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.
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.
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.
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.
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.
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
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
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.
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.
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.
Optocouplers frequently fail without a sound in labs or during repairs. The package appears to be undamaged, but there may be no output from the LED source or the photosensitive output stage. Testing for failure with a multimeter is only partially effective, whereas a dedicated optocoupler testing circuit provides clear results in just seconds. For related tutorials and step-by-step build guides, explore Circuit Digest's Electronic Circuits hub.
An optocoupler tester is a small device that helps verify whether an optocoupler is functioning properly or has failed. In labs and repair work, optocouplers often fail without clear signs. They may look fine from the outside, but the internal LED or photo part may not function properly. Guessing in such cases wastes time and can damage the main circuit. This tester dispels that doubt by checking whether the internal LED turns on and whether the output side responds to light. The circuit stays simple, runs on a 3.7 V lithium-ion battery, and can be built on a dot board without using any measuring tools. It does not aim to test detailed performance, but it works well for quick and reliable checks at the workbench. More details about the Optocoupler and its applications are provided on the Optocoupler tutorial page. Also, you can explore more applications and other electronic circuits on our resources page.
What does an Optocoupler Tester Check?
∗ The IR LED at the input side is conducting and producing light (IR emission) ∗ The Photodetector at the output side is triggering due to the IR light that the IR LED is producing ∗ The testing circuit is able to conduct both a 4-pin DIP and a 6-pin DIP with no wiring changes being required.
Components Required to Build the Optocoupler Tester
The image below shows the list of components used to build the Optocoupler Testing circuit.
The circuit uses only commonly available components. It avoids special or complex parts, making it easy to build and understand. The table shows every component used in this DIY optocoupler tester build.
The circuit uses IC bases instead of soldering optocouplers directly. This avoids heat damage and allows the same tester to be used repeatedly with different optocouplers.
Optocoupler Tester Circuit Diagram and Schematic
How to Read the Schematic
The optocoupler tester schematic consists of two main sections: the input and output parts of the optocoupler. On the input side, the Li-ion battery supplies power via a resistor, and the push button determines when the power is delivered. When the button is pressed, current flows through the optocoupler's internal LED, causing the red LED to light up, indicating that the input side is receiving power and is functioning.
On the output side, the light from the internal LED reaches the light-sensitive component inside the optocoupler. This allows current to flow through the green LED, turning it on and showing that the output side is working correctly. Both the input and output sides are connected to the same ground. This optocoupler tester circuit is constructed on a dot board with IC bases. The optocoupler tester circuit diagram shows that this configuration enables testing of both 4-pin and 6-pin optocouplers without changes to the wiring.
How the Optocoupler Tester Works
Understanding the optocoupler tester working principle requires only three concepts: IR LED emission, phototransistor activation, and current-limited indicator LEDs. The optocoupler tester works based on optical isolation. When you press the button, power flows to the input LED inside the optocoupler. If everything is working properly on the input side, the internal LED lights up and the red LED turns on to indicate that current is flowing correctly.
The light from the input LED then reaches the light-sensitive part on the output side of the optocoupler. This allows current to flow through the green LED, causing it to glow and indicating that the output side is working correctly. This optocoupler test helps you quickly identify issues. If only the red LED turns on, it means there's a problem with the output side or the light isn't transferring properly. If neither LED turns on, the input LED may be faulty, or the optocoupler may not be connected correctly.
Red LED
Green LED
Test Result
Action
ON
ON
PASS — Good optocoupler
Safe to use in a circuit
ON
OFF
FAIL — Output stage dead
Replace the optocoupler; the phototransistor is damaged
OFF
OFF
FAIL — Input LED open or wrong insertion
Check pin orientation; replace if correct
OFF
ON
SUSPECT — Output shorted or wiring error
Check tester wiring; the output transistor may be shorted CE
Practical Working Demonstration
In real use, insert the optocoupler into the correct IC socket and verify that it is positioned properly. Then press the button to activate the circuit. A working optocoupler will light up the red LED immediately, showing that the input side is active, followed by the green LED, which confirms that the output side is responding. If only the red LED lights up, the optocoupler is faulty and should not be used. If neither LED turns on, the device may be damaged or inserted incorrectly. This DIY optocoupler tester is especially useful when checking salvaged components or verifying a batch of parts. To better understand why optocouplers are used for electrical safety and isolation, you can read more about galvanic isolation.
Alternate Methods to Test the Optocouplers
Different methods are used to test an optocoupler, depending on the tools available and the level of accuracy required. A multimeter can quickly check the internal LED, and simple testing circuits built on a breadboard can show how the input and output work. For more detailed testing, labs use advanced tools such as component testers and curve tracers. Here are the commonly used testing methods.
1. Comparison Method
In this method, the optocoupler suspected of being faulty is removed from the circuit and tested with a multimeter. Then, the readings from the multimeter are compared with those from another optocoupler known to be working properly and of the same type. The test measures the forward and reverse resistance of the internal LED and the resistance between the transistor pins. If the measured values differ significantly from those of the good optocoupler, the tested optocoupler is likely damaged. This approach is straightforward and fast, but it only gives a general idea and does not guarantee that the device will work correctly in real situations.
2. Digital Multimeter Detection Method
This is the most widely searched approach. Here is a structured procedure for how to check an optocoupler with a multimeter:
A digital multimeter can be used to test both the input and output parts of a circuit separately. To start, check the input LED using the diode setting to make sure it conducts properly when forward-biased. Next, measure the output pins while the LED is on to see whether the transistor switches on or if there is a change in current or gain. If the readings change when the input is activated, the optocoupler is working correctly; if there is no change, it may be faulty. This method provides more detailed information than a simple resistance check, but the setup and results can be confusing for someone new to electronics and still need some interpretation.
3. Photoelectric Effect (Battery and Resistor) Method
This method directly tests the optocoupler's working principle by powering the input LED with a small battery and a current-limiting resistor, while monitoring the output pins with a multimeter. When the LED turns on, the light inside the device should activate the output transistor, causing the meter reading or pointer to change. If the reading changes or the pointer deflects, the optocoupler is working; if there is no change, the device is defective. Because it checks real input-to-output behaviour, this method is more reliable and practical than simple resistance measurements.
Comparison Between the Optocoupler Tester and Multimeter Method
Using a Multimeter
A multimeter is convenient because it is already available in most labs and does not require any extra hardware. It can check basic things like LED continuity and diode behaviour, which helps with a quick preliminary inspection. However, it only tests the input LED of the optocoupler and cannot verify the output side properly. This means the device may appear fine even when it is actually faulty. The process also involves manual probing and interpretation of readings, which can be slow and confusing for beginners. As a result, a multimeter provides only a rough estimate rather than a clear confirmation.
Using an Optocoupler Tester
An optocoupler tester circuit is designed specifically for testing optocouplers and checks both the input LED and the output transistor simultaneously. It directly shows whether the device is working or faulty using simple LED indicators, so no probing or analysis is required. The test is fast, easy, and reliable, making it suitable even for first-year students or beginners. The only disadvantage is that an extra circuit must be built or purchased, but once it's available, it provides a clear, accurate optocoupler test every time.
Optocoupler Tester vs. Multimeter Method
Criterion
Dedicated Optocoupler Tester
Digital Multimeter
Tests input LED
✔ Yes
✔ Yes (diode mode)
Tests output phototransistor
✔ Yes- simultaneously
Partial - requires extra setup
Result readability
Instant LED pass/fail
Numerical values need interpretation
Test speed
<2 seconds per device
2–5 minutes for the full 3-step test
Additional hardware needed
The tester itself (~₹50 / $1 in parts)
Multimeter already in the lab
Detects partial output degradation
Only gross failures
Only gross failures (without scope)
Suitable for batch testing
✔ Yes — very efficient
✘ No — too slow
Advantages and Disadvantages of the Optocoupler Tester
Advantages
Disadvantages
Checks optocouplers quickly without using any instruments
Does not show the output signal strength
Small size and runs on a battery
Not useful for very fast or special optocouplers
Works with both 4-pin and 6-pin optocouplers
Cannot clearly find weak or ageing optocouplers
LED lights make the result easy to see
Only checks basic working conditions
Low cost and easy to build again
Not meant for detailed testing
Troubleshooting Optocoupler Testing Issues
These are some troubleshooting methods for optocoupler testing issues
Problem Observed
Possible Cause
Solution
The input LED is not glowing.
Wrong pin connection or reversed polarity
Check the pinout and reconnect correctly
Input LED ON, but no output response
Output transistor damaged
Replace the optocoupler
No diode reading in the multimeter test
Internal LED open
Replace the optocoupler
Output always ON or always OFF
Wiring mistake or short circuit
Inspect and correct connections
The tester is not working or is showing unstable readings
Low battery or loose contacts
Replace the battery and secure connections
Frequently Asked Questions About Optocoupler Testing
⇥ Can an optocoupler be tested using only a multimeter?
Yes, but only partially. A multimeter can check the internal LED using diode mode, but it cannot fully verify whether the output side is working. It provides a basic check, not a complete functional test.
⇥ Why is a dedicated optocoupler tester better than a multimeter?
An optocoupler tester checks both the input LED and the output transistor simultaneously. It provides a clear pass-or-fail result instantly, making testing faster, easier, and more reliable.
⇥ What is the simplest way for beginners to test an optocoupler?
Using a small optocoupler tester circuit with LEDs is the easiest method. It requires no calculations or measurements and shows the result visually.
⇥ Can an optocoupler look normal but still be faulty?
Yes. Physical damage is rarely visible. The internal LED or photo-transistor may fail even when the package looks perfect. That is why functional optocoupler testing is necessary.
⇥ Is a breadboard test circuit enough for learning purposes?
Yes. A simple breadboard-based optocoupler testing circuit is good for understanding how the device works. However, for regular lab or repair work, a dedicated tester is more efficient.
Conclusion
This optocoupler tester circuit gives a simple and reliable way to check whether 4-pin and 6-pin optocouplers are working. The LED indicators clearly indicate whether the input side receives power and whether the output side responds correctly. The small, battery-powered design makes it useful for quick checks during assembly, learning, or repair work. This optocoupler tester circuit diagram focuses on basic working checks rather than detailed electrical testing. It helps detect faulty optocouplers early, saving time and preventing mistakes during installation. The tester delivers consistent, practical results without unnecessary complexity. Find practical, real-world Electronics Projects and step-by-step tutorials at this resource hub
Projects Using Optocoupler Isolation
These projects demonstrate how optocouplers provide safe electrical isolation between high-voltage AC circuits and low-voltage electronics. They are used for applications like zero-cross detection and AC power control in embedded systems.
An AI-based system that analyses ECG signals and vital parameters to predict heart disease, while also featuring an adaptive musical instrument that allows physically challenged individuals to create music through simple sensor-based interaction.
A Zero Crossing Detector circuit uses an op-amp (such as the LM741) as a comparator to detect when an AC signal crosses zero, converting the sine-wave input into a square-wave output for applications such as frequency measurement and phase control.
An Arduino-based AC fan speed controller that uses a TRIAC and zero-crossing detection to adjust the phase angle of the AC signal, allowing the fan speed to be varied using PWM and a potentiometer.
We love tinkering with our LiteWing ESP32 drone, and this time we gave it a simple but exciting upgrade, a WiFi camera module! With this addition, the drone can now stream live video while flying, perfect for hobby flights, aerial experimentation, or just having fun seeing the world from above.
On the technical side, the setup remains straightforward. The camera module uses its own built-in WiFi to stream video directly to a nearby device, while the LiteWing supplies stable power from its onboard battery during flight. Because the camera operates independently from the flight controller, the drone continues to fly normally while continuously transmitting live video. This build gives you real-time aerial footage without spending on a commercial drone with a camera.
Beyond its core functionality as a flying drone with a camera, the ESP32-based system can be further enhanced by integrating a Bluetooth speaker for wireless audio output. This upgrade enables the drone not only to capture live aerial footage but also to broadcast real-time voice announcements, making it suitable for surveillance, public addressing, or smart monitoring applications. For detailed guidance, refer to the project titled “How to Add a Loudspeaker to LiteWing ESP32 Drone for Wireless Audio Announcement”.
LiteWing ESP32 Drone with Camera – Overview
Parameter
Detail
Drone platform
LiteWing ESP32 Drone
Camera type
Dual WiFi camera module (toy-drone type)
Camera operating voltage
3.3 V (onboard regulator accepts up to 5 V)
Power source
1S LiPo battery (high C-rating recommended)
Data connection to flight controller
None required
Camera WiFi password (default)
12345678
Viewing app
WebCam / IP Camera (Android & iOS)
Control app
LiteWing drone control app (separate WiFi)
Key troubleshooting fix
Use higher C-rating battery to reduce video jitter
Components Required for the LiteWing ESP32 Drone Camera Build
This project requires only a compact flight platform with essential components for smooth aerial operation. The LiteWing ESP32 drone serves as the core system, paired with a dual WiFi camera module for real-time video streaming. A lightweight Li-Po battery powers the setup, while basic wiring and mounting accessories ensure secure assembly. Together, these components create a streamlined and efficient mini drone with camera designed for stable flight and live monitoring.
LiteWing ESP32 Drone
WiFi - Camera Module
1S LiPo Battery(Need High C Rating)
How the LiteWing ESP32 Drone with Camera Works
This drone system works through two separate pathways that don't interfere with each other. The LiteWing ESP32-Drone connects to your phone's Drone Control Application through its own Wi-Fi network, letting you fly the drone smoothly.
By splitting control and video into two separate channels, you get lag-free flying even while watching live video Feed. Use a high-C-rating battery to ensure the camera receives stable and sufficient power during flight. It’s like having two walkie-talkie frequencies, one for giving directions and one for receiving updates, so neither signal gets jammed or slowed down.
Workflow Summary:
» Channel 1 - Flight control - The LiteWing ESP32 has an in-built WiFi Access Point (AP). Your phone will connect to the LiteWing's drone control application to control throttle, roll, pitch, and yaw.
» Channel 2 - Live video - The WiFi camera module establishes its own Access Point (AP) and is completely separate from the LiteWing. You will connect to this Access Point (AP) through your phone using the WebCam application.
» No interference from either system - Because each system operates on its own WiFi Network, neither system's signal will slow down or jam the other system's signal; therefore, you will be able to fly with zero lag while simultaneously receiving smooth real-time video.
WiFi Camera Module Details
We used a dual-camera module from a toy drone. The module features two cameras, allowing you to switch between them easily, which is great for capturing different angles during flight. The cameras operate at 3.3V, but the module includes a built-in voltage regulator that can handle up to 5V, making it easy to power directly from the drone’s battery without additional circuitry.
Because the camera has its own WiFi connection, it can stream live video independently of the drone’s flight controller. This means you get continuous video even while the LiteWing ESP32 handles stable flight. Its compact design also makes it simple to mount on the drone without affecting weight or balance, making it a perfect fit for hobby video flights and experimentation.
WiFi Camera Module vs ESP32-CAM
Feature
Dedicated WiFi Camera Module
ESP32-CAM
Power requirement
Up to 5 V via built-in regulator
Stable 5 V, higher current draw
Integration complexity
Power only (VCC + GND)
Requires firmware configuration
Stability on 1S LiPo
Good with a high C-rating battery
Prone to resets under motor load
Onboard image processing
No
Yes
Best suited for
Simple live streaming builds
Projects requiring custom logic
Weight impact
Minimal – compact module
Slightly heavier with antenna
Hardware Connections
For this project, the hardware setup is very simple. We used the LiteWing ESP32 drone as the flying platform and mounted a dual WiFi camera module taken from a toy drone onto the frame. The camera does not require any data connection to the flight controller. We only connected the VCC of the camera module to the VBUS line and the GND to the common ground of the drone.
The system runs on a 1S LiPo battery, which powers both the drone and the camera. Proper mounting and secure wiring are important to keep the setup balanced during flight, and using a higher C-rating battery helps maintain stable performance.
How to Connect a Drone Camera to a Mobile Phone: Step-by-Step
Once the camera is powered on, it automatically creates its own WiFi access point. To view the live feed:
Step 1 ⇒ Connect your mobile phone to the camera’s WiFi network using the default password 12345678.
Step 2 ⇒ Download and open a compatible Web Cam app (many camera modules support apps like “IP Camera” or “WebCam” on Android/iOS).
Step 3 ⇒ In the app, click on the start button to start getting the live feed
Step 4 ⇒You should now see the live video feed streaming directly from the drone.
This setup keeps the camera completely independent of the LiteWing ESP32 flight controller, allowing smooth drone operation while continuously viewing live video. The key advantage of a dual-channel architecture for a drone with camera at hobby scale.
Working Demo
When the system is powered on, the LiteWing ESP32 manages the drone’s flight, which you can control through the LiteWing mobile app. At the same time, the WiFi camera powers up independently and creates its own network. To view the live video feed, you connect to the camera’s network using its dedicated viewing app. This setup lets the drone fly smoothly while streaming live video at the same time, showing how both systems work together.
Troubleshooting the LiteWing Drone Camera Setup
In some cases, noise or jitter may appear in the live video feed when the drone motors start operating. This issue can occur even if the camera footage looks clear while the drone is stationary. The disturbance is mainly caused by PWM switching noise from the motor control MOSFETs, which can introduce power fluctuations affecting the WiFi camera module.
To avoid this problem, it is recommended to use a battery with a higher C-rating, as it can supply stable current during rapid motor load changes. Using a higher C-rating battery significantly reduces power-related interference, resulting in smooth and jitter-free video streaming during flight.
Frequently Asked Questions
⇥ Can an ESP32-CAM be used instead of the WiFi camera module on the drone?
Yes, an ESP32-CAM can be used on the drone, but it requires more careful design compared to a standalone WiFi camera module. The ESP32-CAM needs a stable 5V supply and draws higher current, which can be difficult to maintain on a 1S LiPo battery when the motors are running, leading to possible resets, frame drops, or WiFi disconnections. It also adds extra processing load and power consumption to the system, increasing overall complexity. For simple live video streaming, a dedicated WiFi camera module is easier and more reliable, while the ESP32-CAM is better suited for projects that require onboard image processing or custom control logic.
⇥ Why does the drone’s video feed show noise or jitter during flight?
The video jitter or noise usually happens due to a voltage drop when the motors draw high current during flight. If the battery cannot supply enough current consistently, the voltage fluctuates, which can affect the WiFi camera module and cause instability in the video feed. Using a battery with a higher C-rating helps maintain stable voltage under load, reducing video noise and ensuring smoother transmission.
⇥ How to connect the drone camera to a mobile phone?
To connect the drone camera to a mobile phone, first power on the drone so that the WiFi camera module turns on. Once powered, the camera automatically creates its own WiFi access point. Open the WiFi settings on your mobile phone and connect to the camera’s WiFi network using the default password 12345678. After connecting, open the Web Cam app (available on the Play Store), and the live video feed will be displayed on your phone in real time.
LiteWing Drone Projects
Explore LiteWing drone tutorials covering programming, configuration, and experimental control methods using Python, Crazyflie tools, and ESP32-based hardware integrations.
A gesture-controlled drone using ESP32 and MPU6050 that translates hand movements into real-time drone flight commands through Python and the LiteWing library.
cfClient is a GUI tool used to connect, monitor, and control the LiteWing drone from a computer, allowing users to adjust flight settings, view real-time data, and configure input devices like game controllers.
“Everything starts with the product definition,” is how G. S. Madhusudan, CEO and Co-Founder of InCore Semiconductors, began walking us through the complex web of players that bring a chip to life. Given that we were on a Google Meet, he picked an IP camera chip as his example, because it essentially functions the same way. The list of things this chip does includes
