Robotics and AI for Cybersecurity and Critical Infrastructure in Smart Cities

This book bridges principles and real-world applications, while also providing thorough theory and technology for the development of artificial intelligence and robots. A lack of cross-pollination between AI and robotics research has led to a lack of progress in both fields. Now that both technologies have made significant strides, there is increased interest in combining the two domains in order to create a new integrated AI and robotics trend. In order to achieve wiser urbanization and more sustainable development, AI in smart cities will play a significant part in equipping the cities with advanced features that will allow residents to safely move about, stroll, shop, and enjoy a more comfortable way of life.

If you are a student, researcher, engineer, or professional working in this field, or if you are just curious in the newest advancements in robotics and artificial intelligence for cybersecurity, this book is for you!

Contenu

Deep Learning in Robotics for strengthening Industry 4.0.: Opportunities, Challenges and Future Directions.- The Design of a Pheromone-based Robotic Varroa Trap for Beekeeping Applications.- Walk Through Event Stream Processing Architecture, Use Cases and Frameworks Survey.- Artificial Intelligence for Cybersecurity: Recent Advancements, Challenges and Opportunities.- Privacy & Security Concerns in Edge Computing-based Smart Cities.- A Taxonomy of DDoS Defense Mechanism in Software Defined Networking (SDN).- Developing instrument for investigation of blockchain technology.- An IoT-based system for expert user supporting to monitor, manage and protect Cultural Heritage Buildings.- Commercialising Blockchain in a Smart City: Autonomous Vehicles, Cryptocurrency, and Contract Law.- Finding all shortest meaningful meta-paths between two vertices of a Secured Large Heterogeneous Information Network using distributed algorithm.- Creation of a Dataset Modeling the Behavior of Malware Affecting the Confidentiality of Data Managed by IoT Devices.- Anomaly Detection on Static and Dynamic Graphs using Graph Convolutional Neural Network.- Secure Medical Data sharing through Blockchain and Decentralized Models.