SAP v2: Modular Three-Board Environmental Monitoring & Control System

Nice — you can do a clean pulse + latch using a single quad Schmitt-NAND chip: 74HC132 (or 74LVC132 for 3.3 V systems). The HC132 contains four 2-input NAND gates with Schmitt inputs so you can both clean a noisy SYN480R DATA line and build an SR latch (NAND SR is active-LOW) inside one package. Only a few passives and a driver transistor are needed. Below is a ready-to-build recipe (parts, wiring, explanation, tuning tips, and an ASCII schematic) — no extra logic ICs required. Parts (per latch) 1 × 74HC132 (quad 2-input NAND with Schmitt inputs). If your system is 3.3 V use 74LVC132 / 74HC132 rated for 3.3 V. Rin = 47 kΩ (input series) Cfilter = 10 nF (input RC to ground) — tweak for debounce/clean time Rpulldown = 100 kΩ (pull-down at input node, optional) Rpullup = 100 kΩ (pull-up for active-LOW R input so reset is idle HIGH) Rbase = 10 kΩ, Q = 2N2222 (NPN) or small N-MOSFET (2N7002) to drive your load Diode for relay flyback (1N4001) if you drive a coil Optional small cap 0.1 µF decoupling at VCC of IC Concept / how it works (short) Use Gate1 (G1) of 74HC132 as a Schmitt inverter by tying its two inputs together and feeding a small RC filter from SYN480R.DATA. This removes HF noise and provides a clean logic transition. Because it's a NAND with tied inputs its function becomes an inverter with Schmitt behavior. Use G2 & G3 as the cross-coupled NAND pair forming an SR latch (active-LOW inputs S̄ and R̄). A low on S̄ sets Q = HIGH. A low on R̄ resets Q = LOW. Wire the cleaned/inverted output of G1 to S̄. A valid received pulse (DATA high) produces a clean LOW on S̄ (because G1 inverts), setting the latch reliably even if the pulse is brief. R̄ is your reset input (pushbutton, HT12D VT, MCU line, etc.) — idle pulled HIGH. Q drives an NPN/MOSFET to switch your load (relay, LED, etc.). Recommended wiring (pin mapping, assume one chip; use datasheet pin numbers) I’ll refer to the 4 gates as G1, G2, G3, G4. Use G4 optionally for additional conditioning or to build a toggler later. SYN480R.DATA --- Rin (47k) ---+--- Node A ---||--- Cfilter (10nF) --- GND | Rpulldown (100k) --- GND (optional, keeps node low) Node A -> both inputs of G1 (tie inputs A and B of Gate1 together) G1 output -> S̄ (S_bar) (input1 of Gate2) Gate2 (G2): inputs = S̄ and Q̄ -> output = Q Gate3 (G3): inputs = R̄ and Q -> output = Q̄ R̄ --- Rpullup (100k) --- VCC (reset is idle HIGH; pull low to reset) (optional) R̄ can be wired to a reset pushbutton to GND or to an MCU pin Q -> Rbase (10k) -> base of 2N2222 (emitter GND; collector to one side of relay coil) Other side of relay coil -> +V (appropriate coil voltage) Diode across coil If you prefer MOSFET low side switching: Q -> gate resistor 100Ω -> gate of 2N7002 2N7002 source -> GND ; drain -> relay coil low side

make this for me now # Device Summary & Specification Sheet ## 1. Overview A rugged, Arduino-Uno-and-Raspberry-Pi-style single-board micro-PC featuring: - Smartphone-class CPU (Snapdragon 990) - USB-C Power Delivery + 4×AA alkaline backup + ambient-light harvester - On-board Arduino-Uno-compatible ATmega328P - External NVMe SSD via USB3 bridge & optional Thunderbolt 3 eGPU support - 5× USB 3.0 ports, HDMI in/out, Gigabit Ethernet & SFP fiber, Wi-Fi, Bluetooth, LoRa - 0.96″ OLED status display, 3.5 mm audio jack with codec --- ## 2. Key Specifications | Category | Specification | |--------------------|-------------------------------------------------------------------------------| | CPU | Snapdragon 990, octa-core up to 2.84 GHz | | Memory | 6 GB LPDDR4x DRAM | | Storage Interface | PCIe Gen3 ×4 → M.2 NVMe + USB 3.1 Gen1 bridge | | MCU | ATmega328P (Arduino-Uno-compatible) | | Power Input | USB-C PD up to 20 V/5 A; 4×AA alkaline backup; ambient-light photodiode boost | | Power Rails | 12 V, 5 V, 3.3 V, 1.8 V, 1.2 V via buck/buck-boost regulators | | USB Hub | 5× USB 3.0 downstream ports | | Display | 0.96″ 128×64 OLED via I²C/SPI | | Networking | 1 × Gigabit RJ45; 1 × SFP fiber; Wi-Fi 802.11ac + Bluetooth; LoRa SX1276 | | Video I/O | HDMI 2.0 input (RX) & output (TX) | | Audio | 3.5 mm jack + TLV320AIC3101 codec; Bluetooth audio | | Form Factor | Raspberry Pi–style header + Arduino-Uno shield headers; 4× standoff mounts | --- ## 3. Complete Parts List | Part | Function | Qty | |------------------------------------------------------------------------------------------------|-----------------------------------------------|-----| | [Snapdragon 990](https://www.flux.ai/search?type=components&q=Snapdragon%20990) | Main application CPU | 1 | | [LPDDR4x DRAM](https://www.flux.ai/search?type=components&q=LPDDR4x%20DRAM) | System memory | 1 | | [eMMC 64GB](https://www.flux.ai/search?type=components&q=eMMC%2064GB) | On-board storage | 1 | | [M.2 NVMe Connector](https://www.flux.ai/search?type=components&q=M.2%20NVMe%20Connector) | External SSD interface | 1 | | [JMS583](https://www.flux.ai/search?type=components&q=JMS583) | PCIe→USB 3.1 bridge for NVMe | 1 | | [Titan Ridge](https://www.flux.ai/search?type=components&q=Titan%20Ridge) | Thunderbolt 3/eGPU controller | 1 | | [STUSB4500](https://www.flux.ai/search?type=components&q=STUSB4500) | USB-C Power-Delivery controller | 1 | | [LTC4412](https://www.flux.ai/search?type=components&q=LTC4412) | Ideal-diode OR-ing | 1 | | [LTC3108](https://www.flux.ai/search?type=components&q=LTC3108) | Ambient-light (solar) energy harvester | 1 | | [Battery Holder 4×AA](https://www.flux.ai/search?type=components&q=Battery%20Holder%204xAA) | Alkaline backup power | 1 | | [TPS53318](https://www.flux.ai/search?type=components&q=TPS53318) | 6 V→5 V synchronous buck regulator | 1 | | [MCP1700-3302E/TO](https://www.flux.ai/search?type=components&q=MCP1700-3302E/TO) | 6 V→3.3 V LDO | 1 | | [TPS63060](https://www.flux.ai/search?type=components&q=TPS63060) | Buck-boost for 12 V rail (eGPU power) | 1 | | [ATmega328P](https://www.flux.ai/search?type=components&q=ATmega328P) | Arduino-Uno microcontroller | 1 | | [ESP32-WROOM-32](https://www.flux.ai/search?type=components&q=ESP32-WROOM-32) | Wi-Fi + Bluetooth co-processor | 1 | | [SX1276](https://www.flux.ai/search?type=components&q=SX1276) | LoRa transceiver | 1 | | [TUSB8041](https://www.flux.ai/search?type=components&q=TUSB8041) | 5-port USB 3.0 hub IC | 1 | | [Ethernet PHY](https://www.flux.ai/search?type=components&q=Ethernet%20PHY) | Gigabit Ethernet physical transceiver | 1 | | [SFP Cage](https://www.flux.ai/search?type=components&q=SFP%20Cage) | Fiber-optic SFP module connector | 1 | | [TDA19978](https://www.flux.ai/search?type=components&q=TDA19978) | HDMI 2.0 receiver (input) | 1 | | [TFP410](https://www.flux.ai/search?type=components&q=TFP410) | HDMI 2.0 transmitter (output) | 1 | | [TLV320AIC3101](https://www.flux.ai/search?type=components&q=TLV320AIC3101) | Audio codec for 3.5 mm jack & Bluetooth audio | 1 | | [Audio Jack 3.5mm](https://www.flux.ai/search?type=components&q=Audio%20Jack%203.5mm) | Headphone/mic port | 1 | | [SSD1306 OLED](https://www.flux.ai/search?type=components&q=SSD1306%20OLED) | Status display | 1 | --- ## 4. High-Level Design & Implementation Steps 1. **Schematic Creation** - Section off blocks: CPU + memory, power-supply, NVMe/USB bridge, MCU, wireless, USB hub, video, audio, I/O headers. - Place all parts from the list and wire per respective datasheet reference circuits. 2. **Power System** - Implement USB-C PD with STUSB4500 → buck/buck-boost & LDO rails. - Add LTC4412 to OR-ing battery pack into 6 V bus. - Include LTC3108 harvest input to 6 V bus (no recharge to AA). - Add decoupling & bulk caps per regulator datasheets; PTC fuses & ESD diodes on inputs. 3. **SoC & High-Speed Interfaces** - Break out Snapdragon 990 BGA with DDR4 routing (point-to-point). - Route PCIe Gen3 lanes to M.2 slot via JMS583 and to Titan Ridge for TB/eGPU. - Follow high-speed layout guidelines: impedance, length matching, EMI filters. 4. **MCU & Expansion Headers** - Place ATmega328P with UNO-style 2.54 mm headers; add ISP 6-pin, I²C pull-ups, reset circuit. 5. **Connectivity Blocks** - USB hub: TUSB8041 + ESD + chokes → five USB-A 3.0 ports. - Ethernet: RJ45 + magnetics + PHY; SFP cage + PHY/SFP interface. - Wireless: ESP32 module pad + SX1276 + antenna matching; program pads. 6. **Video & Audio** - HDMI RX (TDA19978) & TX (TFP410) blocks with TMDS ESD & termination. - Audio codec + 3.5 mm jack; route differential audio lines; add ESD. 7. **Display & Indicators** - SSD1306 OLED on I²C; add pull-ups & backlight power if needed. - LEDs for power, charge, status. 8. **PCB Layout & Mechanical** - Follow Raspberry Pi 2×20 header footprint & UNO shield hole pattern. - Add reinforcement for rugged use; standoffs at corners. - Define 4-layer stackup: • Top: signal • L2: GND • L3: PWR • Bottom: signal 9. **DRC/ERC Reviews** - Run ERC for decoupling, pull-ups, power nets. - Run DRC for high-speed clearance, differential pairs, via aspect ratios. 10. **Fabrication & Testing** - Export Gerbers, IPC-2581, BOM. - Prototype assembly; verify power sequencing, rails, interfaces. - Functional tests: USB-C PD negotiation, NVMe throughput, eGPU over TB3, wireless comm, audio, OLED. --- This spec sheet and part list should guide your Flux schematic and PCB layout workflow through to fabrication and validation. Let me know if you’d like to deep-dive into any specific block or review datasheet details next!

The electronic speed controller (ESC) is an essential part of an electric propulsion system’s hardware. It acts like the brain of the system by telling the motor how fast to go based on data signals it receives from the throttle controller. For smaller applications like drones and RC vehicles, this controller has the name ‘ESC’, whereas for larger manufacturing applications it may be called an electronic control unit, inverter, or motor controller. #drone #motorController #PCA9685 #controller #motor #esc #referenceDesign #project #EFM8BB21F16G #MPU9250 #template

High-Frequency Full-Bridge Series-Resonant Converter with LM331 and TL431-Based Inverse-Control System for 330–385V HV DC Bus Regulation

Original Nintendo Entertainment System (NES) controller. Just like the originals, it uses a CD4021B 8-bit shift register to send serial data of the button state to the console.

NEO-M9N GPS Breakout with on-board chip antenna is a high quality GPS board with equally impressive configuration options. The NEO-M9N module is a 92-channel u-blox M9 engine GNSS receiver, meaning it can receive signals from the GPS, GLONASS, Galileo, and BeiDou constellations witn ~1.5 meter accuracy. This breakout supports concurrent reception of four GNSS. This maximizes position accuracy in challenging conditions, increasing precision and decreases lock time; and thanks to the onboard rechargeable battery, you'll have backup power enabling the GPS to get a hot lock within seconds! Additionally, this u-blox receiver supports I2C (u-blox calls this Display Data Channel) which made it perfect for the Qwiic compatibility so we don't have to use up our precious UART ports. Utilizing our handy Qwiic system, no soldering is required to connect it to the rest of your system. However, we still have broken out 0.1"-spaced pins in case you prefer to use a breadboard.

This project is a reference design based on the BQ25606, a single cell Li-Ion battery charger. It manages the power between an external power source (VIN), a Li-Ion battery (BAT), and a system power rail (SYS). Key features include power-path management, battery thermistor monitoring, and charge status indication. #project #BQ25606 #ReferenceDesign #charger #BatteryManagement #referenceDesign #bms #texas-instruments #template #reference-design #polygon

The TUSB8041 by Texas Instruments is a highly integrated four-port USB 3.0 hub controller designed to facilitate high-speed data transfers and power management in computer systems, docking stations, monitors, and set-top boxes. This component offers simultaneous SuperSpeed USB (5 Gbps), high-speed (480 Mbps), full-speed (12 Mbps), and low-speed (1.5 Mbps) data connections, ensuring backward compatibility with USB 2.0 and USB 1.x devices. Key features include multi-transaction translation with four transaction translators, asynchronous endpoint buffers for improved data management, and comprehensive battery charging support compliant with various standards including CDP, DCP, and Chinese Telecommunications Industry Standard YD/T 1591-2009. Flexible power management options are available, catering to both per-port and ganged power control configurations, alongside over-current protection mechanisms. The device also supports custom configurations via OTP ROM, serial EEPROM, or I2C/SMBus interfaces, enabling customization for vendor IDs, product IDs, port specifics, and string descriptors. Ease of integration is further enhanced with the ability for on-board and in-system OTP/EEPROM programming via the USB 2.0 upstream port, and the device requires no special drivers, operating seamlessly with any OS that supports USB. Packaged in a compact 64-pin QFN format, the TUSB8041 is offered in both commercial (0℃ to 70℃) and industrial temperature (-40℃ to 85℃) ranges, ensuring robust performance across diverse environmental conditions. With a single clock input requirement and comprehensive system resource support, the TUSB8041 is ideal for developers aiming to implement high-performance and reliable USB hubs in their designs.

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.

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

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.

This project is a WiFi-enabled door and window sensor using the ESP8684-WROOM-02C module from Espressif Systems. It includes a triple-color LED indicator, Reed switch for detection, a 3.3V Regulatory mechanism, and USB C for firmware flashing. It's powered by a regular non-rechargeable AAA battery. #WiFi #MCU #ReferenceDesign #project #ESP8684 #referenceDesign #simple-embedded #espressif

The Ariel AI Chip, a state-of-the-art integrated circuit designed for high-performance computing applications, incorporates an innovative architecture that leverages radical transistor technology to optimize AI and machine learning tasks. At the heart of this chip lies a quad-core CPU operating at a clock speed of 2GHz, distinguished by its part number CPU-RT-4C-2G. The chip's power management is efficiently handled by a DC power supply, specified as DCPS-5V, ensuring a stable 5V input. Key to its operation are two NPN transistors, identified by part numbers NPN-TRANS-001 and NPN-TRANS-002, which, along with a pair of 1kΩ resistors (RES-1K and RES-1K-002) and a 10µF capacitor (CAP-10UF), form the critical signal processing and conditioning circuitry. This assembly is designed for seamless integration into advanced computing systems, particularly those focused on Flux AI environments, where its performance and efficiency can be fully leveraged. The Ariel AI Chip sets a new benchmark in AI computing, offering unparalleled processing power and efficiency for cutting-edge applications.

The RC522 is a 13.56MHz RFID module that is based on the MFRC522 controller from NXP semiconductors. The module can supports I2C, SPI and UART and normally is shipped with a RFID card and key fob. It is commonly used in attendance systems and other person/object identification applications. #RFID #Module

Use this Copilot's template to design satellite payloads, avionic systems, or space instruments, considering MIL-STD, radiation hardening, and extreme environmental constraints. Modify project requirement properties to adapt to specific needs. #template #project-template

The Ariel AI Chip, a pioneering component in the realm of artificial intelligence hardware, integrates a suite of electronic elements tailored for high-performance computing applications. At the heart of this assembly lies a CPU with a Radical Transistor architecture, featuring a quad-core setup clocked at 2GHz, identified by the part number CPU-RT-4C-2G. Power management is facilitated through a DC Power Supply, marked DCPS-5V, ensuring a stable 5V supply to the intricate circuitry. The chip's switching capabilities are bolstered by two NPN transistors, NPN-TRANS-001 and NPN-TRANS-002, which play a crucial role in signal modulation. Essential to the chip's operation are the passive components: two 1kΩ resistors (RES-1K and RES-1K-002) and a 10µF capacitor (CAP-10UF), which together with the transistors, form a robust network ensuring reliable performance under varying load conditions. Designed for integration into advanced AI systems, this chip stands out for its innovative use of standard components in a configuration that emphasizes efficiency, reliability, and high-speed data processing capabilities.

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.

Use this Copilot's template to design satellite payloads, avionic systems, or space instruments, considering MIL-STD, radiation hardening, and extreme environmental constraints. Modify project requirement properties to adapt to specific needs. #template #project-template

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.

Use this Copilot's template to design satellite payloads, avionic systems, or space instruments, considering MIL-STD, radiation hardening, and extreme environmental constraints. Modify project requirement properties to adapt to specific needs. #template #project-template

The Ariel AI chip prototype is an advanced electronic component designed to enhance the capabilities of Flux AI systems through a sophisticated arrangement of transistors, resistors, capacitors, and a cutting-edge CPU. Key components include two NPN transistors (part numbers NPN-TRANS-001 and NPN-TRANS-002), which are essential for signal amplification, alongside precision resistors (RES-1K and RES-1K-002) each with a resistance of 1kΩ, and a capacitor (CAP-10UF) with a capacitance of 10μF, crucial for filtering and stabilizing the voltage supply. At the heart of the design is a revolutionary CPU (part number CPU-RT-4C-2G) featuring a quad-core setup with a clock speed of 2GHz, based on a radical transistor architecture, designed to deliver unparalleled computational performance for AI tasks. This component set is powered by a 5V DC power supply (DCPS-5V), ensuring a stable and efficient operation. The Ariel AI chip is engineered for high-speed, reliable performance in demanding AI applications, representing a significant advancement in electronic component design for artificial intelligence systems.

Imperium Digital Analog Control Systems

This is a smart blind control system reference design designed to automate the operation of window blinds. It utilizes an ESP32 microcontroller for managing control signals and an A4988 stepper motor driver to control blinds' movement. It also includes USB interfacing and LED feedback. #referenceDesign #edge-computing #edgeComputing #espressif #template #blind #DC #motor #servo #esp32 #reference-design

Tesla Roadster open-sourced schematics for the vehicle display system: https://service.tesla.com/docs/Public/Roadster/Roadster_Schematics/Vehicle-Display-System.zip

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

This is a smart blind control system reference design designed to automate the operation of window blinds. It utilizes an ESP32 microcontroller for managing control signals and an A4988 stepper motor driver to control blinds' movement. It also includes USB interfacing and LED feedback. #referenceDesign #edge-computing #edgeComputing #espressif #template #blind #DC #motor #servo #esp32 #reference-design

A smart ESP32-based battery management system controller board for Lithium ion battery packs/cells. Capable of communicating to wide varieties of hybrid-smart inverters with CANbus, RS485 and UART communication.

A smart ESP32-based battery management system controller board for Lithium ion battery packs/cells. Capable of communicating to wide varieties of hybrid-smart inverters with CANbus, RS485 and UART communication. #smartHomeDevices

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

This project is a plant care system that uses an ESP32-S3-MINI-1U-N8 microcontroller to automate plant care tasks. This system includes three Songle relays, multiple resistors, capacitors, and transistors, all powered at 3.3V, 5V, or 12V. It also incorporates a USB Type-C connector. #referenceDesign #edge-computing #edgeComputing #espressif #template #iot #ESP32 #relay #reference-design

A smart ESP32-based battery management system controller board for Lithium ion battery packs/cells. Capable of communicating to wide varieties of hybrid-smart inverters with CANbus, RS485 and UART communication.

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot:

A smart ESP32-based battery management system controller board for Lithium ion battery packs/cells. Capable of communicating to wide varieties of hybrid-smart inverters with CANbus, RS485 and UART communication.

This is a climate control system reference design with a STM32WB5 microcontroller, power manager IC, USB Type-C, JST connectors, and an LCD driver. #referenceDesign #edge-computing #edgeComputing #stm #template #iot #control #BLE #reference-design

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.

Vehicle Display System for Tesla Roadster #project #Template #projectTemplate

Learn how to optimize your project for cost with this Vehicle Display System project that was open sourced from the Tesla Roadster. Optimizing your BOM for cost can take forever to research component alternatives and understand the supply chain. Learn how to optimize for cost in seconds with Flux Copilot.