AI-Powered Smart Grain Silo & Warehouse Spoilage Prevention System
Multi-depth grain probe array detecting moisture hotspots, CO2 respiration, and insect acoustic vibrations to prevent agricultural post-harvest spoilage.
Project Overview
A functional student agricultural prototype with a miniature acrylic grain silo, multi-tier capacitive moisture probes, MQ-135 gas sensor for grain respiration monitoring, piezoelectric acoustic sensor for early weevil detection, and an ESP32 LoRa wireless node. ### Real-World Problem Up to 25% of harvested food grains are ruined annually in storage silos due to unnoticed moisture condensation and fungal spoilage. ### Practical Student Solution Continuous spatial telemetry detects microclimate degradation 10 days before visible mold growth and activates automated ventilation fans. ### Hardware Modules & Sensors - ESP32 LoRa Node - Multi-Tier Moisture Probes - MQ-135 Respiration Sensor - Piezo Acoustic Tap Probe - Miniature Acrylic Silo Model - Relay Ventilation Fan ### Commercial & Institutional Value High institutional value for Agricultural Engineering and IoT rural tech grants.
Modern commercial and industrial infrastructure requires automated, real-time sensing and telemetry. Conventional manual monitoring suffers from high latency, human error, and lack of predictive fault visibility for AI-Powered Smart Grain Silo & Warehouse Spoilage Prevention System.
A turnkey engineering prototype integrating high-precision sensor modules, dedicated microcontroller unit, and cloud telemetry protocols to automate measurement, trigger alert thresholds, and provide remote dashboard control.