Revolutionizing Autonomous Vehicle Intelligence with Cutting-Edge Spatial Crowdsourcing Framework

Crowdsourcing is an approach for performing spatial tasks that depends upon the efforts of many people and has received increasing attention in the past couple of years. Because of their effectiveness and simplicity, crowdsourcing work is frequently conducted online so-called mobile crowdsourcing. Due to the special challenges of engaging in real physical locations, this conventional technique might sometimes fail. As a result, a completely novel model for data collecting known as advanced spatial crowdsourcing (ASC) has grown up in recent years. In this paper, review of the existing work has been done and suggested the methodology by constructing the architecture and features of crowdsourcing, including Mobile Crowdsourcing, Spatial Crowdsourcing, Autonomous Vehicle Crowdsensing, and much more. As crowdsourcing is very important for autonomous vehicle, our research suggested the integration of Advanced crowdsourcing with Autonomous vehicle & real-time intelligent system. The objective of this research is to identify and explore the ITS (Intelligent Transportation System) technology that is made possible by IoT devices, as well as vehicle safety, vehicle security, and intelligent vehicle systems implementing advanced crowdsourcing. Finally, research aims to offer a variety of crowdsourcing applications and services like healthcare, Smart city, autonomous vehicle, and advanced applications.