Method and system for analyzing quality of a food item

A remote analysis device for analyzing quality of a food item, the remote analysis device comprising a processor operably connected to a memory, the memory storing a first trained machine learning model, the remote analysis device being configured to:

• receive, from a user device, sensor data of the food item, wherein the sensor data comprises image data and measurement data comprising odor data;
• process the image data using the first trained machine learning model to determine a food class of the food item from among a plurality of food classes;
• process the measurement data based on the determined food class using a second trained machine learning model to determine a food quality indicator of the food item, wherein the second trained machine learning model is trained using a training database comprising a plurality of samples, wherein a sample of the plurality of samples comprises training measurement data of a training food item including training odor data and labels including a training food class and a training food quality indicator;
• and
• transmit the food class and the food quality indicator to the user device.

A user device configured to cooperate with a remote analysis device to analyze a food item, the user device comprising:

• a camera configured to capture image data of the food item;
• a communication interface configured to receive measurement data of the food item from one or more sensors placed close to the food item, wherein the measurement data comprises odor data;
• a network communication component configured to send the image data and the measurement data to the remote analysis device and receive a food class and a food quality indicator in response to the image data and the measurement data;
• and
• a human-machine interface configured to output a representation of the food class and the food quality indicator.