Complete Guide for Fingerprint Modules 2022

Many of the complex IoT projects in a wide range of applications like environmental, home automation, and robotics have witnessed the integration of fingerprint sensor modules. The increasing demand for a secure, fast, and cost-efficient method for identification has made it important to review some of the popular fingerprint modules in the market. This article will discuss the top 5 fingerprint sensor modules for your IoT projects that will help you enhance the user experience. 

We can realize the necessity for fingerprint modules through Crowdfunding projects like Chhavi. This ESP-32 based Arduino-compatible fingerprint sensor with optional NFC marked over 100% funding from the maker community. There has also been a shift from optical fingerprint modules towards capacitive fingerprint sensors which are tiny, accurate, and power-efficient for remote applications. 

The essential aspect of power efficiency is very important for it to be battery-controlled giving the user chance to take advantage of the compact form factor. However, not all fingerprint modules are designed for space-constraint applications, hence we are also featuring those looking for a decently sized with minimalistic design for access control system hobby projects. A few of the sensors in the market are also manufactured with the aim to save fingerprints for identification, comparison, and analysis in the flash memory of the system. This gives an overview of the advancements in the fingerprint sensor modules over the last few years.

What are Fingerprint Sensor Modules?

Fingerprint sensor modules are manufactured into two parts, one for fingerprint registration and another for matching purposes. The matching can be done 1:1 or 1:N depending on the purpose of the designed hardware. Once the user enters the finger for the registration, the system takes the image and generates a template based on the processed results, and stores the image. Once the unique fingerprint is stored in the onboard flash memory. The matching process starts with the user again entering the finger through the capacitive/optical fingerprint sensing area and will generate another template of the finger which is later used to compare with the pre-existing image from the library.

Sometimes, the hardware interface for such sensors can be challenging. But the innovation has made it easy for the manufacturers to provide easy hardware interface communication through UART or even USB in some cases. With some simple commands, the fingerprint sensor can be deployed in your hobby projects. The raw image of the fingerprint can also be retrieved from the sensor and used for other projects and applications. Let's take a look at our top 5 fingerprint sensors picks for your IoT projects. 

Top 5 Fingerprint Sensors for IoT Projects

1.SparkFun AD-103 Fingerprint Sensor Module


The first fingerprint sensor module in the list comes from SparkFun, which is a capacitive fingerprint scanner operating through the UART interface port for easy functionality. This AD-103 fingerprint sensor module is different from many of the sensors in the market because of its ability to read a fingerprint image by pixel array and deliver ridge or valley signals to the A/D converter and digital processor. This information is then carried to the serial peripheral interface for reading the data. The image resolution for the AD-103 fingerprint sensor is 508dpi and has a recognition time of less than 0.6 giving faster and accurate results. As mentioned earlier, the SparkFun AD-103 fingerprint sensor module is capable of storing up to 40 high-quality templates in the flash memory.

Specifications of SparkFun AD-103 Fingerprint Sensor Module

  • Type: Capacitive fingerprint sensor
  • Capacity: 40 fingerprints
  • Resolution: 508 dpi
  • Interface type: UART
  • Dimensions: 29x19.6x6.06 mm 
  • Supply voltage: 3.3V
  • Operating temperature: -20 to 70 C
  • Sensing area: 8x8 mm
  • Sensing array: 160x160 pixels
  • Recognition time: <0.6 second
  • False rejection rate: 6%
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2. SparkFun Fingerprint Scanner - TTL (GT-521F32)


For your access control projects, this fingerprint scanner is one of the best choices you can make. GT-521F32 fingerprint module communicates over the TTL serial communication enhancing the ease-to-use experience. The onboard 32-bit Arm Cortex M3 processors integrated with the optical sensor provide the capabilities to read and identify fingerprints. Even this fingerprint scanner has the ability to store different fingerprints which can be stored and downloaded for other applications. Unlike the previous fingerprint sensor modules, the SparkFun GT-521F32 fingerprint module can store up to 200 unique fingerprints with an image resolution of 450dpi and a false rejection rate of <0.1%.

Specifications of SparkFun GT-521F32 Fingerprint Module

  • Type: Fingerprint Scanner (Optical Sensor)
  • Capacity: 200 fingerprints
  • CPU: Arm Cortex M3 Core
  • Resolution: 450 dpi
  • Interface type: UART and USB
  • Dimensions: 36.1x21x9.39 mm 
  • Supply voltage: 3.3 to 6V
  • Sensing area: 16.9x12.9 mm
  • Sensing array:258x202 pixels
  • Recognition time: <1.5 second
  • False rejection rate: <0.1%
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3. Seeed Studio’s Grove - Fingerprint Sensor


The Grove modules are famous series of sensors from Seeed Studio that cater to the increasing demand for various sensors and easy interfacing. This Seeed Studio’s grove fingerprint sensor is an optical fingerprint module that can detect and verify unique fingerprints with ease. The onboard DSP chip AS601 does maximum of the processing on the image like rendering, calculation, featuring identification and search. With the onboard flash memory, the sensor can store up to 162 fingerprints which can be later used for identification purposes. The false rejection rate of 1% makes it a good fingerprint sensor module you can consider purchasing for your next project.

Specifications of Seeed Studio’s Grove Fingerprint Sensor:

  • Type: Optical Fingerprint Sensor
  • Capacity: 162 fingerprints
  • CPU:  DSP AS601 chip
  • Interface type: UART
  • Dimensions: 110x65x21 mm 
  • Supply voltage: 3.3 to 6V
  • Recognition time: 1.0 second
  • False rejection rate: <1.0%
  • Operating temperature: -20 to 50 C
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4. Adafruit Fingerprint Sensor


Yet another optical fingerprint sensor for detection and verification based on a DSP chip. This Adafruit fingerprint sensor communicates with the TTL series that sends a packet of data to capture photos and detect fingerprints. Same as the Seeed Studio’s fingerprint module, even this is capable of storing up to 162 fingerprints on the onboard flash memory. The difference this module brings in is the support for Windows software for testing and deployment. Even though the datasheet for this module is not available, the manufacturers have provided an Arduino and CircuitPython library. 

Specification of Adafruit Fingerprint Module:

  • Type: Optical Fingerprint Sensor
  • Capacity: 162 fingerprints
  • CPU: DSP chip
  • Interface type: TTL Serial
  • Dimensions: 56x20x21.5 mm 
  • Supply voltage: 3.3 to 6V
  • Sensing area: 14x18 mm
  • Recognition time: <1.0 second
  • False rejection rate: <1.0%
  • Operating temperature: -20 to 50 C
  • Weight: 20 grams
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5. DFRobot Gravity Capacitive Fingerprint Sensor


Finally, we would like to introduce DFRobot Gravity capacitive fingerprint sensor, designed for fingerprint collection, processing, storing, and comparing. All the heavy workload is done by the onboard ID809 high-performance processor core that comes with the built-in IDfinger6.0 fingerprint algorithms. This has enabled fingerprint recognition independently without the assistance of any other subsystem. The support for 360-degree arbitrary angle recognition and deep self-learning function along with high-performance and low-power consumption makes it a good choice for remote applications. The ability to work alongside microcontrollers like Arduino UNO, micro:bit and many more.

Specification of DFRobot Gravity Capacitive Fingerprint Sensor Module

  • Type: Capacitive Fingerprint Sensor
  • Capacity: 80 fingerprints
  • CPU: ID809 high-performance processor core
  • Resolution: 508 dpi
  • Interface type: I2C
  • Dimensions: 22.5x32 mm 
  • Supply voltage: 3.3 to 5V
  • Sensing area: 8x8 mm
  • Sensing array: 160x160 pixels
  • Recognition time: <300-400 microsecond
  • Operating temperature: -40 to 60 C
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Final Thoughts on the Integration of Fingerprint Sensors

If you are reading this, it is likely that you are looking for some easy-to-use fingerprint sensor modules for your next IoT project. The importance of integrating low-power, compact and accurate fingerprint sensors has increased over recent times. Depending on your application, consider buying any one of the above-mentioned fingerprint sensors.

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