Abstract
Humans are blessed with the intelligence to create links, develop semantic metaphors and models for reasoning; construct rules for decision making; and to form bounded loops for interaction, socialization and knowledge sharing. But machines are inadequate with these extraordinary abilities rather, numerous algorithms and mathematical models can be used to connect physical resources with cyberspaces to control objects and, develop cognitive learning for optimal decision making. Connected users and devices in closed virtual and physical proximity give direction towards the plethora of real-world applications for physical, social and, cyber computing. Because of the increase in social media networking and 5G communication links offer real-time crowdsourcing and sensing as a complementary base for information. Proceeding this idea, in this study we have proposed Cyber-Physical and Social Networks (CPSN) for two fundamental operations in IoV (Internet of Vehicles) as CPSN-IoV; (1) to define conceptual architecture of CPSN-IoV for data-oriented network for smart infrastructure and, (2) to create the significant virtual space where the instances of smart vehicles, devices, and things will have meaningful links with the real world objects where, CPSN-IoV will evolve, emerge, compete, and collaborate with all connected objects to strengthen the decision making process. To investigate the potential impact of our proposed study, we have simulated the taxicab trajectory data of the urban city of Portugal in OMNeT++ for the in-depth understanding of road topology, connected vehicles and things, and their traffic trends; and users’ social media streams in respective edge for efficient route planning. The results of simulation demonstrate that our proposed framework has the ability to achieve human-machine intellectual association for managing the smart environment.
Highlights
We have proposed edge and cloud-based multimodal architecture as Cyber-Physical and Social Networks (CPSN)-Internet of Vehicles (IoV), where all aspects of real-time navigation can strengthen by identifying related patterns and associations using mining and aggregation of VOLUME 8, 2020
For CPSN-IoV real-time traffic scenarios have been studied that contain vehicle mobility in an urban city of Portugal, where the original data set contained instances of 800 vehicles including 15,434 observations
We have categorized CPSN-IoV objects into three categories: (i) Road Side Units (RSU), those responsible for capturing the vehicular and GPS data of the mobile users
Summary
The emergence of technology has encouraged ubiquitous networks that enabled computing capabilities and control for every human 24/7, remotely [2]. This is evident that the interaction between peers can often happen due to shared geolocation. People visiting the same university, museum, shopping mall, sports event, or people travelling by the same bus, train and, flight.
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