Abstract
The food industry is one of the most rapidly evolving sectors, with new technological advancements constantly emerging. Artificial intelligence (AI) has emerged as a crucial component in this industry, revolutionizing various aspects of food production, from recipe generation to quality control. In recent years, AI has been integrated into the food industry in a big way, and its impact on the industry has been profound. An important benefit of AI in the food industry is its capacity to automate monotonous tasks, freeing up human workers for more complex responsibilities. AI also aids in recipe generation, enabling food companies to create innovative products that cater to consumer preferences. Moreover, AI plays a crucial role in maintaining quality control, guaranteeing that food products adhere to safety and quality requirements before they are delivered to consumers. To provide insights into the impact of AI in the food industry, this chapter will present case studies highlighting successful AI implementations.
TopIntroduction To Ai In Food Industry
The food industry is a rapidly evolving sector, constantly embracing new technological advancements (Hassoun et al.,2022). One such technology that has gained significant importance is AI, which plays a vital role in various aspects of food production, ranging from recipe creation to quality assurance. Over the past few years, AI has been extensively integrated into the food industry, resulting in a significant impact on its operations.
Due to the expected increase in global population, food demand is projected to rise significantly by 2050, with estimates ranging from 59 to 98% (Elferink et al.,2016). As a result, the use of AI has become increasingly prevalent in various aspects of the food industry which encompasses various areas such as supply chain, sorting food, optimizing production processes, improving quality, and maintaining industrial hygiene (Mavani et al.,2022).
AI brings several benefits to the food industry, including the automation of routine and repetitive tasks, which allows human workers to focus on more complex and critical tasks. With AI, food companies can also generate new and innovative recipes that appeal to consumers. Additionally, AI can help with quality control, making sure the safety and quality of food products before they reach consumers. By leveraging AI technologies, the food industry can enhance productivity, reduce waste, and improve the overall customer experience.
Key Terms in this Chapter
Machine Learning (ML): ML is a subset of AI that trains algorithms to make predictions and decisions based on input data, rather than being explicitly programmed to perform a specific task.
Deep Learning: DL is a subset of machine learning that utilizes artificial neural networks to model and train these networks on large datasets, allowing them to learn patterns and make predictions or classifications and solve complex problems.
Supply Chain Management: Supply Chain Management involves the management of the flow of goods and services from raw material acquisition to final product delivery.
Artificial Intelligence: AI is a computer science field focused on developing intelligent machines capable of performing tasks that typically require human intelligence that include learning, problem-solving, perception, and decision-making.
Artificial Neural Network: Artificial Neural Networks are computational models composed of interconnected processing elements called neurons that receive inputs, process them using predefined activation functions, and produce outputs.
Computer Vision: Computer vision is a branch of AI that enables machines to interpret and understand visual data. It involves the development of algorithms and techniques that allow machines to see, perceive, and recognize objects, patterns, and features in images and videos.
Quality Control: Quality control refers to a set of procedures implemented to ensure that manufactured products or performed services meet predefined quality criteria or client/customer requirements.