL level for UART interface and GPIO. Support maximum 80 voice commands, with each voice 1500ms (one or two words speaking). Maximum 7 voice commands effective at same time. Arduino library is supplied. User-control General Pin Output. RoboticsBD
Supply voltage: DC 3.6 ~ 6.0V / 3.3V Supplying Supply Current: Current: <120mA Peak current: <140mA Fingerprint image time: <1.0 seconds
Description: Fingerprint scanners are awesome. Why use a key when you have one right at the tip of your finger? Unfortunately, they're usually unreliable or difficult to implement. Well not anymore! We've found this great fingerprint module from ADH-Tech that communicates over TTL Serial so you can easily embed it into your next project.
Transmission signal processing control chip RCWL-9196 Wide operating voltage range 4.0V to 28.0V Penetrating detection capability, compared with the traditional infrared feeling PIR Adjustable Block time and distance Operating Current: 2.8mA (typical); 3mA (max) Detection Distance: 5-9m Transmitting Power: 20mW (typical); 30mW (max) RoboticsBD
Power supply voltage(VCC): 2.0, 3, 5.5 V. Output high VOH: 0.8VCC V Output low VOL: 0.3VCC V Response time (touch mode) : 60 mS Response time (low power mode) : 220 mS Can replace the traditional touch of a button Four M2 screws positioning holes for easy installation RoboticsBD
Based on MAX30105 – heart rate, oximeter, smoke sensor Green, red, and infra-red LEDs Interface: I2C (address 0x57) Compatible with 3.3V and 5V logic levels.
TTP223 Capacitive Touch switch Digital Touch Sensor Module for Arduino UNO DUE MEGA TTP223 capacitive touch single IC. Onboard level indicator. Working voltage: 2.0V to 5.5V.
Onboard 8 key TTP226 capacitive touch induction IC. RoboticsBD Onboard 8-way level indicator. Working voltage: 2.4 to 5.5 V. Modules, you can set the output mode, key output mode, the longest time and fast/low power output
Arduino TTP229 16 Channel Digital Capacitive Switch Touch Sensor Module GM
FPC1020A is a secondary development module for fingerprint recognition designed for SCM. Fingerprint identification capacity: 150 fingerprints, identification time is less than 1 second, can be customized large capacity Capacitive surface array semiconductor fingerprint sensor Support finger 360 rotation recognition Supported Operating Systems: Windows
Fastest fingerprint identification in the world, Support multi fingerprint Instant match.
HuskyLens is an easy-to-use AI machine vision sensor. It is equipped with multiple functions, such as face recognition, object tracking, object recognition, line tracking, color recognition, and tag(QR code) recognition.