A Smart IoT Solution for Monitoring and Predicting Grocery Freshness and Quality
K Aarya Shri1, Priya Seema Miranda2, Jayalakshmi K P3
1,2,3 St Joseph Engineering College, Mangaluru
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Abstract – According to the statistics,40% of the food produced is wasted before it reaches the consumers. The core problem lies in logistics and infrastructure. Firstly weather varies widely and it makes generalization difficult. This makes it impossible for perishables to naturally survive long-haul transport. Secondly, cold storage facility is not available and affordable to all farmers. Today food spoilage is a crucial problem. The food we consume can affect in any form of contamination that may occur due to storage or chemical changes within the food. This makes it necessary to develop a system that can help people to identify and predict the freshness of food or quality of food items. A smart grocery management system helps users manage groceries in large warehouses and long transportations. Users no longer have to worry about continuous food monitoring. This project aims to ensure the freshness of grocery by predicting the spoilage of grocery in prior and to notify the user about the same so that he can take necessary precautions to prevent grocery spoilage.
Continuous analysis of temperature and humidity of the grocery is carried out by using DHT11 Temperature and Humidity sensor to monitor varying parameters of the grocery. ESP8266 Node MCU is used as the main controller of the system which is used to control the sensing action of the sensor. Data collected from the sensor is used to analyse the variations in the values of temperature and humidity when the grocery is fresh and when it is completely spoilt. The humidity and temperature data are sent to the cloud storage by using the Wi-Fi module which is inbuilt to the Node MCU. ThingSpeak cloud platform is set up for the storage purpose which is retrieved back to use it for predicting the spoilage of the grocery which is the main goal of the system. A prediction algorithm is used for this purpose which is basically a combination of machine learning and data mining approach for forecasting or predicting the future values based on some past set of values. The values of fresh grocery has been given as the input to prediction algorithm which is used to predict the future values of temperature and humidity. Predicted values obtained is compared with the spoilt values measured earlier to detect the spoilage of grocery. Predicted status of the grocery has been notified to the user through SMS.
Key Words: food, grocery, freshness, prediction
