Abstract
With the maturation of Artificial Intelligence of Things, many countries have promoted the smart city concept to improve citizens’ living quality, encouraging many technology developments on the Internet of Behavior (IoB) that utilizes Internet of Things (IoT) to analyze behavioral patterns. For example, during the epidemic of COVID-19, a face-mask detection system and thermal imaging camera can identify if employees fulfill the standards; the equipment can also check if people keep social distances in public gatherings. Smart Care Systems can utilize IoT to analyze older adults’ behaviors, which understand elders’ living and health conditions or track their diets, heartbeats, and sleep through wearable watches. After collecting and analyzing the data, the system will provide feedback regarding personal health suggestions. IoB is at its initial stage that requires combinations from diverse techniques, such as IoT, big data, and artificial intelligence. These technologies analyze behavioral patterns and benefit enterprises to conduct marketing activities or transfer harmful user behaviors. IoB also requires sensor networks to exchange and share data, which makes it essential to consider the energy consumption issue of the sensors. With the development of large-scale sensors and data collection, it is predictable that there will be more and more IoB applications and framework proposed. IoB needs scholars to involve in-depth researches and present more frameworks that are effective, enabling IoB to achieve real-time behavioral analysis. Given IoB's importance and rich applications, it is a very worthwhile topic of research. For this special issue, the goal is to address more than just IoB algorithms; we hope to explore IoB applications and researches in more areas of study and see how IoB models can take a vast amount of available data and help us uncover undiscovered phenomena, retrieve useful knowledge, and draw conclusions and reasoning.