Economic rice stalls are highly popular in Singapore. Cashiers at these stalls typically inspect the dishes visually, and mentally calculate the total price of each plate. This process is error-prone, often leading to inconsistent charges for customers. Existing technology can identify specific dishes or cuisines but lacks the ability to identify the mix of dishes on a single plate. An Artificial Intelligence (AI) model has been trained to identify and calculate the prices of the dishes to streamline operations.
Real-time food detection using an innovative AI Model.
Can be integrated with external systems such as cash registers, enabling further automation.
The inference model can be deployed to an edge device, such as Nvidia Jetson Nano.
Data can be transferred to another system via a JSON format.
Suitable for coffee shops, food court operators, chain restaurants seeking an efficient automated experience across all branches.
Relevant for food and restaurant operators, as well as system integrators.
Applicable in the automated food industry.
Valuable in the health and nutrition technology industry, such as nutrition tracking apps.
Efficient and eliminates human errors.
Provides a seamless, hassle-free customer experience.
Enables further business automation.
Easily manages price fluctuations.
Data can be exported for further analysis.
The technology is available for licensing and technology transfer.
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