Updated at January 30, 2024
— 2 min read
Date of Conference: 03-05 November 2023
Date Added to IEEE Xplore: 30 January 2024
2023 IEEE Silchar Subsection Conference (SILCON)
IEEE
10.1109/SILCON59133.2023.10404183
Silchar, India
Artificial Intelligence (AI) has become a driving force in the food industry, revolutionizing food processing, distribution, and consumption. This research article explores the transformative role of AI in addressing the challenges of growing global food demand while striving for sustainability. The article highlights AI’s impact on optimizing food production and distribution through data-driven decision-making and workforce analytics. AI-driven insights enable improved product quality, safety, and forecasting, contributing to a more efficient and innovative food sector. Various fields of AI, including machine learning, natural language processing, deep learning, robotics, vision, and fuzzy logic, have reshaped food processing practices. Machine learning enhances agricultural productivity, quality control, and personalized nutrition recommendations. Computer vision systems ensure quality assessment and defect identification in food products. The article explores AI applications in beverage production, hot beverages, sorting and classification of fruits, dairy industry, 3D printing, bakeries, and restaurants, enhancing production efficiency and customer experiences. The article also discusses guidelines for selecting appropriate AI techniques, considering research complexity, data availability, and algorithm performance, aiding researchers and practitioners in choosing suitable AI solutions. Despite remarkable advancements, AI faces challenges such as the absence of human intuition, data dependencies, and initial implementation costs. Continued research and collaboration are crucial to fully harness AI’s potential for building a resilient and technologically advanced food sector. Embracing AI-driven solutions, the food industry can lead towards a sustainable and efficient future.
I'm Kushagra, a junior year undergraduate student. Intrigued by Machine Learning, Deep Learning related research.
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