We recognize that in the food industry, different time intervals with different types of foods equate to nonidentical amounts of people visiting, which would impact the amount of food wasted. To consider this factor, we have an observation period where the AI is fed information about trends at different time intervals. First, the initial amount of food prepared would be measured. After the time interval is over, the leftover food will be recorded as well. 

To provide a better understanding, here are some specific scenarios to demonstrate what information the AI would be ingesting: 

• On cruise ships, the AI would be fed the initial amount of food before lunchtime (roughly 12 pm to 3 pm, though subject to change per each food establishment) on Monday, and the final amount of food

• In food supply chains, the AI would be fed the initial amount of food inventory of cheese and the final food inventory of cheese after demand on Monday

To get a more accurate account of the exact food, measurement of the mass and quantity of food passengers take will be accounted too. More specifically, crew members should weigh trays of food before it's sent out to customers. When the trays come back to the kitchen, staff weigh and measure the amount of food again to find the deficit and remaining amount of food. Then use AI to create an algorithm that tracks and advises staff on how much food to buy and cook on certain days and times.

Like step 1, step 2 focuses on providing more observed information for accurate predictions. However, step 2 counts the number of people who enter. 

To provide a better understanding, here are some specific scenarios to demonstrate what information the AI would be ingesting: 

• On cruise ships, the AI would be fed the about of people who confirmed their registration for lunchtime (roughly 12 pm to 3 pm, though subject to change per each food establishment) on Monday

• In food supply chains, this does not apply

Furthermore, another possible way to gather data is that ships can introduce cameras and sensors at specific restaurants, most likely buffets where food consumption isn't quite as regulated. In addition to weighing the amount of food coming from and back to the kitchen, using the tracking AI systems and cameras like at Amazon Fresh stores, we can track individuals' specific consumption. 

With all the data gathered, the AI can predict the amount of food demanded roughly per each time interval and each time of the day. 

For instance, the average of the cruise ship/food establishments can be calculated by getting the average of calculating how much food per person is consumed.

For supply chains, the average demand per product can be calculated by getting the mean of the products through the observation period. For this intended use, it may take a longer observation period to acquire accurate results.

This method gives the optimal amount of food to be ordered. Therefore, there will no longer be a surplus of food. As a bonus, there will also be a reduction in overproduction and over sourcing. This will overall better the environment save cruise ships and supply industries millions annually.