Arduino Nicla Sense Env: Environmental Sensing for Smart Applications

Arduino Nicla Sense Env: Environmental Sensing for Smart Applications

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Continuous environmental monitoring is becoming more common in many industries, but it often requires collecting data all the time, which can use a lot of power. The Arduino Nicla Sense Env aims to address this challenge with its compact design and low power consumption. This makes it suitable for applications requiring 24/7 monitoring with minimal energy use. Featuring advanced sensors for indoor and outdoor environmental data, the Nicla Sense Env is designed to balance performance and power efficiency, supporting continuous operation in a compact package.

The Nicla Sense Env is equipped with a 48 MHz Arm Cortex M23 microcontroller, which cannot be accessed or programmed by the user. Additionally, it features 128 kB of Flash memory and 16 kB of SRAM. The analog peripherals include two 12-bit ADCs while the digital interfaces are provided through UART, I2C, and SPI connections. The board includes onboard sensors for monitoring environmental conditions:

  • A Renesas HS4001 humidity and temperature sensor
  • A Renesas  ZMOD4410AI1V sensor for indoor air quality (detecting volatile organic compounds, CO₂, and general air quality)
  • A Renesas ZMOD4510AI1V sensor for outdoor air quality (monitoring nitrogen dioxide, ozone, and other pollutants).

As mentioned earlier It has small dimensions of 22.86 mm x 22.86 mm and weighs only 2 grams. It has castellated pins for easy mounting on custom boards. It can be powered either by a connected Portenta, MKR, or Nano board or through an external supply via VCC pins. The board integrates smoothly with Portenta boards using ESLOV (I2C) or header pins. It also supports programming with both Arduino IDE and MicroPython, making it easy to set up and customize. The board’s compatibility with Arduino libraries and tutorials helps users quickly implement environmental monitoring in their projects.

Arduino Nicla Sense Env Peripheral data The Arduino Nicla Sense Env board, with its features, can be used in many practical applications. In climate control systems, it can be added to HVAC setups to monitor and control air quality, humidity, and temperature, helping create a more comfortable indoor environment. It also improves automated air purifiers by providing real-time air quality data, allowing them to work only when necessary, saving energy and promoting better health. The board is useful for safety applications like detecting fumes and smoke, giving early warnings for fire risks and ensuring safety in homes, offices, and industrial spaces. In industries, it can be used in heat pumps and other machines to track air quality and detect harmful substances, improving safety and monitoring operations. For prototyping, the Nicla Sense Env board is good for developers working with Portenta and MKR boards, providing an easy-to-use solution for environmental monitoring projects.

Arduino Nicla Sense Env- In the box

The Arduino Nicla Sense Env offers energy-efficient, continuous environmental monitoring in a small design, making it suitable for projects with limited space and power. In comparison,  Adafruit’s BME688 sensor provides advanced gas sensing and detailed air quality analysis but may use more power, making it less ideal for round-the-clock applications. SparkFun’s Environmental Combo Breakout, with CO2 and VOC sensors, is good for indoor air quality tracking, but it’s not as compact or power-efficient as the Nicla Sense Env. Similarly, Seeed Studio’s Grove BME280 tracks temperature, humidity, and pressure effectively but doesn’t detect gasses, limiting its use for complete air quality monitoring. Each of these sensors has unique strengths, depending on the specific needs of the project.

For more information, you can refer to the Nicla sense datasheet. To purchase the board, visit the official Arduino store. The current price of the product is €42.70.

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Saumitra Jagdale is a Backend Developer, Freelance Technical Author, Global AI Ambassador (SwissCognitive), Open-source Contributor in Python projects, Leader of Tensorflow Community India, and Passionate AI/ML Enthusiast

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