The Application of Artificial Intelligence and Big Data in the Food Industry

Abstract

Over the past few decades, the food industry has undergone revolutionary changes due to the impacts of globalization, technological advancements, and ever-evolving consumer demands. Artificial intelligence (AI) and big data have become pivotal in strengthening food safety, production, and marketing. With the continuous evolution of AI technology and big data analytics, the food industry is poised to embrace further changes and developmental opportunities. An increasing number of food enterprises will leverage AI and big data to enhance product quality, meet consumer needs, and propel the industry toward a more intelligent and sustainable future. This review delves into the applications of AI and big data in the food sector, examining their impacts on production, quality, safety, risk management, and consumer insights. Furthermore, the advent of Industry 4.0 applied to the food industry has brought to the fore technologies such as smart agriculture, robotic farming, drones, 3D printing, and digital twins; the food industry also faces challenges in smart production and sustainable development going forward. This review articulates the current state of AI and big data applications in the food industry, analyses the challenges encountered, and discusses viable solutions. Lastly, it outlines the future development trends in the food industry.

The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants

“…The connectivity provided by the IoT enhances the functionality of sensors, enabling remote monitoring and real-time data collection. Moreover, harnessing AI methods and tapping into the power of big data analytics aids in the identification and analysis of potential issues as well as emerging trends within food samples [ 71 ]. Overall, these technological advancements contribute to significantly enhancing the efficiency and intelligence of biosensor-driven food quality assessment systems, ensuring the maintenance of excellent food quality and safety standards.…”

The Future of Food

“…Retail formats that are expected to expand include e-commerce, driven by convenience and personalization, as well as sustainable and ethical retail emphasizing eco-friendly practices. Technology-driven stores and direct-to-consumer brands also represent growth areas in the retail industry [42][43][44][45][46][50][51][52][53].…”

“…Online shopping for groceries is also expected to grow in this direction, focusing on improving user experiences and incorporating AI-driven recommendations to enhance the shopping process. Consequently, many food companies utilize AI and big data to enhance product quality, cater to consumer demands, and drive the industry towards a more intelligent and sustainable future [53]. For example, big data can be used to analyze consumer perceptions after gathering them from social media platforms to aid health food manufacturers in enhancing their products to align with customer preferences [54].…”

Development of a Decision Support System for Perishable Food Management in Culinary Education Institutions Using Machine Learning with Linear Regression

“…The application of artificial intelligence and machine learning methods, such as linear regression, has been shown to be effective in addressing similar challenges in the food industry. (Min et al, 2023) , (Jayapal, 2022), (Ding et al, 2023) Several studies have explored the use of machine learning models for food demand prediction and quality control. For instance, a study by (Min et al, 2023) investigated the use of artificial intelligence in modern consumer-driven food systems, suggesting the application of machine learning algorithms like KNN, PCA, and partial least squares regression for detecting food deterioration and contamination.…”