An IoT-Based Real-Time Quality Monitoring System for Cooking Dairy Products Via Ammonia Emission Detection

Abstract

As the awareness on food safety and quality continuously growth, the significance of effective monitoring system becomes more evident, specifically in dairy industry, where spoilage becomes common within short period of consumption. Fresh milk storage at an elevated temperature with unhygienic practices of product preparation may results to inferior-quality of dairy production. An inferior dairy product emits gases such as ammonia(NH3 ), carbon dioxide(CO2) and methane(CH4), which instigated of foodborne illnesses when consumes by consumers. This escalates public health risks and economic instability in the food industry. Hence, this study proposes and experimentally investigates an Internet of Things (IoT)-enabled real-time monitoring system for spoilage detection in dairy products via ammonia nitrogen trihydride (NH3) emissions patterns analysis. The system integrates gas sensors of MQ 135 and MQ 137, a temperature sensor and a NodeMCU esp8266 microcontroller with loud based monitoring via Adafruit IO and Telegram Bot alerts. The system is then, validated by conducting nine (9) dairy products in which includes of animal and plant-based in liquid and solid forms over 24 hours under controlled enclosed conditions. Results show that MQ 137 provides higher NH3 selectivity and sensitivity compared to MQ 135 due to its narrower cross-sensitivity spectrum with a specific response only towards NH3 within 5-500 ppm. The system indicates an early spoilage detection (32-35 ppm), remote monitoring and an alert automation that contributes an economical, a scalable alternative of experimental testing to support food safety monitoring with digital transfromation in the dairy industry.