Sensing And Artificial Intelligence Solutions For Food Manufacturing

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.

Food is a necessary aspect of human life, and agriculture is crucial to any country’s global economy. Because the food business is essential to both a country’s economy and global economy, artificial intelligence (AI)-based smart solutions are needed to assure product quality and food safety. The agricultural sector is constantly under pressure to boost crop output as a result of population growth. This necessitates the use of AI applications. Artificial Intelligence Applications in Agriculture and Food Quality Improvement discusses the application of AI, machine learning, and data analytics for the acceleration of the agricultural and food sectors. It presents a comprehensive view of how these technologies and tools are used for agricultural process improvement, food safety, and food quality improvement. Covering topics such as diet assessment research, crop yield prediction, and precision farming, this premier reference source is an essential resource for food safety professionals, quality assurance professionals, agriculture specialists, crop managers, agricultural engineers, food scientists, computer scientists, AI specialists, students, libraries, government officials, researchers, and academicians.

Ocean plays a significant role in energy production, human health and economy. Seawater, seaweed, microalgae, yeast, bacteria act as feedstock for biofuels and bioproducts. This book focuses on the application of marine biomass for production of energy, fertilizers, nutraceuticals, pharmaceuticals, cosmetics, bioplastics and other value-added products. It presents technological advancements and optimization strategies for enhancing process efficiency, overcoming challenges and maximizing the potential of marine-based biorefinery. It also describes how marine resources can be applied to wastewater treatment, eco-restoration, environment protection and sustainable development.

It is essential to harness the potential of nanotechnology in a rapidly evolving industrial environment. As industries grapple with the demand for more advanced, efficient, and sustainable solutions, the intricate amalgamation of chemistry, materials science, physics, biology, and technology in nanotechnology emerges as both a beacon of promise and a complex puzzle. The groundbreaking book, Sustainable Approach to Protective Nanocoatings, serves as a transformative solution. Tailored for academic scholars seeking comprehensive insights, this book navigates the labyrinth of nanotechnology with precision, offering a roadmap for leveraging nanostructured materials and coatings to meet the demands of the modern industrial world. By seamlessly weaving together the intricate tapestry of research methodologies, applications, and technological advances, the book emerges as an indispensable resource for those poised at the intersection of academia and industry.

Food Engineering Innovations Across the Food Supply Chain discusses the technology advances and innovations into industrial applications to improve supply chain sustainability and food security. The book captures the highlights of the 13th International Congress of Engineering ICEF13 under selected congress themes, including Sustainable Food Systems, Food Security, Advances in Food Process Engineering, Novel Food Processing Technologies, Food Process Systems Engineering and Modeling, among others. Edited by a team of distinguished researchers affiliated to CSIRO, this book is a valuable resource to all involved with the Food Industry and Academia. Feeding the world’s population with safe, nutritious and affordable foods across the globe using finite resources is a challenge. The population of the world is increasing. There are two opposed sub-populations: those who are more affluent and want to decrease their caloric intake, and those who are malnourished and require more caloric and nutritional intake. For sustainable growth, an increasingly integrated systems approach across the whole supply chain is required. Focuses on innovation across the food supply chain beyond the traditional food engineering discipline Brings the integration of on-farm with food factory operations, the inclusion of Industry 4.0 sensing technologies and Internet of Things (IoT) across the food chain to reduce food wastage, water and energy inputs Makes a full intersection into other science domains (operations research, informatics, agriculture and agronomy, machine learning, artificial intelligence and robotics, intelligent packaging, among others)

This book provides in-depth insights into use cases implementing artificial intelligence (AI) applications at the edge. It covers new ideas, concepts, research, and innovation to enable the development and deployment of AI, the industrial internet of things (IIoT), edge computing, and digital twin technologies in industrial environments. The work is based on the research results and activities of the AI4DI project, including an overview of industrial use cases, research, technological innovation, validation, and deployment. This book’s sections build on the research, development, and innovative ideas elaborated for applications in five industries: automotive, semiconductor, industrial machinery, food and beverage, and transportation. The articles included under each of these five industrial sectors discuss AI-based methods, techniques, models, algorithms, and supporting technologies, such as IIoT, edge computing, digital twins, collaborative robots, silicon-born AI circuit concepts, neuromorphic architectures, and augmented intelligence, that are anticipating the development of Industry 5.0. Automotive applications cover use cases addressing AI-based solutions for inbound logistics and assembly process optimisation, autonomous reconfigurable battery systems, virtual AI training platforms for robot learning, autonomous mobile robotic agents, and predictive maintenance for machines on the level of a digital twin. AI-based technologies and applications in the semiconductor manufacturing industry address use cases related to AI-based failure modes and effects analysis assistants, neural networks for predicting critical 3D dimensions in MEMS inertial sensors, machine vision systems developed in the wafer inspection production line, semiconductor wafer fault classifications, automatic inspection of scanning electron microscope cross-section images for technology verification, anomaly detection on wire bond process trace data, and optical inspection. The use cases presented for machinery and industrial equipment industry applications cover topics related to wood machinery, with the perception of the surrounding environment and intelligent robot applications. AI, IIoT, and robotics solutions are highlighted for the food and beverage industry, presenting use cases addressing novel AI-based environmental monitoring; autonomous environment-aware, quality control systems for Champagne production; and production process optimisation and predictive maintenance for soybeans manufacturing. For the transportation sector, the use cases presented cover the mobility-as-a-service development of AI-based fleet management for supporting multimodal transport. This book highlights the significant technological challenges that AI application developments in industrial sectors are facing, presenting several research challenges and open issues that should guide future development for evolution towards an environment-friendly Industry 5.0. The challenges presented for AI-based applications in industrial environments include issues related to complexity, multidisciplinary and heterogeneity, convergence of AI with other technologies, energy consumption and efficiency, knowledge acquisition, reasoning with limited data, fusion of heterogeneous data, availability of reliable data sets, verification, validation, and testing for decision-making processes.

This book reviews recent innovations in the smart agriculture space that use the Internet of Things (IoT) and sensing to deliver Artificial Intelligence (AI) solutionsto agricultural productivity in the agricultural production hubs. In this regard, South and Southeast Asia are one of the major agricultural hubs of the world, facing challenges of climate change and feeding the fast-growing population. To address such challenges, a transboundary approach along with AI and BIG data for bioinformatics are required to increase yield and minimize pre- and post-harvest losses in intangible climates to drive the sustainable development goal (SDG) for feeding a major part of the 9 billion population by 2050 (Society 5.0 SDG 1 & 2). Therefore, this book focuses on the solution through smart IoT and AI-based agriculture including pest infestation and minimizing agricultural inputs for in-house and fields production such as light, water, fertilizer and pesticides to ensure food security aligns with environmental sustainability. It provides a sound understanding for creating new knowledge in line with comprehensive research and education orientation on how the deployment of tiny sensors, AI/Machine Learning (ML), controlled UAVs, and IoT setups for sensing, tracking, collection, processing, and storing information over cloud platforms for nurturing and driving the pace of smart agriculture in this current time. The book will appeal to several audiences and the contents are designed for researchers, graduates, and undergraduate students working in any area of machine learning, deep learning in agricultural engineering, smart agriculture, and environmental science disciplines. Utmost care has been taken to present a varied range of resource areas along with immense insights into the impact and scope of IoT, AI and ML in the growth of intelligent digital farming and smart agriculture which will give comprehensive information to the targeted readers.

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