This design implements a USB security token powered by an STM32 microcontroller. The device is engineered for compactness and efficient PCB integration while ensuring robust security features. Key elements of the design include: - **Microcontroller Core:** A STM32F103T8U6 serves as the primary processing unit, handling USB communication and security protocols. - **USB Interface:** A USB-A plug provides connectivity to the host. Dedicated net portals ensure proper routing of the VBUS, D+, D–, and ground signals. - **Power Regulation:** A low-dropout regulator supplies a stable 3.3V operating voltage, ensuring low noise and proper current supply to the microcontroller and peripherals. - **Signal Conditioning and EMI Filtering:** An EMI filter is used to maintain signal integrity and reduce interference while preserving the security token’s functionality. - **Synchronous Elements:** A ceramic resonator is incorporated to provide a precise clock source for USB data transfer and microcontroller operations. - **Additional Components:** Surface-mount resistors, capacitors, and LED indicators are deployed to ensure proper conditioning, decoupling, and status feedback. Their compact 0402 packages facilitate a highly integrated design. - **Connectivity and Net Portals:** Custom net portals are used throughout the schematic to streamline connectivity and PCB layout, keeping the design modular and easy to modify. This USB security token is designed with industry-standard components and robust connectivity to ensure secure, reliable operation in portable security applications. #USBToken #STM32 #PCBDesign #SecurityTechnology #PortableSecurity #Microcontrollers #USBInterface #PowerRegulation #EMIProtection #CompactDesign

3D Camera Module is a scalable SPI enabled 4 camera array pinout for 3D photogrammetry reconstruction which uses I2C to connect between each module to expand camera capacity while keeping capture sequences in sync. It uses ATMega32U4 with its built in USB 2.0 for data transfer and camera array adjustments and capture as well as a micro SD card slot for local image storage. An interrupt logic pinout should be used on the SPI master module as capture command. Each module is powered via USB-C (5V) or barrel jack (12V regulated to 5V).

sEMG-DAQ is a wearable 6 channel data acquisition unit for capturing surface electromyographic (sEMG) signals from human arm muscles using SJ2-3593D jack connectors while conditioning, digitizing, processing and transmitting them as sEMG data to an external AI accelerated board through an SM12B-SRSS IDC connector where AI models are run for various applications including robotic control, muscle signals medical assessment and gesture recognition. The board leverages an INA125P instrumentation amplifier together with filter stages utilizing LM324QT op-amps for conditioning and an STM32G4A1VET6 microcontroller for the digitization, processing and data transmission of the signals. Since AI models can only be as good as the data, the design of such a DAQ is necessary to ensure clean, reliable and real-time data for AI applications requiring sEMG data. The board also has USB-FS and JTAG to cater for debugging. The power (5V) is fed through a screw terminal and is regulated by two LDK320AM LDO regulators to offer 5V, 3.3V and 1.8V to meet the requirements of various components on the board.

An ATtiny13 is more than sufficient to control almost any number of NeoPixels via an IR remote. The NeoController was originally developed as a tester for 800kHz NeoPixel strips. Since there was still so much flash left in the ATtiny13, an IR receiver was integrated so that some parameters can be controlled with an IR remote control. In this way, it is also suitable as a simple and cheap remote-controlled control unit for NeoPixels. Due to its small size (21.6mm x 11.4mm), it can be soldered directly to the LED strip without any problems. The power supply via a USB-C connection enables currents of up to 3A. There is still more than a third of the flash memory left for additional ideas.

The semgdaq board is a wearable 6 channel data acquisition unit for capturing surface electromyographic (sEMG) signals from human arm muscles using SJ2-3593D jack connectors while conditioning, digitizing, processing and feature extracting them then transmitting the feature data as vectors to an external AI accelerated board through an SM12B-SRSS IDC connector using 12C and UART communication protocals where AI models are run for various applications including robotic control, muscle signals medical assessment and gesture recognition. The feature vectors are comprised of onset detection, slope sign changes, autoregression coefficients and Short Time Fourier Transform magnitude spectrum data for each segment or window of the signals in real time. This vectors can be used as the basis for further feature extraction on more computationally resourceful hardware where machine learning algorthms can be employed for descision making in the applications mentioned earlier. The board leverages INA125P instrumentation amplifiers together with filter stages utilizing LM324QT op-amps for conditioning and an STM32G4A1VET6 microcontroller for the digitization, processing, feature extraction and data transmission. Since AI models can only be as good as the data, the design of such a DAQ is necessary to ensure clean, reliable and real-time data for AI applications requiring sEMG feature data. The board also has USB-FS and JTAG to cater for debugging and external flash memory to extend its data storage and processing capability. The power (5V) is fed through a screw terminal and is regulated by two LDK320AM LDO regulators to offer 5V, 3.3V and 1.8V to meet the requirements of various components on the board.

I2C to dual PWM controller. The LED-Warrior18, manufactured by Code Mercenaries, is an I2C to dual channel PWM LED driver specifically designed to provide seamless brightness control for LED applications. This component, available in SOIC8 package (LW18-S) and as a ready-to-use module (LW18-01MOD), offers dual 16-bit PWM outputs with a dimming range from 0.001% to 100% and operates at a PWM frequency of 730 Hz. It supports programmable period lengths for higher-frequency or lower-resolution operation and includes an 8-bit data to logarithmic mapping feature for smoother dimming operations with just 256 steps. The LED-Warrior18 is engineered for minimal external circuitry with a 5V power supply requirement, offering ease of use in various lighting applications. It also features a sync mode for synchronized control of multiple units and customizable power-on status settings, making it highly versatile for standalone operations or integrated systems. Additionally, custom variants of both the chip and module are available, catering to specific application needs. The module version, LW18-01MOD, simplifies integration by including terminal blocks and supporting up to 4A load sink current for each output. The LED-Warrior18 stands out for its straightforward interface and operational flexibility, providing a comprehensive solution for advanced LED dimming and control projects.

1. Overview: The Pundit pendant is a wearable AI transcription assistant. An innovative device designed to seamlessly integrate into daily activities, providing real-time transcription and note-taking capabilities. Combining advanced AI algorithms with state-of-the-art hardware components, the device offers crystal clear audio recording, durable construction, and convenient features such as cloud synchronization, weatherproofing, and a vibrant display for animations and expressions. 2. Hardware Specifications: * Rechargeable Battery: Lithium-ion battery providing up to 150 hours of continuous operation. * Construction: Durable aluminum body ensuring longevity and protection against wear and tear. * Audio Quality: High-fidelity microphone array for clear and accurate transcription, with noise cancellation technology. * Weatherproofing: Sealed construction to withstand various weather conditions, making it suitable for outdoor use. * Versatile Mounting: Equipped with a magnetic clasp for easy attachment to clothing or accessories. * Connectivity: Wi-Fi and Bluetooth connectivity for seamless data transfer and integration with other devices. * Charging: USB-C port for fast and convenient charging, with support for various power sources. * Input Microphone Array: Multiple microphones strategically placed for optimal audio capture and transcription accuracy. * Display: Colorful screen for displaying animations, expressions, and status indicators, enhancing user interaction and personalization. 3. Software Features: * Real-time Transcription: Utilizes AI algorithms for instant transcription of spoken words into text, with high accuracy. * Note-taking: Automatically creates and organizes notes based on conversations, timestamps, and contextual cues. * Audio Recording: One-touch button for initiating audio recording, with options for manual or automatic saving. * Cloud Synchronization: Syncs transcription data to the cloud for easy access and retrieval from any device. * Speech Recognition: Advanced speech recognition technology for identifying speakers and distinguishing between multiple voices. * Language Support: Multilingual support for transcription and note-taking in various languages. * Customization: User-configurable settings for adjusting transcription preferences, language models, and display animations. * Security: Encryption and authentication protocols to ensure the privacy and security of transcription data. 4. Dimensions and Weight: * Dimensions: Compact and lightweight design for comfortable wearability. * Weight: Minimal weight to prevent discomfort during prolonged use. 5. Compatibility: * Operating Systems: Compatible with iOS, Android, and other major operating systems. * Applications: Integration with popular productivity and communication apps for seamless workflow management. 6. Warranty and Support: * Warranty: Manufacturer's warranty covering defects in materials and workmanship. * Support: Dedicated customer support for technical assistance, troubleshooting, and software updates. 7. Target Market: * Professionals: Ideal for professionals in various industries, including journalists, researchers, students, and business professionals. * Outdoor Enthusiasts: Suitable for outdoor activities such as hiking, camping, and fieldwork where reliable transcription and note-taking are essential. * Everyday Users: Provides convenience and efficiency for everyday tasks, such as meetings, lectures, and personal reminders. 8. Conclusion: The Wearable AI Transcription Assistant sets a new standard for wearable technology, offering unmatched transcription and note-taking capabilities in a compact and durable package. With its advanced features, seamless connectivity, vibrant display, and user-friendly design, it is poised to revolutionize how we capture and manage information in our daily lives while adding a touch of personality and fun with customizable animations and expressions.

24–30 V to 12 V / 100 W Single-Layer Synchronous Buck Converter with Robust Protection

A synchronous sequential circuit that governs an alarm

Welcome to your new project. Imagine what you can build here.

Welcome to your new project. Imagine what you can build here.

Welcome to your new project. Imagine what you can build here..

Biskuit is a compact, ESP32-S3-powered wearable device designed for real-time transcription and effortless note-taking. Featuring a 3-microphone array and wireless communication to sync to to the cloud instantly.

sEMG-DAQ is a wearable 6 channel data acquisition unit for capturing surface electromyographic (sEMG) signals from human arm muscles using SJ2-3593D jack connectors while conditioning, digitizing, processing and transmitting them as sEMG data to an external AI accelerated board through an SM12B-SRSS IDC connector where AI models are run for various applications including robotic control, muscle signals medical assessment and gesture recognition. The board leverages an INA125P instrumentation amplifier together with filter stages utilizing LM324QT op-amps for conditioning and an STM32G4A1VET6 microcontroller for the digitization, processing and data transmission of the signals. Since AI models can only be as good as the data, the design of such a DAQ is necessary to ensure clean, reliable and real-time data for AI applications requiring sEMG data. The board also has USB-FS and JTAG to cater for debugging. The power (5V) is fed through a screw terminal and is regulated by two LDK320AM LDO regulators to offer 5V, 3.3V and 1.8V to meet the requirements of various components on the board.

Biskuit is a compact, ESP32-S3-powered wearable device designed for real-time transcription and effortless note-taking. Featuring a 3-microphone array and wireless communication to sync to to the cloud instantly.

3D Camera Module is a scalable SPI enabled 4 camera array pinout for 3D photogrammetry reconstruction which uses I2C to connect between each module to expand camera capacity while keeping capture sequences in sync. It uses ATMega32U4 with its built in USB 2.0 for data transfer and camera array adjustments and capture as well as a micro SD card slot for local image storage. An interrupt logic pinout should be used on the SPI master module as capture command. Each module is powered via USB-C (5V) or barrel jack (12V regulated to 5V).

Haptic Glove Controller Board NUCLEO-F411RE based Fixed Servo Connections to match standard servo wiring Revised footprint of 2n3904s transistors since base and emitter footprint were swapped Larger power traces Swapped SDO and SDI of SPI Lines to the FPC connector so it matches with peripheral.

So what is an ESC? Well, electronic speed controllers are used to control brushless motors, in thisc ase the motor has a triple phase input. To control this input, the ESC must apply a special sequence of LOWs and HIGHs signals in a predefined order. It has to conmutate very fast and by taht rotate the rotor of the motor. In this tutorial we will see how to control the rotation, the speed, detect the BEMF and by that know when to make the switch to the next step of the sequence. So this is a sensorless brushless motor speed controller since it uses no sensor to detect the rotor position. We will learn: - The schematic and why we need each part - Triple phase MOSFET bridge control - BEMF detection and 0 cross - Interrumprions and internal comparator of ATMEGA328 - PWM control

Haptic Glove Controller Board NUCLEO-F411RE based Fixed Servo Connections to match standard servo wiring Revised footprint of 2n3904s transistors since base and emitter footprint were swapped Larger power traces Swapped SDO and SDI of SPI Lines to the FPC connector so it matches with peripheral.

3D Camera Module is a scalable SPI enabled 4 camera array pinout for 3D photogrammetry reconstruction which uses I2C to connect between each module to expand camera capacity while keeping capture sequences in sync. It uses ATMega32U4 with its built in USB 2.0 for data transfer and camera array adjustments and capture as well as a micro SD card slot for local image storage. An interrupt logic pinout should be used on the SPI master module as capture command. Each module is powered via USB-C (5V) or barrel jack (12V regulated to 5V).

Automatic 3-channel video switcher using 3 video sync separators and max4545 video switch.

sEMG-DAQ is a wearable 6 channel data acquisition unit for capturing surface electromyographic (sEMG) signals from human arm muscles using SJ2-3593D jack connectors while conditioning, digitizing, processing and transmitting them as sEMG data to an external AI accelerated board through an SM12B-SRSS IDC connector where AI models are run for various applications including robotic control, muscle signals medical assessment and gesture recognition. The board leverages an INA125P instrumentation amplifier together with filter stages utilizing LM324QT op-amps for conditioning and an STM32G4A1VET6 microcontroller for the digitization, processing and data transmission of the signals. Since AI models can only be as good as the data, the design of such a DAQ is necessary to ensure clean, reliable and real-time data for AI applications requiring sEMG data. The board also has USB-FS and JTAG to cater for debugging. The power (5V) is fed through a screw terminal and is regulated by two LDK320AM LDO regulators to offer 5V, 3.3V and 1.8V to meet the requirements of various components on the board.

Advanced health smartwatch platform with multimodal sensing, on-device AI, Wi-Fi plus cellular/eSIM connectivity, secure cloud sync, OTA firmware updates, and automatic emergency outreach over cellular/eSIM for fall and critical-event protection.

Biskuit is a compact, ESP32-S3-powered wearable device designed for real-time transcription and effortless note-taking. Featuring a 3-microphone array and wireless communication to sync to to the cloud instantly.

Biskuit is a compact, ESP32-S3-powered wearable device designed for real-time transcription and effortless note-taking. Featuring a 3-microphone array and wireless communication to sync to to the cloud instantly.