Due to the spread of Internet of Things (IoT) and artificial intelligence (AI) technology, massive amounts of data have been generated, and abundant smart applications and services have emerged, for example: smart cities; smart healthcare; smart agriculture; and smart robots. However, there is a lack of effective and robust architecture, algorithms, models, and systems to identify and understand real data intentions from raw data with multidimensional noise. For instance, the raw data generated by IoT devices with photoplethysmogram (PPG) sensors is an infinite-dimensional time series which would contain a bulk of redundant information. It is impossible to directly use infinite dimensional data in smart healthcare applications. However, the PPG signal is easily interfered with by noises, such as motion artifacts. The smart applications cannot achieve the expected results by directly using the raw data, thus extracting useful information becomes critical in the IoT and associated smart applications.

One of the key issues in smart IoT applications is understanding the raw data generated by IoT sensors, using knowledge extraction and intelligent data analytics technology. Knowledge extraction and data analytics can extract the potential information and remove redundant information and noise in massive raw data. Discovering useful information in raw data is still a challenge in smart IoT applications, as the data may be generated by various sensors. For example, PPG signals collected by fingertip sensors and ECG or EEG signals collected by electrodes are wave data, digital cameras collect image/video data, microphones collect audio data, and temperature or humidity sensors collect scalar or time-series data. For a real IoT application, it needs to design a special knowledge extraction and data analytics method.

The aim of this Special Issue is to attract research using intelligent data analytic technology to reduce the redundant information and remove the noise in the raw data for IoT and related applications. Our Special Issue aims to invite and encourage researchers and developers to contribute original research and review articles, which enhance IoT systems and related applications.

Potential topics include but are not limited to the following:

• Knowledge Extraction and Mining in IoT
• Architectures, Algorithms, Models and Systems for Knowledge Extraction of IoT
• Smart Data Analytic in IoT
• Edge-based IoT Applications
• Smart Denoising Technology in Real-time IoT Decision Systems
• Data Mining and Management for Edge Computing
• AI-Driven Web of Things
• AI-enabled Knowledge Structure and Engines for IoT systems
• AI-based Network and Communication Technologies
• Security and Privacy of Data Communication in Web-based IoT systems