图书简介
The main objective of this book is to provide insights into recent advances in distributed intelligent circuits, systems and their applications. Distributed intelligence is the key enabler for innovations in machine-to-machine communications. The innovations are directed towards keeping existing algorithms as the base and developing new intelligent systems by employing smart technologies. Artificial intelligence (AI) and, more specifically, deep learning (DL) are receiving significant attention in assisting doctors in the detection of disease patterns without much human intervention. In agriculture, robots automate slow, repetitive and dull tasks, allowing farmers to focus more on improving overall production yields.The evolving trends point to the interface of artificial intelligence with machines being a factor in enhancing the decision-making capabilities of smart machines. This book provides relevant theoretical frameworks that include basic models, algorithms, circuit designs and the latest developments in experimental aspects in the field of distributed intelligence systems for industrial applications. The challenges encountered in the development of models for distributed intelligence systems for environmental monitoring are mitigated with artificial intelligence, machine learning and deep learning. This book identifies challenges and helps in applying solutions in the development of advanced intelligent systems for environmental monitoring.Key FeaturesThe comprehensive approach and detailed topics discussed in this book are beneficial to readers as they provide insights into recent advances in distributed intelligent circuits, systems, and their applicationsThe book provides an overview of intelligence system architecture, algorithms, circuits, and systems for the benefit of fields such as healthcare, agriculture environmental monitoringThis book identifies challenges and helps in applying solutions in the development of advanced intelligent systems for environmental monitoring, also providing future research directions in intelligent systems
An Analytical View of DoS or DDoS Attacks for Network Architecture; Designing Scalable Event-Driven Systems with Message-Oriented Architecture; Bone Fracture Detection Using Machine Learning; Urban Smart Connectivity Using Intelligent Technologies; Artificial Neural Network for RF MEMS Circuits; Management of Covid patients by using IoT-based SmartAmbu Bag; VANETs: Introduction, Communication Protocols, and Challenges; Performance Analysis of Clustering Algorithms in WCS Networks for Energy-Efficient Cooperative Communication; Development of Autonomous Vehicles: Perspectives and Challenges; Review on Time Domain Signal Processing Using TDC; Design and Development of Multipurpose Agriculture Robot (Agrobot)
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