The cultivation of crops plays a very important role in agriculture. However, proper maintenance and management are required. Lack of such management would lead to crop loss or reduced crop yields. Hence, the ability to detect and identify diseases on infected crops is a problem of increasing concern. Real-time disease detection systems do not exist in the current agricultural landscape. It requires tremendous amounts of work, expertise in plant diseases, and excessive processing time. Using precision agriculture techniques, combined with AI, a great deal of work is reduced. Contemporary Developments in Agricultural Cyber-Physical Systems provides a forum for researchers and practitioners to exchange ideas and achieve progress in cyber-physical systems by highlighting agricultural applications, advances, and research challenges. The book features chapters on all aspects pertaining to this multidisciplinary paradigm, in particular in its application to sustainable agriculture developments. Covering topics such as automation, monitoring systems, and smart agriculture, this premier reference source is an excellent resource for scientists, healthcare professionals, data analysts, computer scientists, students and educators of higher education, researchers, and academicians.

The internet of things (IoT) has had a major impact on academic and industrial fields. Applying these technologies to healthcare systems reduces medical costs while enriching the patient-centric approach to medicine, allowing for better overall healthcare proficiency. However, usage of IoT in healthcare is still suffering from significant challenges with respect to the cost and accuracy of medical sensors, non-standard IoT system architectures, assorted wearable devices, the huge volume of generated data, and interoperability issues. Incorporating the Internet of Things in Healthcare Applications and Wearable Devices is an essential publication that examines existing challenges and provides solutions for building smart healthcare systems with the latest IoT-enabled technology and addresses how IoT improves the proficiency of healthcare with respect to wireless sensor networks. While highlighting topics including mobility management, sensor integration, and data analytics, this book is ideally designed for computer scientists, bioinformatics analysts, doctors, nurses, hospital executives, medical students, IT specialists, software developers, computer engineers, industry professionals, academicians, researchers, and students seeking current research on how these emerging wireless technologies improve efficiency within the healthcare domain.

Blockchain and artificial intelligence (AI) techniques play a crucial role in dealing with large amounts of heterogeneous, multi-scale, and multi-modal data coming from the internet of things (IoT) infrastructures. Therefore, further discussion on how the fusion of blockchain, IoT, and AI allows the design of models, mathematical models, methodologies, algorithms, evaluation benchmarks, and tools to address challenging problems related to health informatics, healthcare, and wellbeing is required. Contemporary Applications of Data Fusion for Advanced Healthcare Informatics covers the integration of IoT and AI to tackle applications in smart healthcare and discusses the efficient means to collect, monitor, control, optimize, model, and predict healthcare data using blockchain, AI, and IoT. The book also considers the advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. Covering key topics such as disruptive technology, electronic health records, and medical data, this premier reference source is ideal for computer scientists, nurses, doctors, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

The cultivation of crops plays a very important role in agriculture. However, proper maintenance and management are required. Lack of such management would lead to crop loss or reduced crop yields. Hence, the ability to detect and identify diseases on infected crops is a problem of increasing concern. Real-time disease detection systems do not exist in the current agricultural landscape. It requires tremendous amounts of work, expertise in plant diseases, and excessive processing time. Using precision agriculture techniques, combined with AI, a great deal of work is reduced. Contemporary Developments in Agricultural Cyber-Physical Systems provides a forum for researchers and practitioners to exchange ideas and achieve progress in cyber-physical systems by highlighting agricultural applications, advances, and research challenges. The book features chapters on all aspects pertaining to this multidisciplinary paradigm, in particular in its application to sustainable agriculture developments. Covering topics such as automation, monitoring systems, and smart agriculture, this premier reference source is an excellent resource for scientists, healthcare professionals, data analysts, computer scientists, students and educators of higher education, researchers, and academicians.