This book gives readers a practical introduction into machine learning and sensing techniques, their design and ultimately specific applications that could improve food production. It shows how these sensing and computing systems are suitable for process implementation in food factories.

This book starts by giving the reader an overview of the historic structures of food manufacturing standards and how they defined today's manufacturing. It is followed by a topical introduction for professionals in the food industries in topics such as AI, machine learning, and neural networks. It also includes an explanation of the different sensor systems and their basic principles. It shows how these sensing and computing systems are suitable for process implementation in food factories and what types of sensing systems have already been proven to deliver benefit to the food manufacturing industries. The authors also discuss issues around food safety, labelling, and traceability and how sensing and AI can help to resolve issues. They also use case studies and specific examples that can show the benefit of such technologies compared to current approaches.

This book is a practical introduction and handbook for students, food engineers, technologists and process engineers on the benefits and challenges around modern manufacturing systems following Industry 4.0 approaches.