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.
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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