Self-Service Dish Selection, AI Settlement, SingTown Technology Empowers Self-Service Restaurants with Intelligent Upgrades

In traditional self-service restaurant settings, SingTown Technology's intelligent camera system based on OpenMV enables automatic recognition and price calculation of tray dishes. Different dishes correspond to plates of varying colours, shapes, and sizes. Through image recognition and machine vision algorithms, AI detects plate features in real time, automatically matches dish categories with prices, and delivers a fast, unattended checkout experience.

In traditional self-service eateries, customer checkout usually depends on manual verification of dish types and quantities, leading to cumbersome processes, low efficiency, and a high chance of errors.

SingTown Technology's intelligent camera system, developed based on OpenMV, enables automatic identification of meal trays and price calculation at the customer end, delivering a more efficient, accurate, and stable checkout experience with ease.

The system uses cameras to capture tray images in real-time, distinguishing features like the colour, shape, and size of plates through machine vision algorithms. This allows for rapid identification of dish categories—such as meat dishes, veggie dishes, and staples—and automatically labels prices on the recognition interface. The edge AI algorithm maintains high recognition accuracy under various lighting conditions, angles, and backgrounds, while supporting user-defined model training to adapt and optimise for specific tableware styles. This embedded vision system can be directly integrated with POS settlement systems to achieve automatic pricing, statistics, and data analysis. The solution facilitates easy edge deployment—simply installing smart cameras at checkout lanes or tray return points enables fully automated recognition and settlement processes. SingTown drives the digital transformation of the catering industry with OpenMV intelligent vision technology, bringing AI into real-world dining scenarios to achieve faster settlements, more accurate management, and an enhanced intelligent operational experience.