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

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

1. Overview: The Biskuit 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.

Purpose: Design a schematic for a wearable ECG signal monitoring device that is compact and sends readings via Bluetooth. Components: Arduino Nicla Sense ME: To serve as the central processing unit of the device. MCP3911: To capture the ECG signal. AD8606: To amplify the ECG signal. Battery: To power the device with a consideration for the battery to be rechargeable via a Type-C port. Specifications: The device must be small and wearable, like the one shown in the image provided. It should have Bluetooth capabilities for transmitting data. Include a charging circuit for the battery using a Type-C connection. Enhancements: Suggest potential improvements in design for efficiency, size reduction, or additional features. Constraints: The size and shape should be as unobtrusive as possible for ease of wear. Note: Please advise on the inclusion of any additional components that may be necessary for the operation, stabilization, or improvement of signal quality.

Purpose: Design a schematic for a wearable ECG signal monitoring device that is compact and sends readings via Bluetooth. Components: Arduino Nicla Sense ME: To serve as the central processing unit of the device. MCP3911: To capture the ECG signal. AD8606: To amplify the ECG signal. Battery: To power the device with a consideration for the battery to be rechargeable via a Type-C port. Specifications: The device must be small and wearable, like the one shown in the image provided. It should have Bluetooth capabilities for transmitting data. Include a charging circuit for the battery using a Type-C connection. Enhancements: Suggest potential improvements in design for efficiency, size reduction, or additional features. Constraints: The size and shape should be as unobtrusive as possible for ease of wear. Note: Please advise on the inclusion of any additional components that may be necessary for the operation, stabilization, or improvement of signal quality.

Product Type: Wearable AI pendant Primary Function: Records audio, generates transcripts, and organizes information about daily interactions User Interaction: Input: Activation button Output: RGB LED ring, Bluetooth link to phone Key Features: Audio Recording: Activated by button press Transcription: Converts audio to text Sentiment Analysis: Embedded AI evaluates sentiment Information Management: Filters essential information and action items Technical Specifications Form Factor: Wearable pendant Display: RGB LED ring around the edge Sensors: 2 Microphones 1 Button Connectivity: Bluetooth for phone linkage Wi-Fi USB-C for charging Wireless Protocol: Wi-Fi, Bluetooth Battery Type: LiPo 2000 mAh Battery Life: 6 hours of continuous use Charging Method: USB-C Operating Voltage: 3.3V Operating Conditions: Temperature Range: -10°C to 70°C Humidity: 10 to 90% Software: Python for AI and processing Compliance: RoHS, FCC, CE Reliability: 20,000 hrs Life Cycle Expectancy: 10 years AI Capabilities Speech to Text Recognition: Converts audio input to written text Embedded AI Sentiment Analysis: Evaluates the mood or sentiment expressed in the text Essential Information Filtering: Identifies and segregates crucial data and actionable items Power Consumption and Efficiency Power consumption must align with battery capacity to ensure 6 hours of continuous operational use.

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.

1. Overview: The Biskuit 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.

Product Type: Wearable AI pendant Primary Function: Records audio, generates transcripts, and organizes information about daily interactions User Interaction: Input: Activation button Output: RGB LED ring, Bluetooth link to phone Key Features: Audio Recording: Activated by button press Transcription: Converts audio to text Sentiment Analysis: Embedded AI evaluates sentiment Information Management: Filters essential information and action items Technical Specifications Form Factor: Wearable pendant Display: RGB LED ring around the edge Sensors: 2 Microphones 1 Button Connectivity: Bluetooth for phone linkage Wi-Fi USB-C for charging Wireless Protocol: Wi-Fi, Bluetooth Battery Type: LiPo 2000 mAh Battery Life: 6 hours of continuous use Charging Method: USB-C Operating Voltage: 3.3V Operating Conditions: Temperature Range: -10°C to 70°C Humidity: 10 to 90% Software: Python for AI and processing Compliance: RoHS, FCC, CE Reliability: 20,000 hrs Life Cycle Expectancy: 10 years AI Capabilities Speech to Text Recognition: Converts audio input to written text Embedded AI Sentiment Analysis: Evaluates the mood or sentiment expressed in the text Essential Information Filtering: Identifies and segregates crucial data and actionable items Power Consumption and Efficiency Power consumption must align with battery capacity to ensure 6 hours of continuous operational use.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

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.

This is a smart watch project based on E73-2G4M04S1A module with SoC nRF52810 on board. OLED display and coin battery #wearable #nRF52810 #E73 #Ebyte #BLE #referenceDesign

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

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.

Wearable EMG acquisition PCB with 8 differential biopotential channels, BLE/USB MCU, USB-C LiPo charging, 3.3V buck regulation, and 2.4GHz chip antenna path.

This is a smart watch project based on E73-2G4M04S1A module with SoC nRF52810 on board. OLED display and coin battery #wearable #nRF52810 #E73 #Ebyte #BLE #referenceDesign

BLE wearable flex PCB with LiPo charging, PPG plus skin temperature, 3-channel EMG, IMU, and piezo impact sensing for a smart compression sleeve

ESP32 Wearable Health & GPS Tracker with Biometric Security, TFT Display, and Enhanced Power & Data Protection

Audio-first ESP32-S3 wearable PCB. 44 × 26 × 1.0 mm. ESP32-S3-MINI-1 + INMP441 + TP4056 + DW01A/FS8205A + ME6211C33. 800mAh 802545 LiPo. Native USB on GPIO19/20. BLE audio wearable.

Cow health-monitoring wearable PCB for a cow-mounted device. Rear strap electronics target 20-25 g and front sensing assembly target about 15 g. Uses an ESP32-based sensor controller, 200 mAh LiPo battery, battery charging circuitry, and interfaces for ammonia, methane, IR temperature, and saliva sensing. Design must tolerate moisture, mucus, debris, vibration, fur contact, and tongue/lick exposure while remaining compact and lightweight for wearable use.

Wearable closed-loop ultrasonic monitoring and transcutaneous neuromodulation system based on ESP32-C3, powered from a 7.4 V 1000 mAh LiPo battery with TP4056 charging, MT3608 boost conversion, AMS1117-3.3 regulation, JSN-SR04T ultrasonic sensing, LED and buzzer alerts through a BC547 driver, and a reserved neuromodulation interface for future integration.

Compact wearable smart cat collar PCB focused on ultra-low power, miniaturized size, curved-edge waterproof-friendly mechanical fit, GNSS tracking, motion sensing, RFID compatibility, Li-ion charging, and robust mass-production readiness.

Wearable health device prototype schematic with ECG sensing via AD8232, motion sensing via BNO085 or BMI270 IMU breakout, on-board processing using TI TM4C123G LaunchPad or MSPM0G3507 LaunchPad, optional ESP8266 Wi-Fi, LiPo battery charging with MCP73831, regulated 3.3 V power from TPS63031 buck-boost or AP2112 LDO prototype option, and user interfaces including electrode connector, JST battery connector, programming header, and optional on/off switch.

ESP32-S3 Wearable Audio Streaming Pendant (USB-C + LiPo + I2S Mic + microSD + OLED)

8-Channel Wearable BLE5 Brain–Computer Interface with 24-bit Biopotential AFE and Cross-Platform SDKs

Silent Gaude: 10 mm 4‑Layer ESP32-S3 LTE/GNSS Wearable Bracelet

Wearable Multi-Sensor ESP32 Platform

Ultra-Compact 20x10 mm Wearable BLE Finger Gesture PCB with ESP32-C3, IMU, Li-Po Charging, and Flex Sensor Support

ESP32-WROOM-32 Wearable Health Monitor with MAX30102, MPU6050, OLED, Camera Interface, and Advanced Power Management

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.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

Product Type: Wearable AI pendant Primary Function: Records audio, generates transcripts, and organizes information about daily interactions User Interaction: Input: Activation button Output: RGB LED ring, Bluetooth link to phone Key Features: Audio Recording: Activated by button press Transcription: Converts audio to text Sentiment Analysis: Embedded AI evaluates sentiment Information Management: Filters essential information and action items Technical Specifications Form Factor: Wearable pendant Display: RGB LED ring around the edge Sensors: 2 Microphones 1 Button Connectivity: Bluetooth for phone linkage Wi-Fi USB-C for charging Wireless Protocol: Wi-Fi, Bluetooth Battery Type: LiPo 2000 mAh Battery Life: 6 hours of continuous use Charging Method: USB-C Operating Voltage: 3.3V Operating Conditions: Temperature Range: -10°C to 70°C Humidity: 10 to 90% Software: Python for AI and processing Compliance: RoHS, FCC, CE Reliability: 20,000 hrs Life Cycle Expectancy: 10 years AI Capabilities Speech to Text Recognition: Converts audio input to written text Embedded AI Sentiment Analysis: Evaluates the mood or sentiment expressed in the text Essential Information Filtering: Identifies and segregates crucial data and actionable items Power Consumption and Efficiency Power consumption must align with battery capacity to ensure 6 hours of continuous operational use.

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.

Product Type: Wearable AI pendant Primary Function: Records audio, generates transcripts, and organizes information about daily interactions User Interaction: Input: Activation button Output: RGB LED ring, Bluetooth link to phone Key Features: Audio Recording: Activated by button press Transcription: Converts audio to text Sentiment Analysis: Embedded AI evaluates sentiment Information Management: Filters essential information and action items Technical Specifications Form Factor: Wearable pendant Display: RGB LED ring around the edge Sensors: 2 Microphones 1 Button Connectivity: Bluetooth for phone linkage Wi-Fi USB-C for charging Wireless Protocol: Wi-Fi, Bluetooth Battery Type: LiPo 2000 mAh Battery Life: 6 hours of continuous use Charging Method: USB-C Operating Voltage: 3.3V Operating Conditions: Temperature Range: -10°C to 70°C Humidity: 10 to 90% Software: Python for AI and processing Compliance: RoHS, FCC, CE Reliability: 20,000 hrs Life Cycle Expectancy: 10 years AI Capabilities Speech to Text Recognition: Converts audio input to written text Embedded AI Sentiment Analysis: Evaluates the mood or sentiment expressed in the text Essential Information Filtering: Identifies and segregates crucial data and actionable items Power Consumption and Efficiency Power consumption must align with battery capacity to ensure 6 hours of continuous operational use.

Product Type: Wearable AI pendant Primary Function: Records audio, generates transcripts, and organizes information about daily interactions User Interaction: Input: Activation button Output: RGB LED ring, Bluetooth link to phone Key Features: Audio Recording: Activated by button press Transcription: Converts audio to text Sentiment Analysis: Embedded AI evaluates sentiment Information Management: Filters essential information and action items Technical Specifications Form Factor: Wearable pendant Display: RGB LED ring around the edge Sensors: 2 Microphones 1 Button Connectivity: Bluetooth for phone linkage Wi-Fi USB-C for charging Wireless Protocol: Wi-Fi, Bluetooth Battery Type: LiPo 2000 mAh Battery Life: 6 hours of continuous use Charging Method: USB-C Operating Voltage: 3.3V Operating Conditions: Temperature Range: -10°C to 70°C Humidity: 10 to 90% Software: Python for AI and processing Compliance: RoHS, FCC, CE Reliability: 20,000 hrs Life Cycle Expectancy: 10 years AI Capabilities Speech to Text Recognition: Converts audio input to written text Embedded AI Sentiment Analysis: Evaluates the mood or sentiment expressed in the text Essential Information Filtering: Identifies and segregates crucial data and actionable items Power Consumption and Efficiency Power consumption must align with battery capacity to ensure 6 hours of continuous operational use.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

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.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.

This is a smart watch project based on E73-2G4M04S1A module with SoC nRF52810 on board. OLED display and coin battery #wearable #nRF52810 #E73 #Ebyte #BLE #referenceDesign

The Biskuit pendant is a WiFi/BLE Enabled wearable AI Diary which captures Images and sounds periodically and creates an audio visual timeline of your day so that you don't forget anything.