• Aradhana Sharma
• Madhuri Borawake
• Ulfat Shaikh
• Sejal Barkade
• Rutuja Paturkar

Food spoilage is a crucial problem everyone is facing in the world. Every year about 48 million cases of food-borne illness are reported across the world. This is due to the consumption of spoiled food. Spoiled food contains several volatile organic compounds which are harmful to health. So, it is necessary to develop a system that can detect food spoilage before even the signs of spoilage are visible. The system aims at detecting spoiled food using appropriate sensors and by monitoring gases released from food. Different sensors are used to detect different parameters of food such as pH, moisture, oxygen level, ammonia gas, methane, and ethylene. The microcontroller takes readings from sensors. These readings are used as input to the machine learning model which will determine whether food is spoiled or not. If food is not spoiled, then the ML model will also predict the lifespan of food. This would help consumers to consume fresh food and avoid food-borne illnesses. With the help of this gadget, human mistakes that occur during the inspection can also be avoided. As in this system, the work of humans has been taken by the sensor, due to which there is no chance of human errors. That's why its accuracy has increased. The device gets the accurate results while detecting food spoilage. Time and money consumption can be reduced due to the high efficiency of the system, which will be profitable for large industries.

Arduino Uno, Internet of Things, Machine Learning, Sensors, Spoilage detection

"Spoilage detection and shelf life prediction of food using Internet of Things and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.k320-k327, May-2022, Available :http://www.jetir.org/papers/JETIR2205B42.pdf

"Spoilage detection and shelf life prediction of food using Internet of Things and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppk320-k327, May-2022, Available at : http://www.jetir.org/papers/JETIR2205B42.pdf