Did you know? How many volatile organic compounds are hidden in the air we breathe every day? Is the office lighting intensity secretly affecting work efficiency? The soil in flowerpots has actually been using a “moisture code” to tell plants whether they’re thirsty—it’s just that human senses can’t pick up these signals.
But now, an “ultra-sensory system” composed of AI and sensors is helping us uncover these hidden environmental truths. Today, in the Episode 4 of the 「Redefining the Present with AI」 series, teacher Rockets Xia will guide everyone in using DFRobot’s powerful tools to transform invisible environmental changes into a “life guide” that can be understood, warned about, and interacted with.
-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.
These “environmental detectives” are 100 times more sensitive than human senses
To decode environmental secrets, you first need a team of “detectives” that can “see,” “smell,” and “touch” invisible signals—this is the DFRobot sensor family.
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Gravity Capacitive Analog Waterproof Soil Moisture Sensor: It acts like a personal doctor for plants, inserting into the soil to accurately read moisture data. When watering potted plants, it captures every detail of water penetration in real time, ensuring you never kill your plants by “watering based on feeling” again, achieving precise irrigation where “every drop of water is used effectively.”
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Gravity 5-in-1 Environmental Sensor: One sensor replaces five, measuring temperature, humidity, air pressure, light, and UV all at once. What’s the most comfortable temperature for office air conditioning? Will the UV on the balcony harm your succulents? It handles everything in one go, earning the title of “all-in-one environmental data collector.”
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Gravity I2C SGP40 Air Quality Sensor: Invisible volatile organic compounds (VOCs) like formaldehyde and benzene in the air are no match for this sensor, which detects them as sensitively as an “electronic nose.” When you spray insect repellent, it instantly detects the spike in VOC concentration and triggers an alert—recording air changes you didn’t even notice.
For beginners, the Arduino Starter Kit is the perfect choice. It includes basic sensors and actuators, plus a user-friendly learning platform, making it easy to learn data collection even with zero programming experience.
Two “brains” work together to turn data into alerts even elders can understand.
Sensors alone aren’t enough—data needs a “brain” to process it. DFRobot’s two main control boards are the “intelligent core” of this system.
The FireBeetle2 ESP32-S3-U is the undisputed “data processing hub.” As a powerful AIoT microcontroller, it can receive signals from multiple sensors and combine scattered humidity, temperature, and VOC data into meaningful insights. Even better, it features an ESP32-S3 processor for local AI inference (edge computing), eliminating the need to upload data to the cloud—reducing latency and protecting privacy. For example, it can identify plant diseases or analyze water quality changes on the spot, working 10x faster than “cloud-based requests.”
Meanwhile, the UNIHIKER Python Educational Main Control Board is the “interaction expert.” Its visual interface turns dry data into dynamic charts: soil moisture changes appear as wavy lines, and air quality alerts use color codes—making it easy for elders to understand. If data exceeds limits, it activates the Fermion DFPlayer PRO MP3 module to announce, “Air quality dropping—open a window!”—100x more direct than a phone notification.
More importantly, the Xingkong Board is extremely Python-friendly. No need to wrestle with complex code—just a few simple commands can display data and trigger alerts, making AIoT development accessible to everyone.
From balconies to cities, how many scenarios can this system unlock?
When sensors and the main control board team up, the “super-sensory system” unleashes its potential across various scenarios:
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Home gardening : Plug a soil moisture sensor into your succulent, and the curve on the Xingkong Board will tell you whether the plant is “well-hydrated” or “thirsty,” eliminating the guesswork of “should I water it today?”
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Indoor health : Place a five-in-one sensor on your desk—it reminds you to open the curtains when light is insufficient and automatically prompts you to turn on the air purifier when VOC levels exceed limits, far more practical than a colleague’s “drink more water.”
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Outdoor monitoring : Move the system to your balcony or community garden, and it cycles through temperature, air pressure, and UV data. Before a weekend picnic, check its report to decide whether to pack sunscreen.
And this is just the beginning. With technological upgrades, this system can integrate into smart cities (monitoring PM2.5 and guiding traffic), precision agriculture (directing irrigation and fertilization based on soil data), and environmental protection (detecting forest fires or illegal hunting)—proving that the boundaries of human perception can truly be expanded infinitely by technology.
Everyone can become an “environmental decoder.”
In fact, building such a super-sensory system is not difficult at all. DFRobot has already prepared a full toolkit for you: from sensors to the main control board, modular design makes assembly as easy as building blocks; open-source platforms and tutorials allow even beginners to learn programming and debugging step by step.
As mentioned in earlier episodes of the series, the barrier to AI innovation has already been lowered by DFRobot’s open-source hardware—whether you’re a student, office worker, or tech enthusiast, you can build your own environmental monitoring system.
Next time you see the fluctuating data curves on the Xingkong Board or hear the sensor-triggered voice alerts, you might suddenly realize: those once-invisible environmental codes are being deciphered by our own hands. And this is precisely the most touching aspect of technology — enabling everyone to understand the world more profoundly and actively safeguard their lives.
That concludes all 4 episodes of this video series. Click on the homepage to revisit all the content and try following along to give it a try~
Related project information:
Related product information:
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
SEN0308 Gravity Analog Capacitive Waterproof Soil Moisture Sensor
This is a newly launched waterproof soil moisture sensor from DFRobot. Compared to the older version, it features enhanced waterproof performance, allowing normal operation even when fully submerged in water. The corrosion resistance has been optimized with a multi-layer board design, eliminating concerns about accelerated sensor corrosion due to scratches from soil rocks. The electrode length has been increased, and circuit performance has been improved, expanding the measurement range and making the sensor readings more accurate!
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-SEN0308-ND
SEN0501 Gravity 5-in-1 Environmental Sensor
This is a 5-in-1 sensor that integrates five environmental parameters: the SHTC3 temperature and humidity sensor, BMP280 atmospheric pressure sensor, VEML7700 light sensor, and UV sensor (V1.0: ML8511, V2.0: LTR390-UV-01). For each environmental parameter, we use professional sensor chips. The circuit design carefully considers the rational layout and heat conduction of the core chips, effectively ensuring data accuracy.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-SEN0501-ND
SEN0394 Gravity I2C SGP40 Air Quality Sensor
The SGP40 air quality sensor adopts the next-generation SGP40 digital VOC sensor chip from the renowned Swiss company Sensirion. Based on Sensirion’s CMOSens® technology, the SGP40 provides a complete sensor system on a single chip, including a temperature-controlled micro-hotplate and humidity-compensated signals for indoor air quality. Combined with Sensirion’s powerful VOC algorithm, the sensor signals can be directly used to evaluate indoor air quality. It features low power consumption (2.6mA), fast response (2 seconds), no need for user calibration, and output data that can intuitively assess air conditions.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-SEN0394-ND
DFR0768 Fermion DF1201S DFPlayer PRO MP3 Player Module
The DFR0768 player module supports four control methods: Arduino, AT commands, onboard buttons, and AD buttons. With onboard buttons, music playback and switching can be performed even without a microcontroller. The module comes with 128MB of storage space, allowing you to easily copy your favorite music to the module via a USB cable. This module can serve as a sound card for computers or Raspberry Pi. Connect the module to a computer via USB cable, and music played on the computer can be output through this module.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-DFR0768-ND
FIT0502 Passive Mini Speaker
The new version of FIT0502 passive mini speaker features a JST PH2.0 interface, 8-ohm internal resistance, and 3-watt power. Its elongated design includes mounting screw holes, making it suitable for various audio source projects. It delivers crisp, distortion-free sound.
DFRobot official website development resources link
DigiKey online purchase link
DigiKey Part Number: 1738-FIT0502-ND
Editor’s note:
As introduced in articles and videos, DFRobot has packaged “boards + sensors + software” into plug-and-play environmental perception kits, transforming AI environmental sensing systems from wheel-reinventing to Lego-like assembly. With its all-in-one sensor integration and edge AI inference, AI environmental sensing system development can be completed within a day at just a hundred-dollar-level cost. What development resources do you use when building environmental sensing systems? What experiences or questions do you have regarding the selection of related resources? Feel free to leave a comment and share with the DigiKey community!