Spatial Augmented Reality Based Customer Satisfaction Enhancement and Monitoring System

Abstract

The research proposes a novel scheme that enhances customer satisfaction through spatial augmented reality and a customer expression-based deep learning network to customize the dining environment in high-grade restaurants. The perception of the quality of food was also enhanced by the recreation of the live environment on the preparation of the menu ordered utilizing the waiting time after each ordering session. Initially, a virtual menu driven by a web page is projected onto the table using a Three-dimensional (3D) projection by which the customers can interactively choose dishes after examining how the dish looks in quality and quantity. The dishes are being portrayed in 3D also adding Spatial Augmented Reality (SAR) features in a special angle creating a 3D illusion to the naked eye. By using photogrammetry we could portrait an identical 3D model of restaurant dishes. With the use of software's parallax effect was added to the video animation to bring out the 3D effect. A virtual restaurant background is created on the walls with relaxing videos and soothing soundtracks to enhance the restaurant ambiance as the restaurant ambiance deals more with the sensory and emotional aspects. On the analysis of the ordered menu and based on preferences available within the database, menu suggestions are also proposed depending on the recommendations of the customer satisfaction analysis model. . This provides customers with a firsthand experience at the restaurant; known as "Business to Customer" (B2C) strategy in marketing. The deep learning-based facial expression recognition system is running in the background to monitor customer satisfaction levels through facial expressions. The captured data will be processed loaded into a database containing a ranking system, which the restaurant management can use for future analytics, to re-arrange prices and upgrade profit margins. The performance was analyzed with numerous experimental evaluations with ambient light levels and desired viewing angles, where we found optimal angle values for spatial augmented reality applications. A survey was done on a sample with different ages, gender, and social status to analyze user perception on evaluating the proposed system. The results revealed 87.5% of responders were very satisfied with the 3D virtual experience. 79.2% indicated rareness of feedback on food and service and more than 50% liked a system that will automatically measure their satisfaction. The outcome and resulting insights may lay a foundation for a novel approach towards the management of customer experience.

Implementasi Sistem Kasir Digital Berbasis Teknologi Deteksi Tangan Computer Vision dan OpenCV

“…Dalam hal ini, salah satu aspek yang perlu diperhatikan adalah pelayanan kepada pelanggan. Dalam industri makanan dan minuman, pelayanan yang cepat dan efisien menjadi salah satu faktor penting dalam meningkatkan kepuasan pelanggan pada saat pemesanan menu [5]. Oleh karena itu, Dalam penelitian ini, kami merancang sebuah antarmuka virtual untuk mesin kasir digital di Café Lentera Coffee & Eatery menggunakan teknologi Computer Vision dan Convolutional Neural Network (CNN) dengan tujuan meningkatkan pelayanan konsumen menggunakan teknologi kecerdasan buatan [6].…”

Product Design Interaction and Experience Based on Virtual Reality Technology

“…In some ways, this technology is an extension of the human body. Virtual reality technology enables users to communicate with the virtual environment [13,14]. To facilitate interaction, either visualizes the online setting as an online setting or as a real-world environment.…”

Evaluation Model and Influencing Factors of Consumer Satisfaction with E-Commerce Platform

“…Most studies on consumer satisfaction with e-commerce platform investigate the influencing factors of consumer satisfaction, and innovate the following aspects of the platform: acquisition form of consumer behavior data, interactive interface, and evaluation algorithm, from the perspectives of theory and technology [22][23][24][25][26]. However, few of the proposed e-commerce platforms manage to put consumers at the center, or meet the ideal expectation of consumers, owing to the overlook of platform consumer feedbacks like sharing, forwarding, and reviewing.…”