ECS-TXO-3225 Series HCMOS SMD TCXO Oscillators
The ECS-TXO-3225 is ideal for portable, wireless applications where stability is critical.
1555F Series IP68 Wall Mounted Enclosures for Harsh Environments
Enclosures with mounting flanges ideal for housing electronic devices in industrial environments
UNO Q Microcontroller Board
Arduino UNO Q bridges high-performance computing with real-time control.
Can You Build Efficient Motors Without Rare-Earth Magnets? Gati Drives Thinks So
As I sit down to write this piece, I notice the fan whirring above and, for the first time, it occurs to me that it runs on an induction motor. So does every other fan in my office and my home. These motors have been around for a long time, not because they’re the best options out there, but because they’re cheap and do the job. BLDC motors have gained a bit of popularity, but are pricier and usually come with an import dependency problem.
FNIRSI-1014D Oscilloscope Teardown
Authors
Divya Sambhayanamath, Kumudini Balobal, Mahantesh Hosur, Shivanand G Holi
Guide & Review
Sandeep Patil, CTO at RedNerds
Model Name: FNIRSI-1014D
Abstract :
An oscilloscope that retails at INR 13K basically covers all of the hands-on subjects a 4-year engineering syllabus teaches in theory. The only issue is that none of this is practiced. We barely get past MCUs hands-on.
This oscilloscope though has
1. MCU: GD32E230. Well, the pattern is repeating. Any guesses as to which other MCU family this resembles?
2. FPGA: EF2L45LG144 FPGA for heavy-duty processing.
3. SoC: Allwinner F1C100s CPU + RAM + video + audio in one chip
4. Power supply
Check this teardown to get insights into the build, how it all comes together, tool chain for development and what the ballpark cost at 100K volume.
Table of Contents
- 1. Introduction
- 2. External Overview of the Oscilloscope
- 3. Technical Specifications
- 4. PCB Architecture and Internal Hardware Layout
- 5. Input Processing Architecture
- 6. FPGA-Based Data Processing
- 7. Display and User Interface Processing
- 8. LCD Display System Architecture
- 9. LCD Display Working Principle
- 10. Front Panel Control System
- 11. Rotary Encoder Control Mechanism
- 12. Complete System Architecture
- 13. Firmware Architecture
- 14. Cost Analysis of Components
- 15. Conclusion
1. Introduction
A digital storage oscilloscope (DSO) is a critical instrument used in electronics for analyzing electrical signals over time. Modern oscilloscopes integrate high-speed analog front-ends, digital signal processing hardware, and graphical user interfaces to provide accurate waveform visualization and measurement.
The FNIRSI-1014D is a dual-channel digital storage oscilloscope designed for portable measurement and educational use. It features a 100 MHz bandwidth, a 1 GS/s sampling rate, and dual input channels, allowing simultaneous measurement of two signals. The device integrates multiple embedded subsystems, including an FPGA for high-speed signal processing, an ARM-based system controller, and a microcontroller dedicated to user interface management.
This teardown study aims to analyze the internal structure of the FNIRSI-1014D oscilloscope by physically disassembling the device and examining the internal hardware architecture. The report explores the following aspects:
- Mechanical structure of the oscilloscope
- PCB layout and internal subsystems
- Signal processing architecture
- Display system structure
- User interface hardware
- Firmware architecture
- Estimated component cost
The analysis helps understand how modern oscilloscopes integrate analog electronics, digital processing, and embedded computing systems to perform high-speed signal measurement.
2. External Overview of the Oscilloscope
The FNIRSI-1014D oscilloscope is housed in a plastic enclosure designed for handheld or bench operation. The front panel contains the display, input connectors, and control knobs. The rear panel contains labeling and structural support elements.
The device is designed for ergonomic operation with dedicated controls for waveform scaling, triggering, and signal acquisition.
External Structural Views
The device was inspected from multiple orientations to understand its mechanical design.
- Front View – Contains display, knobs, and connectors
- Top View—Houses' ventilation and structural support
- Bottom View – Contains mounting points and base supports
- Back View – Includes product information and identification labels
3. Technical Specifications
The FNIRSI-1014D oscilloscope includes several performance parameters that define its signal acquisition capability.
| PARAMETER | SPECIFICATION |
| Model | FNIRSI-1014D |
| Bandwidth | 100 MHz |
| Sampling Rate | 1 GS/s |
| Number of Channels | 2 |
| Input Impedance | 1 MΩ |
| Rise Time | 3 ns |
| Storage Depth | 240 Kbit |
| Sensitivity Range | 50 mV – 500 V |
| Time Base | 50 s – 10 ns |
| Trigger Modes | Single / Normal / Auto |
These specifications determine the oscilloscope's ability to capture fast signals while maintaining accurate timing and voltage measurement.
4. PCB Architecture and Internal Hardware Layout
The oscilloscope uses a multi-layer FR-4 printed circuit board integrating analog, digital, and power subsystems on a single board.
The PCB can be divided into five major subsystems:
- Input Signal Interface
- Analog Front End and Sampling System
- FPGA-based Signal Processing Unit
- System Control Processor
- Power Regulation Network
The board design includes extensive ground planes, copper pours, and via stitching to reduce electromagnetic interference and maintain signal integrity during high-speed operation.
5. Input Processing Architecture
The input processing block is responsible for receiving external signals and preparing them for digital conversion.
The block consists of:
- BNC input connectors
- Analog front-end conditioning circuits
- Relay-based voltage range selection
- Signal attenuation networks
- Trigger detection logic
The front panel includes rotary encoders and buttons, which are read by a GD32E303 microcontroller responsible for interpreting user commands.
The decoded commands are then forwarded to the FPGA and system controller.
Flow of Input Processing
- The user rotates knobs or presses buttons.
- MCU interprets user inputs.
- Analog signal enters through BNC connectors.
- The analog front-end conditions the signal.
- FPGA receives sampled data.
- Data is sent to the system processor for display.
This architecture allows the oscilloscope to respond quickly to user commands while maintaining high-speed signal acquisition.
6. FPGA-Based Data Processing
The core signal processing engine of the oscilloscope is the ANLOGIC EF2L45 FPGA.
Field Programmable Gate Arrays are widely used in oscilloscopes because they can process signals in parallel hardware logic, enabling extremely high processing speeds.
The FPGA performs several critical operations:
- High-speed signal acquisition
- Trigger detection
- Timing synchronization
- Waveform buffering
- Digital signal processing
Internal FPGA resources include:
- DSP blocks
- Block RAM buffers
- Clock management units
- High-speed system buses
Data Processing Flow
- ADC samples incoming signal
- FPGA receives digital samples
- Trigger logic detects capture condition
- Waveform data stored in memory buffers
- Data transferred to system controller
This hardware-level parallel processing enables real-time waveform acquisition.
7. Display and User Interface Processing
The Allwinner F1C100s system-on-chip serves as the main system controller.
This processor performs the following functions:
- User interface management
- Waveform rendering
- Menu system control
- Storage management
- System communication
The processor includes several hardware interfaces, such as:
- SPI
- UART
- USB
- GPIO
- SDIO
The SoC converts waveform samples received from the FPGA into graphical waveform plots displayed on the LCD screen.
8. LCD Display System Architecture
The oscilloscope uses a 7-inch TFT LCD display with a resolution of 800×480 pixels.
The display is composed of several layered optical structures that allow light modulation to form visible images.
LCD Layer Structure
The display consists of multiple layers arranged from back to front:
- LED Backlight
- Diffuser Layer
- Rear Polarizer
- Liquid Crystal Layer
- RGB Color Filters
- Front Polarizer
- Protective Glass Layer
9. LCD Display Working Principle
The TFT LCD operates using the principle of polarized light modulation through liquid crystal molecules.
Display Operation
- An LED backlight generates white light.
- A diffuser spreads light uniformly.
- The rear polarizer aligns light polarization.
- Liquid crystal molecules rotate polarization when voltage is applied.
- RGB filters create colored pixels.
- Front polarizer controls light transmission.
- Glass cover protects the display.
This process converts electrical signals into visible graphical waveforms.
10. Front Panel Control System
The oscilloscope includes several user interface controls that allow the user to interact with the measurement system.
Main Controls
Power Button
Activates the device and powers the internal electronics.
USB Host Interface
Used for exporting captured waveform images and measurement data.
Vertical Controls
Adjust voltage scaling (V/div) and channel positioning.
Horizontal Controls
Control time base (s/div) and waveform scrolling.
Trigger Controls
Determine the starting point for waveform capture.
Input Ports
BNC connectors provide electrical signal input.
11. Rotary Encoder Control Mechanism
The control knobs use incremental rotary encoders that generate quadrature pulses when rotated.
Encoder Operation
- Encoder rotation generates digital pulses.
- MCU reads pulse direction and count.
- MCU converts movement into parameter adjustments.
- Commands sent to FPGA.
- FPGA modifies signal processing parameters
12. Complete System Architecture
The complete oscilloscope system integrates multiple hardware subsystems working together.
Signal Flow
- The signal enters through BNC input connector
- The analog front-end conditions the signal
- ADC samples a signal.
- FPGA processes waveform data
- ARM SoC renders a waveform.
- LCD displays the waveform.
This architecture separates high-speed hardware processing from user interface control, improving overall performance.
13. Firmware Architecture
The oscilloscope uses a multiprocessor firmware architecture.
Microcontroller Firmware (GD32F303)
- Reads knobs and buttons
- Controls relay switching
- Sends control commands to FPGA
FPGA Logic
- High-speed signal acquisition
- Trigger detection
- Waveform buffering
System Processor Software
- Runs embedded Linux
- Manages display graphics
- Handles file storage
14. Cost Analysis of Components
Based on an estimated production volume of 100,000 units, the approximate component cost is:
| COMPONENT | ESTIMATED COST |
| FPGA | ₹950 |
| Soc Processer | ₹270 |
| Microcontroller | ₹140 |
| Power Management | ₹135 |
| PCB | ₹625 |
| External Parts | ₹550 |
| TFT LCD Display | ₹1950 |
Total Estimated Cost: ₹4620 per unit
15. Conclusion
The teardown analysis of the FNIRSI-1014D oscilloscope reveals a well-integrated embedded measurement system combining analog electronics, digital hardware, and embedded software.
The architecture uses three main processing elements:
- FPGA for high-speed signal processing
- ARM SoC for display and system control
- Microcontroller for user interface management
This distributed architecture enables the oscilloscope to achieve high sampling rates while maintaining responsive user interaction.
The multi-layer PCB design, controlled impedance routing, and dedicated power regulation ensure stable operation and accurate signal acquisition. The FNIRSI-1014D demonstrates how modern oscilloscopes integrate multiple computing platforms and specialized hardware to deliver high-performance measurement capabilities at relatively low manufacturing cost.
You may reach out to the RedNerds team for custom product development here: http://www.therednerds.com/
- Read more about FNIRSI-1014D Oscilloscope Teardown
- Log in or register to post comments
How to activate Airtel M2M IoT SimCard with Geolinker ESP32
Airtel M2M IoT SIM Activation – Quick Overview
- Log in to Circuit Digest Cloud & open the GeoLinker dashboard
- Enter ICCID and mobile number, verify OTP.
- Submit KYC documents (within 7 days)
- KYC verified by Airtel
- Whitelist up to 4 numbers for SMS/Voice
Table of Contents
- What is an Airtel M2M SIM Card?
- Accessing the Airtel M2M SIM Dashboard on Circuit Digest Cloud
- Step 1 ⇒ How to Activate Your Airtel M2M IoT SIM Card
- Step 2 ⇒ Completing KYC for Your Airtel M2M SIM Card
- Step 3 ⇒Viewing Your Airtel IoT SIM Card Details
- Step 4 ⇒ Setting Up SMS and Voice Whitelisting for Airtel M2M SIM
- └ Airtel M2M SIM Whitelisting Options at a Glance
What is an Airtel M2M SIM Card?
An Airtel M2M SIM card is specifically developed for communicating from one machine to another using the cellular networks. The Airtel M2M SIM is designed specifically for IoT and embedded devices that do not require a human operator or user to operate autonomously.
| Feature | Airtel M2M SIM | Regular SIM |
| Primary Use | IoT devices, GPS trackers, automation | Personal voice and data use |
| Number Regulation | DoT-mandated whitelisting (max 4 numbers) | Open communication with all numbers |
| KYC Requirement | Mandatory within 7 days of activation | Required at purchase |
| Management | Remote via Circuit Digest Cloud platform | Via carrier app or store |
| Included Plan | 3-month free plan (GeoLinker bundle) | Varies by plan |
Accessing the Airtel M2M SIM Dashboard on Circuit Digest Cloud
The Airtel SIM Management feature allows you to manage your IoT SIM cards directly from the Circuit Digest Cloud Platform. You can view SIM details, monitor data usage, submit KYC documents, and track device connectivity. To access the Airtel M2M dashboard, log in to your Circuit Digest Cloud Account. Once logged in, you can click on the view button under the GeoLinker section. The Airtel M2M SIM card is a specialised IoT SIM designed for machine-to-machine communication over India's cellular network. This makes it ideal for secure, internet-independent projects such as GPS trackers, remote automation systems, and GSM-based IoT devices. Before you can use the SIM for voice calls, SMS, or data, you need to complete the Airtel M2M SIM activation process through the Circuit Digest Cloud platform.
Step 1 ⇒ How to Activate Your Airtel M2M IoT SIM Card
Once you are in the GeoLinker Dashboard, click on the Airtel IOT SIM, which will redirect you to the Airtel IOT SIM dashboard. This is where you can see all the activated SIM card details. To activate a SIM card, click on the Activate SIM button in the top right corner.
In the activation page, enter the ICCID and your mobile number. The ICCID can be found on the SIM package, mentioned as SIM number, or you can get it from the serial output when you insert the SIM into the GL868_ESP32 with factory firmware. Check the Factory firmware section for more details. If you are using the number from the package, avoid the last alphabet; only the numeric number is needed. Click on send OTP to receive the OTP on your entered mobile number.
Once the OTP is verified, you will be redirected to the KYC submission page.
Step 2 ⇒ Completing KYC for Your Airtel M2M SIM Card
IMPORTANT: While you can start using the SIM immediately after OTP verification, you must complete the full KYC process within 7 days to avoid deactivation.
For KYC, you can use any of the KYC documents given in the table below. Once the KYC is completed, you can continue using the Airtel IOT M2M SIM card with the GL868_ESP32. If you choose to submit the KYC documents later, you can access the KYC submission page by going to the SIM details page and then clicking on the View KYC button.
| Required Documents | Allowed Documents |
| Identity Proof | - Aadhaar Card - PAN Card - Passport - Driving License - Voter ID |
Enter your mobile number to receive OTP.
Once the OTP is verified, you will be asked to upload your identity proof. Select document type and upload front and back images.
In the next stage, you will have to upload a live selfie.
Note: Your browser will ask for camera permission; please click "Allow" to proceed.
Once the selfie is captured, provide your current residential address, and finally review your details, accept the consent declaration and click on Submit KYC Documents. The KYC verification will be done within 28-48 hours.
TIP: You have a 7-day window from the initial activation to submit these documents. We recommend doing it immediately to ensure uninterrupted service. "Allow" to proceed.
Step 3 ⇒Viewing Your Airtel IoT SIM Card Details
In the SIM card details page, you can see all the details related to your Airtel IOT M2M SIM card, like whether it's active or not, KYC status, ICCID and IMSI, start and end dates of your plan and the remaining time until your plan expires.
Step 4 ⇒ Setting Up SMS and Voice Whitelisting for Airtel M2M SIM
As per DoT regulations, IoT SIMs are restricted to communicating only with whitelisted numbers. So mobile number whitelisting is required to enable calls to and from the M2M number, as well as to send and receive SMS messages. With an Airtel M2M SIM, you can whitelist up to four numbers. To white list numbers, click on the Manage Whitelisting button on the SIM Card Details page.
In the Whitelisting Management page, enter the number you want to whitelist, select the type (Voice, SMS or Both) and direction(Incoming, Outgoing or Both Ways) and click on Save Changes. The whitelisting will immediately take effect, and you can use the SMS and voice services.
Note: The Airtel IoT SIM card includes a 3-month promotional plan. After the promotional period ends, you can recharge the SIM card from here (link will be updated soon).
Airtel M2M SIM Whitelisting Options at a Glance
| Option | Choices Available |
| Communication Type | Voice / SMS / Both |
| Direction | Incoming / Outgoing / Both Ways |
| Maximum Numbers | Up to 4 mobile numbers |
| Effect | Immediately after Save Changes |
Frequently Asked Questions
⇥ Where can I find my Airtel M2M SIM card ICCID?
The ICCID is located on the package, with the SIM number listed as the SIM Number. If using GeoLinker GL868, insert the SIM and check the Serial Monitor; factory firmware will show the ICCID automatically when powered on. When you read the ICCID from the package, only enter the numerals and do not include the letter(s) at the end of the number.
⇥ How long does it take for Airtel to verify KYC (Know Your Customer) for M2M SIM Cards?
Airtel will complete verification of your KYC document submission through the Circuit Digest Cloud platform within 48 to 28 hours after submission. You may continue to use the SIM during this time, provided that your KYC document submission occurred within 7 days of the SIM's initial activation.
⇥ What is the maximum number of phone numbers that I can whitelist on the Airtel M2M SIM Card?
Whitelisting for up to 4 mobile numbers is available on your Airtel M2M IoT SIM. By using Whitelisting of each number, you also choose how you want to communicate (Voice, SMS or Both) and which way (Incoming, Outgoing or Both Ways). Whitelisting is effective immediately after you click Save Changes on the Circuit Digest Cloud dashboard.
⇥ Where can I find my Airtel M2M SIM card ICCID?
The ICCID is located on the package, with the SIM number listed as the SIM Number. If using GeoLinker GL868, insert the SIM and check the Serial Monitor; the factory firmware will show ICCID automatically when powered on. When you read the ICCID from the package, only enter the numerals and do not include the letter(s) at the end of the number.
⇥ How long does it take for Airtel to verify KYC (Know Your Customer) for M2M SIM Cards?
Airtel will complete verification of your KYC document submission through the Circuit Digest Cloud platform within 48 to 28 hours after submission. You may continue to use the SIM during this time, provided that your KYC document submission occurred within 7 days of the SIM's initial activation.
⇥ What is the maximum number of phone numbers that I can whitelist on the Airtel M2M SIM Card?
Whitelisting for up to 4 mobile numbers is available on your Airtel M2M IoT SIM. By using Whitelisting of each number, you also choose how you want to communicate (Voice, SMS or Both) and which way (Incoming, Outgoing or Both Ways). Whitelisting is effective immediately after you click Save Changes on the Circuit Digest Cloud dashboard.
Low-Cost Offline Voice Recognition Module Alternatives to VC-02
Voice control technology has become an important part of modern human-machine interaction. It allows users to control electronic devices and systems using simple spoken commands instead of traditional input methods such as buttons, switches, or touch screens. This type of interaction makes devices easier to use, more accessible, and more convenient in many applications such as smart homes, automation systems, and assistive technologies. Many existing voice recognition systems depend on cloud-based processing. In these systems, the user’s voice is recorded and sent to a remote server through the internet, where the voice is processed and converted into commands. While this method can provide powerful voice recognition capabilities, it also introduces several limitations. These systems require a constant internet connection, and if the network connection is slow or unavailable, the system may not work properly. Cloud-based processing can also cause delays (latency) in response time and may raise privacy concerns, since voice data is transmitted and processed on external servers.
To overcome these challenges, offline voice recognition modules have been developed. These modules are designed to process and recognize voice commands directly on the device without needing any internet connection. This makes the system faster, more reliable, and more secure, since the voice data remains within the local device. Offline voice recognition is especially useful in embedded systems, automation projects, and environments where internet access may not always be available.
In this project, an offline voice command system is implemented using the SU-03T Offline Voice Recognition Module. The VC-02 is an official module by Ai-Thinker, offering well-defined firmware, proper documentation, and SDK support for customizing and training voice commands, making it suitable for advanced development. In contrast, the SU-03T is a more generic module produced by various manufacturers, and it is preferred due to its low cost, making it an economical choice for simple voice control applications. In this system, when the user speaks a command, the SU-03T processes the voice input and compares it with its stored command set. If a match is detected, the module triggers the corresponding action. In this project, the recognised voice commands are used to control LEDs, turning them on or off. Also check out ESP32 Offline Voice Recognition System using Edge Impulse, which provides hands-on experience in edge AI and TinyML deployment on microcontrollers. This guide is based on hands-on testing with the SU-03T offline voice recognition module at the Circuit Digest lab. The SU-03T is used here as a practical, low-cost alternative to the VC-02 for offline voice command projects. Offline voice recognition modules solve this problem by processing and recognising voice commands entirely on-device, with no internet connection required. In this project, we implement an offline voice command system using the SU-03T Offline Voice Recognition Module, one of the cheapest alternatives to the VC-02/VC020 on the market today.
Table of Contents
Overview
Our tutorial has been created using the SU-03T Offline Voice Recognition Module at the Circuit Digest lab for real-time testing. The SU-03T is used here as a practical, low-cost alternative to the VC-02 for offline voice command projects. The offline voice command modules have been designed to allow you to use an offline voice recognition module with no requirement for an internet connection for the voice command to be processed and recognised. In this project, we implement an offline voice command system using the SU-03T Offline Voice Recognition Module, one of the cheapest alternatives to the VC-02 on the market today.
SU-03T vs VC-02 – Quick Comparison
If you're evaluating an alternative offline voice module for the VC-02 or VC020, the table below summarises the key differences to help you choose the right IC for your project:
| Feature | SU-03T | VC-02 (Ai-Thinker) |
| Internet required? | No | No |
| Price (approx.) | Very low (generic) | Low (branded) |
| SDK / Firmware tool | Ai-Thinker SDK portal | Ai-Thinker SDK portal |
| English command support | Yes (via Ai-Thinker SDK) | Yes |
| GPIO output control | Yes | Yes |
| PWM support | Yes | Yes |
| Wake-free commands | Up to 10 | Up to 10 |
| Documentation quality | Limited | Good |
| Best suited for | Budget projects, prototypes | Production, advanced dev |
Components Required
The components which are listed below are the ones required to build the complete setup. All items are widely available from electronics distributors such as DigiKey, Robu.in, and AliExpress.
| S.NO | Components | Quantity | Purpose |
| 1. | SU-03T | 1 | It is the main module used in the setup |
| 2. | Mic | 1 | Used to recognize the commands from the user |
| 3. | Speaker | 1 | Used to reply with the predefined reply words |
| 4. | USB to Serial Converter | 1 | Used to deploy the code to the module |
| 5. | LED(Green and Red) | 2(Each 1) | For observing the output |
| 6. | 100 Ohms Resistor | 2 | For resisting the current |
| 7. | Breadboard | 1 | Used for the temporary connection between components |
| 8. | Jumper Wires | Required amount | Used to connect all the components |
Circuit Diagram
The circuit diagram shows the connection of the microphone and speaker to the voice module, along with LEDs connected to its GPIO pins via resistors. It also includes the USB-to-TTL interface for firmware uploading and communication. The circuit diagram shows the complete hardware connections for this offline voice recognition project.
Pin Connection Summary
| SU-03T Pin | Connects To | Notes |
| VCC (3.3 V) | USB-to-TTL 3.3 V output | Do not exceed 3.3 V; module is not 5 V tolerant |
| GND | Common ground (USB-TTL) | Shared ground for all components |
| TX | USB-to-TTL RX | UART communication/firmware flashing |
| RX | USB-to-TTL TX | UART communication firmware flashing |
| MIC+ / MIC− | Electret microphone | Differential analog audio input |
| SPK+ / SPK− | 8 Ω speaker | Built-in amplifier output |
| GPIO1 | Green LED → 100 Ω → GND | Controlled by the "Turn on LED" command |
| GPIO2 | Red LED → 100 Ω → GND | Controlled by the "Turn off LED" command |
Hardware Connection for the Offline Voice Recognition Module
The SU-03T Offline Voice Recognition Module is connected to a USB-to-Serial converter for power supply and programming. A microphone and speaker are interfaced with the module to handle voice input and audio output. The GPIO pins of the module are connected to LEDs through current-limiting resistors to perform output actions.
How the SU-03T Offline Voice Recognition Module Works
The working of this project is based on the SU-03T Offline Voice Recognition Module, which is designed to recognize voice commands without requiring an internet connection. The module is connected to a mic, speaker and an internal processor that can analyse voice inputs and match them with predefined commands stored in its memory. Before using the module, the required voice commands must be configured and loaded into the module.
Once the commands are configured and uploaded to the module, the SU-03T continuously listens for voice input through the microphone. When a user speaks a command, the module captures the audio signal and converts it into digital data. The internal voice recognition engine then processes this signal and compares it with the stored voice command patterns. If the spoken command matches one of the predefined commands, the module identifies it and immediately triggers the corresponding action. The module then controls the GPIO output pins connected to external components such as LEDs. Actually, there is a website called https://smartpi.cn/#/ where we can flash the SU-03T. However, it has a limitation, it only accepts correct Chinese words, and English words are often ignored. So, we are using the steps and website given below to flash our module. If you have time, you can explore that page for future use.
Step-by-Step: Configure and Flash the SU-03T Offline Voice Recognition Module
This same workflow is compatible with the VC-02 and serves as the recommended offline voice recognition SDK configuration process for all Ai-Thinker-compatible modules.
Step 1: Register on the Ai-Thinker Voice SDK Portal
http://voice.ai-thinker.com/#/SdkVersionList
Click the website (translate it to English)and log in to the website if you don’t have an account. Register for the account after that, you can see “Create the product” in the top left corner, click that.
Step 2: Create a Pure Offline Product Profile
In that, click on other products and select the scene as “Pure Offline”, Module as “VC-02”, then give any name for the product and language as English, now click save.
Step 3: Review Pin and SDK Configuration
After the previous step, it will take you to the voice SDK section, where you need to set the configurations for pins and also set the commands. No need to change anything in the pin configuration section.
Step 4: Configure the Wake Word
In the custom wake word section, you can set any wake word you prefer, like “Hai” or “hello”, and you also need to set the wake-up reply like “hello buddy” or “hello Circuit Digest”.
Step 5: Add Offline Voice Recognition Commands
Set the behaviour words as “turnonled” or “turnoffled” like this for then for the command words give the words which you prefer like “Turn on led” or “lights on” like this also give the appropriate reply sentence like “turning on the led” or “turning lights off”. Near the basic information tab, you can see the control details tab. Click that, and see the configuration as per your requirement, like low or high. Here, you can also set the pulse.
Step 6: Configure Wake-Free Commands
After setting all configurations, scroll down, and you can see the wake-free commands section, where we can set only 10 wake-free command words. After that, we need to tell the wake-up word first and use the command after that so we can able to select which and all commands are wake-free commands in this by selecting.
Step 7: Select Voice Actor and Audio Settings
After that, you can set your preferred voice actor in the voice actor configuration section and also able to set the brightness of the voice, speed, and volume.
Step 8: Add Startup Announcement and Exit Commands
In the other configurations section, you can add the startup announcement, exit reply, voluntary withdrawal exit command and exit reply as per your need.
Step 9: Generate Firmware
After setting all things, click the generate a new version and give a description for it. After that, it will take you to the voice SDK section, where you can see your product. Click the generate SDK " tab. It will generate your SDK or firmware within 30 to 35 minutes max. Now download the firmware it generated and extract the file.
Step 10: Download the UniOneUpdateTool Flash Utility
Download the Unicommon.dll, UniCommunicateSwitch.dll and UniOneUpdateTool.exe from Hummingbird-M-Update-Tool V1.0
After installing, click the UniOneUpdateTool.exe and, as per the circuit diagram, connect all the components. Then connect the USB to TTL to the USB port of the laptop. Now you can see the port COM appear in the window of the UniOneUpdateTool.
Step 11: Flash Firmware to the SU-03T Module
In the UniOneUpdateTool window, you can see the option like this 选择(Choose). Click this option and go to the extracted firmware folder, select the uni_app_release_update.bin file, then you can see the 烧录（Programming/Burning. Click this and wait till all ports are filled with yellow. When all is finished, remove the power pin jumper from the USBs to TTL converter, then again insert it. Now you can see the firmware is getting flashed into the module. Also, spare some time to take a look at our electronics projects to get more ideas in the field of electronics
Working Demo of Offline Voice Recognition Module
Applications of Offline Voice Recognition Modules
1. Smart Home Automation
Offline voice recognition modules can be used to control home appliances such as lights, fans, and other electronic devices using voice commands. This allows users to operate devices easily without using switches or mobile applications.
2. Assistive Technology
Voice-controlled systems can help elderly people and individuals with physical disabilities control electronic devices more conveniently. Simple voice commands can allow them to turn lights on or off without needing physical interaction.
3. Industrial Automation
In industrial environments, voice control can be used to operate certain machines or indicators where manual operation may be difficult. Offline voice systems improve reliability since they do not depend on internet connectivity.
4. Automotive Control Systems
Offline voice recognition can be integrated into vehicles to control features such as lights, music systems, or navigation functions. This allows drivers to operate systems hands-free, improving safety and convenience. Low-cost
5. Educational and Embedded System Projects
Offline voice modules are widely used in educational projects and research to demonstrate voice-based human-machine interaction
| Application | How Offline Voice Recognition Helps | Devices Controlled |
| Smart Home Automation | Local control without cloud dependency; works during internet outages | Lights, fans, curtains, sockets |
| Assistive Technology | Enables hands-free device control for elderly and differently-abled users | Lamps, TV, door locks |
| Industrial Automation | Reliable in offline factory environments; no latency from cloud calls | Indicators, alarms, and conveyors |
| Automotive Systems | In-car voice control without mobile data; instant response | Lighting, HVAC, infotainment |
| Educational & Maker Projects | Low-cost entry point for voice HMI projects; no API keys needed | LEDs, servos, buzzers, displays |
Troubleshooting the SU-03T Offline Voice Recognition Module
Issue 1: Voice command is not recognised
Solution:
This may occur if the spoken command does not exactly match the predefined command stored in the module. Ensure that the command is spoken clearly and with proper pronunciation. Also, check whether the correct voice command dataset has been uploaded to the module using the official configuration tool.
Issue 2: The LED does not turn ON or OFF
Solution:
Check the wiring between the SU-03T module and the LED. Make sure the LED is connected to the correct GPIO pin with a current-limiting resistor. Also, verify that the output pin configuration in the software matches the actual hardware connection.
Issue 3: Module is not responding to voice input
Solution:
This can happen if the microphone is not detecting sound properly or if the module is not powered correctly. Ensure that the module receives the required power supply and that the microphone area is not blocked. Speaking closer to the module can also improve detection.
Issue 4: PWM control is not working properly
Solution:
If the LED brightness or motor speed does not change, verify that the PWM pin is correctly configured in the software. Check whether the PWM output pin is properly connected to the device and confirm that the duty cycle settings are correctly applied.
Issue 5: Module not detected while configuring through the computer
Solution:
Ensure that the USB-to-Serial converter or programming interface is properly connected. Install the correct drivers and verify that the correct COM port is selected in the configuration software. Restarting the software or reconnecting the module may also resolve the issue.
Future Enhancements
Multi-Device Control
The system can be expanded to control multiple devices such as fans, motors, and home appliances using different voice commands.communication/firmware Smartcommunication/firmware Home Integration
It can be integrated with a complete smart home system to control lighting, security systems, and other automation devices.Mobile Application Interface
A mobile application can be added to monitor and control devices along with voice commands.Motor and Appliance Control
The system can be enhanced to control motors, pumps, and other electrical appliances using voice commands.Custom Voice Command Expansion
More voice commands can be added to increase the functionality and control more operations in the system.
Conclusion
This project demonstrates the implementation of a simple offline voice-controlled system using the SU-03T voice recognition module. The system shows how voice commands can be used to control electronic devices without requiring an internet connection. It highlights the advantages of offline voice recognition, such as faster response, improved reliability, and better privacy. By configuring voice commands through the Ai-Thinker offline voice recognition SDK and flashing the firmware with UniOneUpdateTool, you get a reliable, private, low-latency voice control system that requires zero internet connectivity. The project also shows how GPIO and PWM outputs can be used to control devices like LEDs through voice commands. Overall, the system provides a practical example of voice-based human-machine interaction in embedded systems. Such systems can be further expanded for automation and smart control applications in the future. We invite you to look into our projects like “Building a Voice Controlled Home Automation System with Arduino”, which focuses on voice-based appliance control, and “Voice Controlled Lights using Raspberry Pi”, which demonstrates smart lighting automation using speech commands and GPIO interfacing.
Frequently Asked Questions
⇥ Does the module require an internet connection to work?
No, the module works completely offline. All voice commands are processed inside the module, which makes the system faster and more reliable.
⇥ How are voice commands added to the module?
Voice commands can be configured and uploaded using the official configuration tools and SDK available on the platform provided by Ai-Thinker.
⇥ What are the main advantages of using an offline voice recognition module?
Offline voice recognition provides faster response time, improved privacy, and better reliability since it does not depend on internet connectivity.
⇥ Can the module control devices other than LEDs?
Yes, the module can control various devices such as motors, relays, fans, and other appliances through its GPIO pins, depending on the circuit design.
⇥ Is it possible to change or update the voice commands later?
Yes, voice commands can be modified or updated by reconfiguring the settings in the SDK platform and uploading the new firmware to the module.
⇥ How long does it take for the Ai-Thinker SDK portal to generate new firmware for the SU-03T?
After you click 'Generate New Version', the firmware will compile on an Ai-Thinker cloud server in about 30-35 minutes. At this point, you will be able to download the ZIP file (which contains the compiled firmware) in the SDK version list. After downloading the ZIP file, unzip it and locate the uni_app_release_update.bin file for the flashing process.
⇥ What's the recommended flashing tool for the SU-03T voice module?
The recommended flashing tool for the SU-03T is the UniOneUpdateTool (part of the Hummingbird M Update Tool V1.0 package). Connect your SU-03T to your computer through a USB to TTL converter, select the firmware .bin file in the tool, click Burn, wait for all ports to be yellow and then power cycle the SU-03T after the process completes.
Voice-Controlled Projects
Previously, we have explored several voice-controlled projects using platforms like Amazon Alexa and hardware such as ESP8266 and Raspberry Pi. If you want to learn more about these implementations, the links are provided below.
HomePod S3 - A Smart Desk companion
Offline smart desk companion with touch, voice, timer, to-do, medicine reminders and local web control powered by ESP32-S3.
Alexa Voice Controlled LED using Raspberry Pi and ESP12
In this DIY tutorial, we are making an IoT project to control home appliances from anywhere in the world using AlexaPi and ESP12E.
IOT-based Voice Controlled Home Automation using ESP8266 and Android App
Voice-controlled home automation using an ESP8266 Wi-Fi module, where you can control your Home AC appliances using your voice through an Android App from anywhere in the world.
India’s Electronics Powerplay: Why 2026 Will Set the Industry Pace
In conversation with Bhupinder Singh, President – IMEA (India, Middle East, Africa), Messe München | CEO, Messe München India
The Indian Startup Making Robots Do Construction Work | Pace Robotics
Pace Robotics makes robots that paint… just not something you’d hang up at a gallery. As a part of our visit to this Bengaluru-based startup, we got to witness one of those robots in action at an actual construction site. They call it the Centa Painter, and it can spray putty, perform sanding, and apply paint on interior walls and ceilings, all things humans have been doing by hand forever and would rather not.
First Event
Defence & Aerospace SES 2026
Date: 23–24 July 2026
Time: 10AM to 6PM
Place: BIEC, Bengaluru
