Gravity: KnowFlow Basic Kit - DIY Water Monitoring Kit with pH & EC Sensors

Designed as a comprehensive automatic water monitoring solution, KnowFlow AWM empowers environmentalists, researchers, and educators to capture real-time water quality data with unprecedented ease. This open-source science toolkit integrates pH and electrical conductivity sensors into a plug-and-play system based on Arduino, easy to change and add more sensors and modules. Data logs directly to a micro-SD card for offline storage, while integrated Bluetooth communication allows convenient smartphone visualization without cumbersome wiring. Born from the collaboration between GreenSeed Organization and maker communities, this environmental sensing platform reduces the complexity of professional-grade water monitoring, making it accessible for citizen science projects and STEM Education initiatives. By combining reliable Gravity-series sensor interfaces with a flexible Bluno microcontroller core, the system provides a low-cost, extensible foundation for continuous aquatic environment surveillance.

Note: This basic version of the automatic water monitor includes only pH and electrical conductivity sensors. Temperature measurement requires an additional Gravity: Waterproof DS18B20 Sensor Kit, and users should consider a waterproof enclosure (200mm×150mm×75mm) with an acrylic mounting plate for field deployment. Enclosure design files are available in the GitHub repository.

Open-Source Hardware for Environmental Science

This digital water quality tester embodies the principles of open science, with all hardware schematics, code, and course materials publicly accessible. The kit operates with pre-loaded firmware that requires no coding knowledge — simply upload the sketch to the Bluno board and begin logging pH and EC data to the TF card immediately. The modular Gravity interface standardizes sensor connections, allowing users to expand monitoring capabilities by adding optional probes like ORP sensor or Dissolve Oxygen sensor. The system’s compatibility with standard Arduino development boards ensures that custom modifications or advanced data processing workflows remain straightforward for experienced makers.

Integrated Bluetooth and Data Logging Core

Built around a Bluno microcontroller with onboard Texas Instruments CC2540 BLE chip, this portable water analysis device supports wireless programming and transparent serial communication. The Bluetooth module can be configured via AT commands, enabling remote data access through smartphones or tablets without physical connections. For long-term deployments, the system stores time-stamped readings on a micro-SD card, creating a durable offline data repository. The microcontroller’s Arduino Uno bootloader and pin mapping ensure seamless integration with existing shields and libraries, while the USB or external 7–12V DC power options provide flexibility for both bench testing and remote field installations.

High-Accuracy pH and Electrical Conductivity Sensing

The included analog pH sensor delivers measurements from 0 to 14 pH with ±0.1 pH accuracy at 25°C, featuring a BNC connector and gain adjustment potentiometer for calibration. The electrical conductivity sensor supports a 1–20 mS/cm range with ±10% full-scale accuracy when used with the Arduino’s 10-bit ADC, making it suitable for freshwater and moderate salinity applications. Both sensors utilize isolated analog signal paths to minimize electrical noise, ensuring reliable readings even in challenging environments. The EC probe includes a 60cm cable and integrated analog isolator that separates the sensor-side and Arduino-side power supplies, protecting the microcontroller from potential damage in wet conditions.

This open-source water monitoring system serves diverse applications including environmental research, pollution source tracking, agricultural water management, and educational STEM curricula. Field researchers can deploy the kit for continuous stream or lake monitoring, while classroom instructors leverage its visual data logging capabilities for hands-on science lessons. The extensible architecture also supports advanced IoT integrations, such as connecting to Raspberry Pi or LattePanda boards for cloud data aggregation, or enabling long-term unattended operation in remote locations with battery or power bank supplies.