Consentium IoT
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  • Getting Started
    • Consentium IoT Platform usage
    • Sensor Data API Documentation
    • Steps for Using Consentium IoT's OTA Service
    • Consentium Edge Machine Learning
    • ConsentiumNow Library Documentation
    • EdgeModelKit: Sensor Data Acquisition and Logging Library
  • Code usage
    • ConsentiumThings Python API
    • ConsentiumThings Arduino API
    • ConsentiumThings Arduino API with OTA Updates
    • WiFi auto connect API
    • ConsentiumThings Arduino Data Receiver API
    • ConsentiumNow Library API
  • Edge boards
    • Consentium Edge Dalton board
  • Tutorials
    • Receiving sensor data
      • Receiving Sensor Data from Consentium IoT Cloud and Controlling LED
    • Sending sensor data
      • Sending LM35 Sensor Data to Consentium IoT Cloud
      • Sending DHT11 Sensor Data to Consentium IoT Cloud
    • Edge machine learning
      • Sine wave predictor
      • Sine wave predictor with IoT
      • TinyML Occupancy Classification Example with Consentium IoT
  • Board support
    • Adding NodeMCU support to Arduino IDE
    • Adding ESP32 Support to Arduino IDE
    • Programming Raspberry Pi Pico with Arduino IDE (Pico W Compatible)
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  • Features
  • Core Processor
  • Power Options
  • Connectivity & Expansion
  • Sensor Integration & Monitoring
  • Additional Features
  • Applications
  • Getting Started

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  1. Edge boards

Consentium Edge Dalton board

PreviousEdge boardsNextReceiving sensor data

Last updated 2 months ago

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The Edge Dalton IoT Board is a powerful, ESP32-C3-based development board designed for seamless integration with Consentium IoT. It is optimized for industrial IoT applications, featuring multiple sensor interfaces, voltage and current monitoring capabilities, and robust connectivity options.

Features

Core Processor

  • ESP32-C3-MINI with Wi-Fi and Bluetooth LE for wireless connectivity

  • RISC-V 32-bit single-core processor for low-power edge computing

  • FreeRTOS support for real-time applications

Power Options

  • USB-C Port for easy connectivity and power

  • DC Barrel Jack for external power supply

  • Onboard AMS1117 voltage regulator for stable power management

Connectivity & Expansion

  • I2C, UART, and I2S interfaces for sensor and peripheral integration

  • Dedicated GPIO headers for expansion

  • 3.3V logic level support for interfacing with various devices

Sensor Integration & Monitoring

  • Voltage Terminal (J3): Four input channels for voltage monitoring

  • Current Terminal (J5): Four input channels for current sensing

  • Dedicated ADCs for precision measurements

Additional Features

  • Boot and Reset buttons for easy development and debugging

  • LED indicators for power and status

  • Compact and robust PCB design for industrial environments

Applications

  • Industrial Sensor Monitoring – Capture and transmit real-time voltage and current data

  • Edge AI & TinyML – Deploy ML models on the ESP32-C3 for predictive maintenance and anomaly detection

  • IoT Data Logging – Send sensor data to Consentium IoT Cloud for analytics and visualization

  • Wireless Automation – Utilize Wi-Fi and BLE for remote monitoring and control

Getting Started

  1. Power Up: Connect via USB-C or DC barrel jack.

  2. Firmware Setup: Flash your ConsentiumThings firmware or EdgeNeuron using Arduino IDE.

  3. Sensor Integration: Connect voltage/current sensors to respective terminals.

  4. Cloud Connectivity: Send data to Consentium IoT Cloud for real-time analytics.

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