Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages

Abstract

Beverages is a broad and important category within the food industry, which is comprised of a wide range of sub-categories and types of drinks with different levels of complexity for their manufacturing and quality assessment. Traditional methods to evaluate the quality traits of beverages consist of tedious, time-consuming, and costly techniques, which do not allow researchers to procure results in real-time. Therefore, there is a need to test and implement emerging technologies in order to automate and facilitate those analyses within this industry. This paper aimed to present the most recent publications and trends regarding the use of low-cost, reliable, and accurate, remote or non-contact techniques using robotics, machine learning, computer vision, biometrics and the application of artificial intelligence, as well as to identify the research gaps within the beverage industry. It was found that there is a wide opportunity in the development and use of robotics and biometrics for all types of beverages, but especially for hot and non-alcoholic drinks. Furthermore, there is a lack of knowledge and clarity within the industry, and research about the concepts of artificial intelligence and machine learning, as well as that concerning the correct design and interpretation of modeling related to the lack of inclusion of relevant data, additional to presenting over- or under-fitted models.

AI and robotics in the European restaurant sector: Assessing potentials for process innovation in a high-contact service industry

“…• Analysis and development of recipes using neural networks based on recipe data of combined ingredient lists, cooking instructions and food images (Herranz et al 2018;Marin et al 2019;Salvador et al 2017) • Liquid handling control for service robots (Komoguchi et al 2008) • Cooking robots (Berezina et al 2019;Yan et al 2007) • Beverage management (alcoholic and non-alcoholic) (Gonzalez et al 2019) • Kitchen Operation (Mathath and Fernando 2015) Supply chain management…”

Internet of Beer: A Review on Smart Technologies from Mash to Pint

“…The device can auto shutdown the lines in the case of problems preventing waste, e.g., caused by involuntary emptying of beer lines, and represents a valuable tool for marketing by acquiring data regarding what brands were poured at what time and where. Finally, recent studies show a clear trend regarding the use of low-cost techniques using robotics, AI, computer vision, biometrics, and more also to assess the quality and consumer preferences regarding beverages [96,97].…”

QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs

“…Critical roles of sensors and automation techniques in food quality assessment, including process monitoring, shelf-life investigation, freshness evaluation, and authenticity in food processing industries, have been demonstrated [23]. Emerging low-cost and reliable technology based on machine learning (ML) and artificial intelligence (AI), computer vision, biometrics, and robotics for the accurate, remote, automated assessment of the quality and consumer preference of beverage and for the assessment of food smells have resulted in major breakthroughs [24,25].…”