Omer Rana – författare

This book highlights the integration of cloud, edge, and network computing for sustainable farming and future trends in smart farming, including the role of UAVs, 5G, and advanced artificial intelligence. It covers the use of real‑time environmental data for forecasting and tracking agricultural products and livestock health monitoring.

Key Features

Offers a detailed exploration of the integration of Internet of Things, artificial intelligence, and multimodal intelligence in precision agriculture, covering a wide range of applications from crop management to livestock monitoring Identifies and discusses the challenges of using artificial intelligence and multimodal data in agriculture, providing solutions and techniques to overcome these obstacles Discusses advanced technologies like multispectral and hyperspectral imaging, Internet of Things sensors, and data fusion techniques Highlights emerging trends and future directions in smart farming, including UAVs, 5G, cloud‑edge continuum integration, and federated learning Includes case studies and practical examples demonstrating successful applications of multimodal artificial intelligence in precision farming

The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science engineering, agricultural engineering, and information technology.

This book highlights the integration of cloud, edge, and network computing for sustainable farming and future trends in smart farming, including the role of UAVs, 5G, and advanced artificial intelligence. It covers the use of real‑time environmental data for forecasting and tracking agricultural products and livestock health monitoring.

Key Features

Offers a detailed exploration of the integration of Internet of Things, artificial intelligence, and multimodal intelligence in precision agriculture, covering a wide range of applications from crop management to livestock monitoring Identifies and discusses the challenges of using artificial intelligence and multimodal data in agriculture, providing solutions and techniques to overcome these obstacles Discusses advanced technologies like multispectral and hyperspectral imaging, Internet of Things sensors, and data fusion techniques Highlights emerging trends and future directions in smart farming, including UAVs, 5G, cloud‑edge continuum integration, and federated learning Includes case studies and practical examples demonstrating successful applications of multimodal artificial intelligence in precision farming

The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science engineering, agricultural engineering, and information technology.

This book highlights the integration of cloud, edge, and network computing for sustainable farming and future trends in smart farming, including the role of UAVs, 5G, and advanced artificial intelligence. It covers the use of real‑time environmental data for forecasting and tracking agricultural products and livestock health monitoring.Key FeaturesOffers a detailed exploration of the integration of Internet of Things, artificial intelligence, and multimodal intelligence in precision agriculture, covering a wide range of applications from crop management to livestock monitoringIdentifies and discusses the challenges of using artificial intelligence and multimodal data in agriculture, providing solutions and techniques to overcome these obstaclesDiscusses advanced technologies like multispectral and hyperspectral imaging, Internet of Things sensors, and data fusion techniquesHighlights emerging trends and future directions in smart farming, including UAVs, 5G, cloud‑edge continuum integration, and federated learningIncludes case studies and practical examples demonstrating successful applications of multimodal artificial intelligence in precision farmingThe text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science engineering, agricultural engineering, and information technology.

This book constitutes the refereed proceedings of the 12th IFIP WG 6.12 European Conference on Service-Oriented and Cloud Computing, ESOCC 2026, held in Bolzano, Italy, during September 7–8, 2026.The 9 full papers, 4 short papers and 9 project papers included in this book were carefully reviewed and selected from 40 submissions. They were organized in topical sections as follows: research track and project track.

The work on Autonomic Road Transport Support (ARTS) presented here aims at meeting the challenge of engineering autonomic behavior in Intelligent Transportation Systems (ITS) by fusing research from the disciplines of traffic engineering and autonomic computing. Ideas and techniques from leading edge artificial intelligence research have been adapted for ITS over the last 30 years. Examples include adaptive control embedded in real time traffic control systems, heuristic algorithms (e.g. in SAT-NAV systems), image processing and computer vision (e.g. in automated surveillance interpretation). Autonomic computing which is inspired from the biological example of the body’s autonomic nervous system is a more recent development. It allows for a more efficient management of heterogeneous distributed computing systems. In the area of computing, autonomic systems are endowed with a number of properties that are generally referred to as self-X properties, including self-configuration, self-healing, self-optimization, self-protection and more generally self-management. Some isolated examples of autonomic properties such as self-adaptation have found their way into ITS technology and have already proved beneficial.   This edited volume provides a comprehensive introduction to Autonomic Road Transport Support (ARTS) and describes the development of ARTS systems. It starts out with the visions, opportunities and challenges, then presents the foundations of ARTS and the platforms and methods used and it closes with experiences from real-world applications and prototypes of emerging applications. This makes it suitable for researchers and practitioners in the fields of autonomic computing, traffic and transport management and engineering, AI, and software engineering. Graduate students will benefit from state-of-the-art description, the study of novel methods and the case studies provided.

The work on Autonomic Road Transport Support (ARTS) presented here aims at meeting the challenge of engineering autonomic behavior in Intelligent Transportation Systems (ITS) by fusing research from the disciplines of traffic engineering and autonomic computing. Ideas and techniques from leading edge artificial intelligence research have been adapted for ITS over the last 30 years. Examples include adaptive control embedded in real time traffic control systems, heuristic algorithms (e.g. in SAT-NAV systems), image processing and computer vision (e.g. in automated surveillance interpretation). Autonomic computing which is inspired from the biological example of the body’s autonomic nervous system is a more recent development. It allows for a more efficient management of heterogeneous distributed computing systems. In the area of computing, autonomic systems are endowed with a number of properties that are generally referred to as self-X properties, including self-configuration, self-healing, self-optimization, self-protection and more generally self-management. Some isolated examples of autonomic properties such as self-adaptation have found their way into ITS technology and have already proved beneficial.   This edited volume provides a comprehensive introduction to Autonomic Road Transport Support (ARTS) and describes the development of ARTS systems. It starts out with the visions, opportunities and challenges, then presents the foundations of ARTS and the platforms and methods used and it closes with experiences from real-world applications and prototypes of emerging applications. This makes it suitable for researchers and practitioners in the fields of autonomic computing, traffic and transport management and engineering, AI, and software engineering. Graduate students will benefit from state-of-the-art description, the study of novel methods and the case studies provided.

This book constitutes the proceedings of the Second International Conference on Cloud, Networking for IoT Systems, CN4IoT 2017, and the Second EAI International Conference on ICT Infrastructures and Services for Smart Cities, IISSC 2017, held in Brindisi, Italy, in April 2017. The 26 full papers of both conferences were selected from 39 submissions. CN4IoT presents research activities on the uniform management and operation related to software defined infrastructures, in particular by analyzing limits or advantages in solutions for Cloud Networking and IoT. IISSC papers focus on ICT infrastructures (technologies, models, frameworks) and services in cities and smart communities.

This book constitutes the proceedings of the Second International Conference on Cloud, Networking for IoT Systems, CN4IoT 2017, and the Second EAI International Conference on ICT Infrastructures and Services for Smart Cities, IISSC 2017, held in Brindisi, Italy, in April 2017.

The 26 full papers of both conferences were selected from 39 submissions. CN4IoT presents research activities on the uniform management and operation related to software defined infrastructures, in particular by analyzing limits or advantages in solutions for Cloud Networking and IoT. IISSC papers focus on ICT infrastructures (technologies, models, frameworks) and services in cities and smart communities.