Artificial Intelligence-based Internet of Things Systems

<p>Part – I. Architecture, Systems, and Services.- Chapter1. Artificial Intelligence-based Internet of Things for Industry 5.0.- Chapter2. IoT Ecosystem: Functioning Framework, Hierarchy of Knowledge and Intelligence.- Chapter3. Artificial Neural Networks and Support Vector Machine for IoT.- Chapter4. The Role of Machine Learning Techniques in Internet of Things Based Cloud Applications.- Chapter5. Deep Learning Frameworks for Internet of Things.- Chapter6. Fog-Cloud enabled Internet of Things using Extended Classifier System (XCS).- Chapter7. Convolutional Neural Network (CNN) – Based Signature Verification via Cloud-enabled Raspberry Pi System.- Chapter8. Machine to Machine (M2M), Radio Frequency Identification (RFID), Software-defined Networking (SDN): Facilitators of Internet of Things.- Chapter9. Architecture, Generative Model, Deep Reinforcement Learning for IoT Applications: Deep Learning Perspective.- Chapter10. Enabling Inference and Training of Deep Learning Models for AI Applications on IoT Edge Devices.- Chapter11. Non-volatile Memory based Internet of Things: A survey.- Chapter12. Integration of AI and IoT approaches for evaluating cyber Security risk on smart city.- Chapter13. Cognitive Internet of Things: Challenges and Solutions.- Part – II. Applications.- Chapter14. An AI Approach to Rebalance Bike Sharing Systems with Adaptive User Incentive.- Chapter15. IoT-driven Bayesian Learning: A Case Study of Reducing Road Accidents of Commercial Vehicles on Highways.- Chapter16. On the Integration of AI and IoT Systems: A Case Study of Airport Smart Parking.- Chapter17. Vision-based End-to-End Deep Learning for Autonomous Driving in Next-Generation IoT Systems.- Chapter18. A Study on the Application of Bayesian Learning and Decision Trees IoT-enabled system in Post-harvest Storage.</p>