This project designs a Linux Single Board Computer using STM32MP157FAC1, featuring DDR memory, a power management IC, USB and SD card interfaces, and essential user controls, aimed at versatile embedded applications.

The Texas Instruments MSP430FR604x and MSP430FR603x family comprises highly integrated ultrasonic sensing and measurement system-on-chips (SoCs) designed specifically for water and heat metering applications. The featured components, including MSP430FR6047, MSP430FR60471, MSP430FR6045, MSP430FR6037, MSP430FR60371, and MSP430FR6035, deliver best-in-class ultrasonic water flow measurement with ultra-low power consumption. These microcontrollers excel with an active mode current consumption of approximately 120 µA/MHz and a standby mode power draw as low as 450 nA with a real-time clock (RTC) enabled. Key functionalities include a high-precision differential time-of-flight (dTOF) accuracy of less than 25 ps, integrated analog front-end, programmable pulse generation (PPG), and an analog comparator. They also interface directly with standard ultrasonic sensors up to 2.5 MHz and feature up to 256KB FRAM, robust RAM options, and integrated LCD drivers for up to 264 segments. The embedded low-energy accelerator (LEA) enhances digital signal processing capabilities, making these components ideal for battery-powered metering solutions. Peripherals include multiple enhanced serial communication interfaces, high-performance ADCs, DMA controllers, and a suite of timers and encryption modules. These features combine to offer a powerful solution for high-accuracy, low-cost, and ultra-low-power metering applications.

This project designs a Linux Single Board Computer using STM32MP157FAC1, featuring DDR memory, a power management IC, USB and SD card interfaces, and essential user controls, aimed at versatile embedded applications.

IP65 Marine/Industrial Embedded Computer with Raspberry Pi CM5 and Integrated Power Resilience

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.

This project designs a Linux Single Board Computer using STM32MP157FAC1, featuring DDR memory, a power management IC, USB and SD card interfaces, and essential user controls, aimed at versatile embedded applications.

The Ariel AI Chip, a pioneering component in the field of artificial intelligence hardware, integrates advanced features designed to enhance computational efficiency and AI processing capabilities. This chip is distinguished by its utilization of a quad-core CPU with a clock speed of 2GHz, operating on a radical transistor architecture that promises significant improvements in speed and power efficiency. Key components that constitute the Ariel AI Chip include a DC power supply with a 5V output (DCPS-5V), NPN transistors (NPN-TRANS-001 and NPN-TRANS-002) that serve as the fundamental switching elements, precision resistors (RES-1K and RES-1K-002) each with a resistance of 1kΩ, and a capacitor (CAP-10UF) rated at 10μF to stabilize voltage and filter noise. This chip is designed for integration into systems requiring advanced AI capabilities, offering a comprehensive solution for developers looking to leverage machine learning and artificial intelligence in their applications. With its innovative architecture and component selection, the Ariel AI Chip stands out as a versatile and powerful tool for a wide range of AI applications, from embedded systems to more complex computational platforms.

This project designs a Linux Single Board Computer using STM32MP157FAC1, featuring DDR memory, a power management IC, USB and SD card interfaces, and essential user controls, aimed at versatile embedded applications.

This project designs a Linux Single Board Computer using STM32MP157FAC1, featuring DDR memory, a power management IC, USB and SD card interfaces, and essential user controls, aimed at versatile embedded applications.

This project designs a Linux Single Board Computer using STM32MP157FAC1, featuring DDR memory, a power management IC, USB and SD card interfaces, and essential user controls, aimed at versatile embedded applications.

Power management board for a low-power embedded system with solar panel, 1S LiPo battery, and USB 2.0 inputs; charges the battery from available external power, powers the system from battery when external sources are absent, prioritizes USB over solar, and generates selectable boosted 12V or 5V output plus a regulated 3.3V rail.

Power management board for a low-power embedded system with solar panel, 1S LiPo battery, and USB 2.0 inputs; charges the battery from available external power, powers the system from battery when external sources are absent, prioritizes USB over solar, and generates selectable boosted 12V or 5V output plus a regulated 3.3V rail.

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.

Single-subsystem 3.3 V synchronous buck-boost regulator reference built around the TI TPS63802DLAR in a 10-pin VSON package. The design accepts a VBUS input rail into VIN, uses a Bourns SRP4020TA-4R7M 4.7 µH power inductor between L1/L2, and generates PP3V3 from the adjustable TPS63802 output path. The TPS63802 metadata lists a 1.3 V to 5.5 V input range, 2 A output current, selectable switching-frequency modes around 1.4 MHz to 2.1 MHz, and -40 °C to +125 °C junction operation. Support circuitry includes 22 µF and 1 µF ceramic input/output capacitors, a 511 kΩ / 91 kΩ feedback divider for the PP3V3_FB node, a VBUS-derived enable divider using 93.1 kΩ and 100 kΩ resistors, MODE tied to GND, and a 100 kΩ pull-up from PP3V3 to the power-good output. Intended as a reusable compact 3.3 V buck-boost power-supply module for USB, battery, portable, IoT, or embedded sensor designs.

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.

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.

ESP32 /eMMC Integration with Bidirectional Level Shifting Project Overview: This project aims to integrate an ESP32 microcontroller with an eMMC (embedded Multi Media Card) storage module to create a robust data processing and storage solution. The system utilizes bidirectional level shifting to ensure seamless communication between the 3.3V logic of the ESP32 and the 1.8V logic of the eMMC, enabling efficient data handling and processing. Objectives: Data Storage and Processing: Leverage the high-speed capabilities of the eMMC for data storage while offloading processing tasks from the ESP32 to enhance overall system performance. Voltage Level Compatibility: Implement a bidirectional level shifting solution to facilitate communication between the ESP32 and eMMC, ensuring signal integrity and compatibility across different voltage levels. Modular Design: Create a modular and scalable design that can be easily adapted for various applications, including IoT devices, data logging systems, and embedded applications. Key Components: ESP32 Microcontroller: A powerful microcontroller with integrated Wi-Fi and Bluetooth capabilities, ideal for IoT applications. eMMC Storage Module: A high-speed storage solution that provides ample memory for data-intensive applications. Bidirectional Level Shifter: A 20-channel level shifter (74LVC4245 and TXB0104D) to convert signals between 1.8V and 3.3V, ensuring reliable communication between the ESP32 and eMMC. Power Management: Utilize a MIC5205 LDO voltage regulator to step down the 3.3V supply to 1.8V for the eMMC, ensuring stable power delivery. Implementation Steps: Circuit Design: Design the circuit schematic, including connections for the ESP32, eMMC, level shifter, and power management components. PCB Layout: Create a PCB layout that optimizes trace lengths for high-speed signals, ensuring proper length matching and minimizing noise. Firmware Development: Develop firmware for the ESP32 to handle data reading, writing, and processing tasks, as well as managing communication with the eMMC. Testing and Validation: Conduct thorough testing to validate the functionality of the system, ensuring reliable data transfer and processing capabilities. Expected Outcomes: A fully functional system that demonstrates the integration of the ESP32 with eMMC storage, showcasing efficient data handling and processing. A modular design that can be adapted for various applications, providing a foundation for future projects in IoT and embedded systems.

This project designs a Linux Single Board Computer using STM32MP157FAC1, featuring DDR memory, a power management IC, USB and SD card interfaces, and essential user controls, aimed at versatile embedded applications.

Seeed Studio XIAO nRF52840 Sense is carrying Bluetooth 5.0 wireless capability and is able to operate with low power consumption. Featuring onboard IMU and PDM, it can be your best tool for embedded Machine Learning projects. #SeeedStudio #xiao

This project designs a Linux Single Board Computer using STM32MP157FAC1, featuring DDR memory, a power management IC, USB and SD card interfaces, and essential user controls, aimed at versatile embedded applications.

The Atmel® | SMART SAM9260, manufactured by Atmel, is an ARM-based Embedded Microprocessor Unit (MPU), integrating the ARM926EJ-STM processor operating at 180 MHz. This MPU includes substantial on-chip memory and extensive peripherals, including an Ethernet MAC, USB Device and Host Ports, along with various standard interfaces such as USART, SPI, TWI, Timer Counters, and MultiMedia Card Interface. Architected on a 6-layer matrix delivering a maximum internal bandwidth of six 32-bit buses, it supports external 32-bit bus interfaces for SDRAM, static memories, CompactFlash, and SLC NAND Flash with ECC. The SAM9260 is available in 217-ball LFBGA and 208-pin PQFP packages. Key features include 8 Kbytes each of data and instruction cache, integrated MMU, two internal 4-Kbyte SRAMs, a 32-Kbyte ROM with bootloader, 22 Peripheral DMA channels, various power-on reset modes, two programmable clock signals, advanced interrupt controller, and multiple power management options for optimized performance and energy efficiency.

Seeed Studio XIAO nRF52840 Sense is carrying Bluetooth 5.0 wireless capability and is able to operate with low power consumption. Featuring onboard IMU and PDM, it can be your best tool for embedded Machine Learning projects.