Social Internet of Things (SIoT) Localization for Smart Cities Traffic Applications

• Main Authors: Elnour R.A.M., Ali E.S., Yousif I., Saeed R.A., Mokhtar R.A., Hayder G., Khalifa O.O.
• Other Authors: 59354093400
• Format: Conference Paper
• Published: Springer Nature 2024
• Subjects: Localization techniques; Machine learning (ML); Social IoT (SIoT); Social network system (SNS)

In recent years, many applications have appeared that use GPS systems extensively, especially in GPS data-based traffic monitoring systems for phones and smart vehicles as well. These systems help to provide information about movement, speed, geographical location, and some other information related to traffic. Currently, these systems interact with social networks (SNS) on several platforms to communicate between people to share different spatial and temporal information on social networking platforms such as Twitter, Facebook, WhatsApp, and Instagram. These systems can also provide users with information such as weather, traffic details, and several changes in smart cities. Many statistics show that there is massive activity in the use of social networks and benefit from them as sources of many information and exploration for some events related to places in real time. By analyzing social communication data using the machine learning technique (ML), the SNS can achieve the concept of the social Internet of things (SIoT). The concept of localization is social networking platforms allow obtaining location information for different objects through wireless sensor networks for both indoor and outdoor environments. This paper presents an explanation of technical details of localization in the social Internet of things (SIoT) and some applications in which the concept of localization is used. � 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.