Guest Editorial: Data Science Driven Intelligent IoT

The Internet of things (IoT) is an interconnected system of computing devices, machinery, and digital machines that digitize the real world. The IoT has already affected people's lives, including transportation, housing, food, clothing, health, and remote monitoring. Many home appliances can be controlled through mobile phones and voice. Many applications allow users to improve their quality of life, and even enable the elderly and the disabled to live more conveniently. Data science (DS) is a multidisciplinary approach to discovering, extracting, and presenting insights in data by focusing on data collection, data store and access, data analysis, and data communication techniques. Data science includes descriptive, diagnostic, predictive, and prescriptive capabilities. This means that through data science, administrators can use data to figure out what happened, why it happened, what happened, and what they should do with expected outcomes. Since the automation of an intelligent IoT system requires all tasks of DS, DS will be the most proper candidate technology ready to solve those issues faced by intelligent IoT systems. To collect data for IoT applications features, how to design sensor deployment and their connections via communication networks is the first main problem for intelligent IoT. The next step is how to apply machine learning (ML) and artificial intelligence (AI) algorithms to analyze and interpret insights concerning collected intelligent IoT data. Finally, it is also very crucial to communicate analysis results effectively to users of intelligent IoT devices.