Intelligence of Things: Technologies and Applications

This book constitutes the refereed proceedings of the First Conference on Intelligence of Things (ICIT 2022), held in Hanoi, Vietnam, in August 2022. A total of 40 full papers in this book have been rigorously peer-reviewed and selected from over 100 submissions. The papers focused on the intelligence of things (AIoT) studies are organized in the following parts: theoretical intelligence analyses, intelligence services and applications, and intelligence service experiments. This book provides interested students and engineers with comprehensive and cutting-edge studies in the fields.

Focuses on the integration AI technologies into the IoT infrastructure Covers proceedings of the 1st International Conference on Intelligence of Things (ICIT 2022) Provides state-of-the-art knowledge in the field of Intelligence of Things

Inhalt
Structural Health Monitoring and IoT: Opportunities and Challenges.- Semantic Interoperability Issues and Challenges in IoT: A Brief Review.- An Intelligent Method Based on Dissimilarity Measure Picture Fuzzy and Apply to Supplier Selection.- A New Intelligent Computing Method for Scheduling and Crashing Projects with Fuzzy Activity Completion Times.- A Study of Filter-Based Feature Selection in Software Fault Prediction.- Applying Lecturer Expectation and Learning Retention to an Adaptive Learning System.- An Intelligent Approach for Multi-Criterial Decision Making using Similarity of Intuitionistic Fuzzy Sets.- Edge Computing For Wireless Sensor Network.- Mathematical Expression Detection in Camera Captured Document Images.- A-DEM: The Adaptive Approximate Approach for the Real Scheduling Problem.- A Framework to Verify the ABAC Policies in Web Applications.- Aspect-based Sentiment Analysis with Deep Learning: A Multidomain and Multitask Approach.- Combined Local and Global Featuresfor Action Recognition from Motion Sensors.- Combining Artificial Intelligence with the Internet of Things in Microalgae Cultivation.- Computer-Aided Provisional Diagnosis System Using Machine Learning.<p