Tableside AI waiter for personalized guest experience

A method for artificially intelligent tableside customer engagement, comprising:

• detecting a wake word using deep learning-based wake word recognition or keyword spotting, wherein audio input is continuously monitored through a microphone array for wake word detection and thereby transitioning the system to a listening and processing state upon detecting the said wake word;
• triggering a plurality of sensors to gather input data the said sensors including microphone, camera, hardware identifier of customer's devices and geotagging and wherein the said input data includes video data, audio data, hardware identity data of customer's devices and location history;
• extracting facial features and vocal features of a customer from the captured video and audio data respectively using face detection and voice detection models and comparing the extracted face and voice features with customer data stored in the database to identify a returning customer;
• comparing the collected unique hardware identifiers data of the customer's devices and geolocation data with the data stored in the database under the customer's profile for enhanced customer recognition;
• retrieving profile of a returning customer stored in the database, and greeting the customer;
• signing up a new customer by creating a unique customer profile using predeterminate templates and said input data;
• displaying available menu items from restaurant establishment data on a display device;
• processing customer's natural language input via natural language processing and transcribing the said input into text by a transcription module thereby classifying the intent and entity through an intent and entity recognition of the chatbot module to generate context-aware responses;
• providing personalized menu recommendations to the customer based on AI models, the said AI models processing a plurality of data sets including customer profile data, restaurant establishment data, contextual data, and real-time input data for generating personalized recommendations;
• transmitting the said personalized order information to a fulfillment terminal or kitchen display system in real-time;
• re-transmitting the real-time updates from the fulfillment terminal or Kitchen Display System to the connected tableside system;
• and
• relaying the said order information and payment details from the centrally integrated point-of-sale system to the connected tableside system.