Smart Refrigerator Shelf with Spoiled Food Detection

Author : Jagadish M

Abstract : This paper presents the design and implementation of a Smart Refrigerator Shelf with Spoiled Food Detection system that integrates embedded sensing, Internet of Things (IoT) connectivity, and multimodal artificial intelligence for real-time freshness assessment. The system employs an ESP32- CAM node for image capture, an MQ135 sensor for volatile organic compound (VOC) detection, and a DHT11 sensor for temperature-humidity monitoring. Sensor data undergoes pro- cessing through a Python-based gateway that leverages the Google Gemini multimodal API for intelligent analysis, delivering human-readable explanations, confidence scores, and estimated shelf-life via Telegram bot notifications. Practical implementation overcomes hardware challenges including ADC WiFi conflicts through external I2C-based ADS1115 converter and power sta- bility issues using dedicated power banks. Results demonstrate accurate spoilage detection with reduced false positives through multimodal fusion logic, achieving 92-96% accuracy with only 6-12% false positive rate. The system achieves deployment readi- ness suitable for households, retail refrigerators, and commercial kitchens, contributing to waste reduction, improved food safety, and sustainable resource management across the food value chain.

Keywords : IoT, Food Spoilage Detection, Machine Learning, Computer Vision, Gas Sensors, Edge Computing, Multi-modal AI, Smart Refrigeration, ESP32-CAM, Gemini API

Conference Name : International Conference on Science, Engineering & Technology (ICSET - 25)

Conference Place : Visakhapatnam, India

Conference Date : 27th Dec 2025