For a midsize corporation running multiple cafeterias, an AI tool may be feasible, provided sufficient time and resources are invested well in advance of system use. Selling as a full strategy an AI tool without a corporate commitment to a strategy which includes costs listed below is unwise. As of this writing and for the foreseeable future, there are no drop-in AI systems that will recognize a command such as, "Learn these foods and their prices and then keep learning whenever we adjust the menu due to cycling of main dishes, buying considerations, or substitutions made due to shortages. By the way, when one food obscures another, either by design of the buyer to avoid paying for items or by accident, detect that and respond appropriately."
You cannot assume that the foods in the tray will look like a single photo of that food in a tray either. How many frames of them will be required is variable and some domain specific research may be required to size the project. A smaller investigative project will need to be completed before the corporation can decide whether to invest all the way.
The best approach is to set up multiple camera angles focused on a target area clearly outlined between the existing human cashier and the tray holder. The cashier involved in training the AI must ensure the trays are in the outlined target area and charge for the food on the tray accurately. The data from cameras and point of sale systems must be merged to produce videos with itemized lists of items on the trays.
A sufficiently deep LSTM network could be trained, tested, and verified on a sample of that data. Theft detection would need to be designed into all elements of the strategy. The current database schema would need to link to image files. Thirty frames per second would not be necessary. Two or three FPS might be sufficient. Some theoretical investigation and subsequent experimentation as part of the initial investigation would be be wise.
These are probable costs and considerations associated with transition and continued use of the AI system, and this is not meant to be an exhaustive list.
- Initial research to size the project properly
- At least two cameras at each location, usable for both training and execution
- Extension of networking equipment
- Software to tie itemized lists of items at the point of sales with the associated video feed and indicate to the point of sales system what to charge the tray-holder once the items can be recognized
- Database storage to support low frame rate, medium resolution video storage
- Human personnel training time and materials so that they can participate in the machine training as new items are added (so that the recognition of the items in the trainers is transferred to the machine trainee)
- An off line cashier station for training so that items can be added to the database without interrupting cafeteria revenue generation
- Purchase and shipping of items to the simulation station
- Training programs for food buyers and cooks
- A plan for how to transition the workforce in accordance with legal and ethical standards
- Associated customer and public relations
- Equipment to indicate probable theft to the food purchaser or to the appropriate security personnel if the food purchaser will not comply
- Plan for dealing with cash or excluding it from payment options