Hey, tech enthusiasts, we meet again! Pay attention—DigiKey’s new 2025 series 「Redefining the Present with AI」 videos are now live!
“Hello, Xiao Zhi.”
“Hi there, I’m Potato.
How’s your day going?” “Activate work mode.”
“Got it, work mode is on, and volume is turned up~”
This friendly conversation didn’t happen between people but between a person and a palm-sized circuit board. When AI cameras can call your name in real time, when sensors can predict if an elderly person is about to fall, when development boards enable voice control as easily as building blocks—we’re witnessing a “machine perception revolution,” and it’s open-source hardware players like DFRobot bringing this revolution within reach of ordinary people.
In the first episode of the series, DFRobot senior engineer Rockets Xia will explore: How is AI reshaping human perception? How does DFRobot’s hardware make AI innovation accessible beyond just experts?
-Featured Speaker:-
Rockets Xia(夏青), Senior Engineer at DFRobot and Co-founder of Maker Space Mushroom Cloud
Rockets Xia is an active figure in global maker communities. Since 2008, he has promoted maker culture and the growth of China’s maker movement. In 2010, he co-created China’s first maker space, XinCheJian, with “Godfather of Chinese Makers” David Li. In 2013, with support from DFRobot and Pujiang Group, he established Maker Space Mushroom Cloud. As a co-founder of Mushroom Cloud, he frequently encourages and advances community maker projects. As a senior engineer at DFRobot, he actively promotes the adoption of AI, IoT, and other advanced technologies in maker education.
From “Executing Commands” to “Active Thinking”: What Makes AI Main Control Boards So Special?
Those who have used traditional development boards know that a regular Arduino board is like an “obedient little assistant”: you tell it to turn on a light, and it conducts electricity; you command a motor to spin, and it drives the motor. But if you want it to “recognize” whether there’s a cat in a photo or “understand” a spoken dialect command, it’s completely clueless — this is the core difference between traditional development boards and AI main control boards.
DFRobot engineers define an “AI main control board” as an “optimized super brain” specifically designed for AI tasks. Its secrets lie in three areas:
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Built- in “AI accelerator”: For example, the FireBeetle 2 comes with an ESP32-S3 chip featuring a vector calculation extension module, enabling complex neural network models to run locally at high speeds. It’s like adding a dedicated graphics card to a computer, making image and voice processing speeds over 10 times faster than a standard MCU.
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“Massive memory” to store intelligence: The XingKong Board K10 is equipped with 8MB PSRAM, easily storing image frames and AI models. In contrast, the SRAM in traditional development boards is so small it can only handle simple data — like trying to store a movie on a USB drive, it just won’t fit.
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“Plug-and-play” smart interfaces: Cameras, microphones, and screens connect directly without complex wiring. For example, the XingKong Board M10 comes with a 2.8-inch screen, displaying recognition results instantly upon connection, whereas a regular development board might require soldering and power adjustments just to connect a camera — a major deterrent for beginners.
Most importantly, these “super brains” enable localized AI computation. When using the FireBeetle 2 with an OV2640 camera for face detection, the model runs directly on the board without relying on the cloud. Not only is the response speed as fast as milliseconds, but there’s also no worry about privacy data leaks — a must-have for smart homes, elderly monitoring, and similar scenarios.
The “evolution” of sensors : From “reporting data” to “thinking.”
If AI main control boards are the “brain,” then AI sensors are the “smart senses.” Traditional sensors are like dull messengers: temperature 26°C, humidity 87%, VOC 300 — they report the data and that’s it. Whether it’s the aroma of coffee or the sweetness of mangoes, they have no clue.
But DFRobot’s AI sensors have long evolved into “interpreters”:
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The SEN0305 HuskyLens visual module doesn’t just take photos—it can directly tell you “this is a cat” or “that’s a human face,” and even distinguish between different people;
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The SEN0609 millimeter-wave radar doesn’t just detect human presence—it can use point cloud algorithms to determine “whether this person is about to fall,” and even monitor subtle changes in breathing and heartbeat when the person is completely still;
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The BME688 smart gas sensor goes further by embedding AI models into hardware, able to sniff out whether it’s “coffee” or “alcohol.”
Behind these “smart senses” lies deep integration of hardware and algorithms. They come with built-in processors and pre-trained models, capable of completing the entire workflow from “data collection” to “decision-making” locally. Take the offline voice module, for example—it can understand “turn on the lights” without an internet connection and even respond with “lights on,” forming a complete interaction loop. This is practically a necessity in network-less mountainous areas or factories.
Choose the right tools, and the barrier to AI innovation drops by 80%.
Many think AI development is out of reach, but DFRobot’s open-source hardware is breaking down those barriers into “building blocks”:
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Starting from scratch? Begin with Arduino kits : 35 components + 30 illustrated lessons, from lighting an LED to controlling a servo, step by step to understand how sensors work. Don’t dismiss it as non-AI—it’s the “scaffolding” for building foundational skills.
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Want to quickly create smart projects? Go for the UNIHIKER K10: the graphical programming platform Mind+ lets you code like stacking blocks, making it easy even for students to build voice-controlled cars. With onboard cameras and screens, no extra accessories are needed.
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Working on IoT + AI? FireBeetle 2 is the top choice: Wi-Fi + Bluetooth dual-mode communication, low-power design extends battery life to six months, perfect for smart locks or environmental monitoring devices that need to run long-term.
What’s even better is that DFRobot’s ecosystem covers everything from beginner-friendly MicroPython to expert-level ESP-IDF development. Even if you want to customize neural network models, these hardware platforms can handle it—meaning whether it’s AI experiments in K-12 classrooms, makers’ wild ideas, or corporate prototyping, there’s a tool for every need.
The Future is Here: When “Smart” Becomes Standard
Today’s AI hardware is no longer a rarity confined to labs: In nursing homes, millimeter-wave radar monitors elderly falls 24/7; in farmlands, AI sensors distinguish “weeds from crops”; at home, voice-controlled smart lights understand your habits better than switches.
What DFRobot is doing is making this “smart” technology as simple as buying a screwdriver – no complex algorithms, no intricate circuit soldering, not even coding required, allowing ordinary people to participate in AI innovation.
This is just the first episode of the series. In upcoming episodes, we’ll uncover:
- From “Centralized Intelligence” to “Distributed Intelligence”: TinyML and Local Offline AI
- Multimodal Interactive Experiences: Exploring AI Applications like Speech Synthesis/Recognition and Image Recognition
- Expanding Human Perception Across Time and Space: AI+Environmental Monitoring Projects
If you want to build a “thinking” device yourself, start with a development board and a sensor – after all, world-changing innovations often hide in these accessible tools.
Join DFRobot in exploring AI – you might be the next to change the world! See you next time – don’t miss it~
Related Product Information:
DFR0992-EN UNIHIKER-K10
The UNIHIKER-K10 is a learning board specifically developed for programming education, IoT, and AI project teaching in information technology curricula. It integrates a camera, LCD color screen, microphone, speaker, WiFi/Bluetooth modules, RGB indicators, multiple sensors, and expansion interfaces – enabling sensor control, IoT applications, image detection, speech recognition, and speech synthesis projects without additional equipment.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-DFR0992-EN-ND
DFR0706-EN UNIHIKER-M10
The UNIHIKER-M10 is a highly integrated domestically-produced educational open-source hardware (with independent intellectual property), designed specifically for K12 teachers and students, meeting new curriculum standards for interdisciplinary teaching in information technology, physics, biology, and other subjects. Integrated single-board computer (4-core CPU/512MB RAM/16GB storage), Linux system, complete Python environment, pre-installed with common Python libraries, and comes with a 2.8-inch color touchscreen and rich sensors. Just two steps to start the Python teaching platform.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-DFR0706-EN-ND
DFR0975-U High-performance main control based on ESP32-S3, suitable for AIOT, image acquisition, and image recognition projects
FireBeetle 2 ESP32-S3-U is a main control board designed based on the ESP32-S3-WROOM-1U-N16R8 module. The ESP32-S3-WROOM-1U-N16R8 module features 16MB Flash and 8MB PSRAM, allowing for more code and data storage. The ESP32-S3 chip on the module has powerful neural network computing and signal processing capabilities, making it suitable for projects like image recognition and speech recognition.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-DFR0975-U-ND
DFR0100 Maker education starter learning kit, suitable for Arduino UNO R3 development board and electronics beginners
The Arduino starter kit is a tool package specifically designed for beginners in electronic circuit building and programming logic. It covers course content ranging from basic LED control to complex environmental sensing, monitoring, and actuator applications.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: DFR0100-ND
SEN0609 24GHz millimeter-wave presence sensor (25m, UART) Long-range, high-precision, motion detection, and distance/speed measurement sensor
The C4001(25m) millimeter-wave presence sensor uses a 24GHz wavelength signal, with a 100° horizontal detection range, 16m presence detection range, 25m motion detection range, and distance measurement range.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-SEN0609-ND
SEN0539-EN Gravity: Offline speech recognition module (I2C & UART)
This module adopts a brand-new offline speech recognition chip. It comes with 135 commonly used fixed command entries and adds a command self-learning function. Self-learned commands can be not just a voice segment but also a whistle, a snap, or a cat’s meow, supporting up to 17 self-learned commands. Dual-microphone design provides better noise resistance and longer recognition distance. The module comes with a built-in speaker and an external speaker interface, providing real-time voice feedback of recognition results. The module supports both I2C and UART communication methods, features a Gravity interface, and is compatible with controllers such as Arduino Uno, Arduino Leonardo, Arduino MEGA, FireBeetle series, Raspberry Pi, ESP32, and more.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-SEN0539-EN-ND
SEN0305 Gravity: HuskyLens AI Vision Sensor
HuskyLens is an easy-to-use AI vision sensor with six built-in functions: face recognition, object tracking, object recognition, line tracking, color recognition, and tag recognition. AI training can be completed with just one button, eliminating tedious training and complex visual algorithms, allowing you to focus more on project conception and implementation.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-SEN0305-ND
SEN0617 Gravity: I2C BME688 Environmental Sensor
The Gravity BME688 environmental sensor is a highly integrated MEMS environmental sensor capable of comprehensively measuring environmental parameters such as temperature, humidity, barometric pressure, and VOC gases (volatile organic compounds). Its software protocol and hardware dimensions are fully compatible with the BME680, allowing direct replacement of the BME680 in existing systems without any adjustments. Additionally, the BME688 improves temperature measurement accuracy and features a hollowed-out design around the chip on the circuit board to reduce the impact of external component heat on measurements.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-SEN0617-ND
DFR0760 Gravity: Chinese-English Text-to-Speech Module V2.0
Let sound add a unique touch to your project! Connect the text-to-speech module and add a few simple lines of code to make your project speak. Whether it’s Chinese or English, it’s “so easy” for the text-to-speech module. It can announce the current time, report environmental data, and even enable voice dialogue when combined with a speech recognition module! The module supports both I2C and UART communication methods, features a Gravity interface, and is compatible with most controllers. The module already includes a built-in speaker, so no additional speaker is needed.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-DFR0760-ND
Editor’s note:
As introduced in the articles and videos, DFRobot’s open-source hardware leverages three core advantages—technical simplification, cost optimization, and ecosystem maturity—to effectively break down the professional barriers of AI development. This enables individual makers, educational institutions, and enterprises to participate in AI innovation with low costs and high efficiency. At the same time, it deeply integrates the “open-source spirit” with “AI engineering,” accelerating the implementation and commercialization of AI ideas. Have you used DFRobot’s open-source hardware for AI projects? What experiences or questions do you have about related development? Feel free to leave a comment and share with the DigiKey community!