Artificial Intelligence A Real Opportunity In The Food Industry
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Artificial Intelligence: A Real Opportunity in the Food Industry by Aboul Ella Hassanien,Mona Soliman Pdf
This book emphasizes the latest developments and achievements in AI and related technologies with a special focus on food quality. The book describes the applications, and conceptualization of ideas, and critical surveys covering most aspects of AI for food quality.
Artificial Intelligence for Medicine by Yoshiki Oshida Pdf
The use of artificial intelligence (AI) in various fields is of major importance to improve the use of resourses and time. This book provides an analysis of how AI is used in both the medical field and beyond. Topics that will be covered are bioinformatics, biostatistics, dentistry, diagnosis and prognosis, smart materials, and drug discovery as they intersect with AI. Also, an outlook of the future of an AI-assisted society will be explored.
AI in Food Industry for Food Products Quality Inspection by Dr Syeda Sumera Ali Pdf
Artificial Intelligence (AI) is a branch of science & engineering that deals with machine learning (ML) and Deep Learning (DL) are the commonly used algorithms in the field of Artificial Intelligence namely. Models learn from data available and used by customers, government agencies & companies for sake of analysis. In food industries, the design of standard reliable procedures to inspect & control the quality of products is a major objective. The deployment of AI to achieve better customer experience, supply chain, management, improve operational efficiency, reduction in material movements , vehicle activity, and better results in the business . Automation in the food industry for sake of control a process at optimum level, reducing costs & time, monitor food processing, minimize the error, respond to production issues, safety, tracking & improving quality . AI has various applications includes sorting fresh produce, effective cleaning, consumer preference, saving time and resources.
Impactful Technologies Transforming the Food Industry by Ayd?n, ?ule,Özgül Katlav, Eda,Çaml?ca, Koray,Yönet Eren, Firdevs Pdf
In today's rapidly evolving world, technology has permeated every aspect of our lives, and the culinary world is no exception.Impactful Technologies Transforming the Food Industry delves into the revolutionary role of technology in transforming the way we produce, prepare, and experience food. From restaurant operations to the dining experience and the rise of food delivery services, this book explores the profound impact of technology on the food industry. Impactful Technologies Transforming the Food Industry provides an in-depth exploration of the objectives, motivations, and consequences associated with the adoption of technology in the food industry through meticulous analysis and real-world examples. From advanced ordering systems and kitchen automation to virtual reality and interactive dining experiences, readers gain valuable insights into how technology has revolutionized the way food businesses operate and how it has reshaped the relationship between consumers and food. This book also addresses the emergence of food delivery services, the ethical considerations of technology in the industry, and the potential future trajectory of food tech. It is an essential resource for food industry professionals, students, policymakers, and consumers interested in the intersection of gastronomy and technology.
Sensing and Artificial Intelligence Solutions for Food Manufacturing by Daniel Hefft,Charles Oluwaseun Adetunji Pdf
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.
Artificial Intelligence Applications in Agriculture and Food Quality Improvement by Khan, Mohammad Ayoub,Khan, Rijwan,Praveen, Pushkar Pdf
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.
Sustainable Food Systems (Volume II) by Monika Thakur Pdf
Sustainable Food System has cutting-edge green & circular Technologies, food Safety & diversity that aims to provide quality and safe foods in an environmentally conscious and sustainable way. The book addresses both the theoretical and applied aspects of sustainable food diverse food systems. This concept of Sustainable Food System under SDG Goals is such a vast concept that, it has been impossible to highlight all the concepts in one volume. Therefore, the Editor have compiled this voluminous, comprehensive and compendious approach as balanced and organized structure of work as: Sustainable Food System Volume I & II. A Sustainable Food System (SFS) is a comprehensive food system and Volume II targets the Novel Sustainable Green Food Processing Technologies, Circular Strategies for Recovery & Valorization and the overall sustainable techniques for Food Safety & Food Diversity. The book has a very comprehensive outline, divided in 3 major sections and further 20 different chapters. All chapters in different sections will be written by key scientists with diverse backgrounds in either industry / R&D / academia, and will provide an update on emerging ideas and sustainable technologies as well as vision for the future. The Section 5: Novel Sustainable Green Food Processing Technologies primarily focusing on the novel green different food processing technologies in different food categories. The Section 6: Circular Strategies for Recovery & Valorization, deals with different circular strategies for valorization of the food products. The Section 7: Sustainable Techniques for Food Safety & Food Diversity, will cover the food safety trends and food diversities nationally & internationally.
Artificial Intelligence by Harvard Business Review Pdf
Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business.
Food Structure Engineering and Design for Improved Nutrition, Health and Well-being by Miguel Angelo Parente Ribei Cerqueira,Lorenzo Miguel Pastrana Castro Pdf
Food Structure Engineering and Design for Improved Nutrition, Health and Wellbeing presents new insights on the development of new healthy foods and the understanding of food structure effect on nutrition, health and wellbeing. Sections cover a) New ingredients, typicity and ethnicity of foods in different cultures and geographic regions; b) New and innovative strategies for food structure development; c) Strategies to address the challenges for healthier food products, such the reduction of sugar, salt and fats; d) Assessment of health effect of foods by in vitro and in vivo tests, and more. Edited by experts in the field, and contributed by scientists of different areas such as nutritionists and food engineers, this title offers a broad overview of the field to the readers, boosting their capability to integrate different aspects of product development. Brings examples and strategies on how to improve the nutritional value of foods through food engineering and design Includes a broad vision of food trends and their impact in new product development Features the newest methodologies and techniques for the analysis of developed food products
Towards Unmanned Apple Orchard Production Cycle by Zhao Zhang,Xufeng Wang Pdf
The book provides the most recent technology for sensing and automation in apple production cycle in terms of bagging robotics, flower pollination robotics, pruning robotics, and harvest robotics. It does not only summarize the development of technology progress, but also discuss the future trend for unmanned apple production cycle. Though apple production still mainly relies on manual labor, a huge number of innovative technologies emerge during the past years, which pave the road for unmanned apple orchard management. A book summarizing all these new and innovative technologies is needed, to provide an easy approach to understand this field quickly and comprehensively, which drives the publication of this book. This book is a useful reference for students, researchers, and practitioners in the field of apple production.
What Are Marketing Information and Artificial Intelligence Customer Psychological Predictive by Johnny Ch Lok Pdf
(AI) digital data gather technology predicts food consumer behavior's main barriersWhat are the main barriers to food industry? When the food manufacturer applies (AI) big data gather technology to predict food consumer behavior? The barriers include that the food manufacturer / provider needs to decide whether when the right time is applied to the right (AI) digital big data prediction tool channel to find the right food consumers to be chose to full food consumption satisfactory questionnaires, how to gather multi-class food consumption classifiers on real-world food consumers transactional data from the food sale domain consistently to show the critical numbers of different kinds of food items at which the predictive performance most accurate? So, any food manufacturer / provider's advanced in (AI) digital data gather warehousing and management technologies can provide that opportunities for food business to enhance long term relationship with the food providers' clients. However, food industry's (AI) digital data gather aims to improve food customer product targeting, increase food customer loyalty and food purchase probability to the food supplier. To effective identify, understand and satisfy the needs of their food customers, the food suppliers need to develop the right (AI) digital questionnaire questions and find the right food customers to fill every right questions from every digital questionnaire at the right time through the right channel. Above of all these, they will be the barriers when one food supplier expects its (AI) digital data gather questionnaires which can conclude the most accurate prediction concerns any kinds of consumer food product choices. So, such as (AI) digital data prediction model, it is needed to incorporate into the food market segmentation, food customer targeting, and food challenging decisions with the goal of maximizing the total food customer lifetime. For example, (AI) big data gather transaction data is reasonable and accurate for building predictive models. Transaction data can be electronically collected and readily made available for data mining in lot quantity at minimum extra costs.Suggestion to apply (AI) prototypes of food customer profiles method to predict food customer behavioral changes. Prototypes of food customer profiles mean to be extracted from the discovered bins and multi-class classifies models are built using those prototypes. The learned models can than be used to predict the class of food customer profiles ( e.g. restaurants, school canteens, supermarkets etc. food suppliers) based on their food purchases. The approach is validated on the case study of a food retail and food service company operating in food and beverages market.So, a food customer profile, it is a description (AI) data gather tool will record every of food customer using available information, which help in understanding their background and food consumption behavior. (AI) data gather tool can well develop every food customer profile, every food customer data is essential in food market analysis as they aid food suppliers in saving time and money by highlighting the real potential food consumers whose needs are to be met rather a range of individuals.So, (AI) data gather tool can record every food consumer profile and every can be factual or behavioral food consumption. A factual food customer profile consists of a set of characteristics for (AI) big data gather record, e.g. demographic information, such as food customer name, gender, birth date, when a behavioral food customer profile consists of what the food customer is actually doing and is usually derived from (AI) digital transactional data gather record.
AI Renaissance: Reshaping Dairy and Food Industry Professionals for the Future by Pavan Kumar Reddy C Pdf
"Diving into the heart of innovation, 'AI Renaissance: Reshaping Dairy and Food Industry Professionals for the Future' is a groundbreaking exploration of the intersection between artificial intelligence and the food & dairy world. With captivating insights and inspiring anecdotes, this book illuminates the transformative power of AI in revolutionizing food and dairy manufacturing, from optimizing production processes to enhancing quality control. Through compelling narratives and visionary perspectives, readers are empowered to embrace the technological advancements driving the industry forward, fostering a new era of creativity, efficiency, and sustainability. Prepare to embark on a journey of discovery, innovation, and endless possibilities."
Artificial Intelligence Raises: Efficiency and Productivity by Johnny Ch Lok Pdf
(AI) digital data gather technology predicts food consumer behavior's main barriersWhat are the main barriers to food industry? When the food manufacturer applies (AI) big data gather technology to predict food consumer behavior? The barriers include that the food manufacturer / provider needs to decide whether when the right time is applied to the right (AI) digital big data prediction tool channel to find the right food consumers to be chose to full food consumption satisfactory questionnaires, how to gather multi-class food consumption classifiers on real-world food consumers transactional data from the food sale domain consistently to show the critical numbers of different kinds of food items at which the predictive performance most accurate? So, any food manufacturer / provider's advanced in (AI) digital data gather warehousing and management technologies can provide that opportunities for food business to enhance long term relationship with the food providers' clients. However, food industry's (AI) digital data gather aims to improve food customer product targeting, increase food customer loyalty and food purchase probability to the food supplier. To effective identify, understand and satisfy the needs of their food customers, the food suppliers need to develop the right (AI) digital questionnaire questions and find the right food customers to fill every right questions from every digital questionnaire at the right time through the right channel. Above of all these, they will be the barriers when one food supplier expects its (AI) digital data gather questionnaires which can conclude the most accurate prediction concerns any kinds of consumer food product choices. So, such as (AI) digital data prediction model, it is needed to incorporate into the food market segmentation, food customer targeting, and food challenging decisions with the goal of maximizing the total food customer lifetime. For example, (AI) big data gather transaction data is reasonable and accurate for building predictive models. Transaction data can be electronically collected and readily made available for data mining in lot quantity at minimum extra costs.Suggestion to apply (AI) prototypes of food customer profiles method to predict food customer behavioral changes. Prototypes of food customer profiles mean to be extracted from the discovered bins and multi-class classifies models are built using those prototypes. The learned models can than be used to predict the class of food customer profiles ( e.g. restaurants, school canteens, supermarkets etc. food suppliers) based on their food purchases. The approach is validated on the case study of a food retail and food service company operating in food and beverages market.
Machine Learning for Healthcare Applications by Sachi Nandan Mohanty,G. Nalinipriya,Om Prakash Jena,Achyuth Sarkar Pdf
When considering the idea of using machine learning in healthcare, it is a Herculean task to present the entire gamut of information in the field of intelligent systems. It is, therefore the objective of this book to keep the presentation narrow and intensive. This approach is distinct from others in that it presents detailed computer simulations for all models presented with explanations of the program code. It includes unique and distinctive chapters on disease diagnosis, telemedicine, medical imaging, smart health monitoring, social media healthcare, and machine learning for COVID-19. These chapters help develop a clear understanding of the working of an algorithm while strengthening logical thinking. In this environment, answering a single question may require accessing several data sources and calling on sophisticated analysis tools. While data integration is a dynamic research area in the database community, the specific needs of research have led to the development of numerous middleware systems that provide seamless data access in a result-driven environment. Since this book is intended to be useful to a wide audience, students, researchers and scientists from both academia and industry may all benefit from this material. It contains a comprehensive description of issues for healthcare data management and an overview of existing systems, making it appropriate for introductory and instructional purposes. Prerequisites are minimal; the readers are expected to have basic knowledge of machine learning. This book is divided into 22 real-time innovative chapters which provide a variety of application examples in different domains. These chapters illustrate why traditional approaches often fail to meet customers’ needs. The presented approaches provide a comprehensive overview of current technology. Each of these chapters, which are written by the main inventors of the presented systems, specifies requirements and provides a description of both the chosen approach and its implementation. Because of the self-contained nature of these chapters, they may be read in any order. Each of the chapters use various technical terms which involve expertise in machine learning and computer science.