Smart Soil Health Monitoring: Empowering Dapoli Agriculture College with IoT-Based Soil Research Insights

College of Agriculture

UN SDG 12 - Responsible Consumption and Production

Dapoli

Pain Points

Difficulty in real-time soil parameter monitoring for research accuracy.

Manual Soil Sampling Delays

Traditional sampling methods delayed research data collection and reduced accuracy.

Inconsistent Data Recording

Lack of centralized monitoring led to data inconsistency and manual entry errors.

Limited Environmental Correlation

Absence of connected data limited correlation between soil health and weather factors.

Our Offerings

IoT-based soil monitoring solution integrated for real-time data analysis.

LoRaWAN Soil Sensor Deployment

Installed multi-parameter LoRa sensors to measure soil moisture, temperature, and EC.

Cloud Dashboard Integration

Enabled continuous visualization and historical data access for research analysis.

Automated Data Logging

Eliminated manual data recording with scheduled, wireless data transmission.

Correlated Weather Insights

Linked soil data with weather parameters for holistic soil health understanding.

Installed multi-parameter LoRa sensors to measure soil moisture, temperature, and EC.

Enabled continuous visualization and historical data access for research analysis.

Eliminated manual data recording with scheduled, wireless data transmission.

Linked soil data with weather parameters for holistic soil health understanding.

Outcomes

Accurate Soil Health Data

Real-time monitoring improved the reliability of soil quality assessments.

Enhanced Research Productivity

Automated data collection saved time and improved research turnaround cycles.

Data-Driven Decision Making

Researchers gained actionable insights from continuous and accurate datasets.

Scalable Research Model

System established a scalable model for smart soil monitoring across crop zones.

Smart monitoring enhanced our soil research efficiency and analytical precision.

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