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Soil Moisture Mapping using IoT

IoT-Based Soil Moisture Mapping

Efficient irrigation and soil health management are critical challenges in modern agriculture. Traditional soil moisture monitoring methods are either expensive, require continuous internet connectivity, or lack flexibility for small and medium-sized farms, research plots, and educational setups. This makes real-time, localized soil analysis difficult and limits data-driven farming decisions.

This Soil Moisture Mapping project offers a low-cost, portable, and standalone system to monitor soil moisture, light intensity, and temperature across agricultural land. Built around the IndusBoard Coin, the system operates in Wi-Fi Access Point (AP) mode, allowing users to connect directly to the device and view live sensor data through a web-based dashboard—without relying on external internet connectivity.

Key Features
  • Standalone Wi-Fi AP mode for offline operation
  • Real-time sensor updates every second
  • Supports land division into up to 30 sections with a 5×6 color-coded grid
  • Visual moisture mapping from light blue (wet) to deep blue (dry)
  • Single-button data capture with automatic section progression
  • Displays averages, driest area, and overall moisture profile
  • Customizable land area input (in square meters)
  • Modular, configurable code for Wi-Fi, sensors, grid size, and calibration
  • Affordable hardware setup (under $50) and quick assembly (under 1 hour)
  • Supports both single-sensor manual mapping and multi-sensor real-time deployment
Applications
  • Precision agriculture and irrigation planning
  • Small and medium-scale farming
  • Agricultural research and field experiments
  • Soil health assessment and crop planning
  • Educational projects and IoT learning labs
  • Hobbyist and prototype development for smart farming solutions

By combining affordability, portability, and real-time visualization, the Soil Moisture Mapping project demonstrates how IoT can empower smarter agricultural practices. With minimal hardware, no internet dependency, and flexible customization, it enables farmers, researchers, and students to make informed decisions that improve resource efficiency and promote sustainable farming.

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