Conceptual Analytics on Integration of Network Technologies with Crowdsourcing Infrastructure

Abstract

Technology seeks a new dimension as collaboration of various methods and technologies in transmission of data. Crowdsourcing enables the availability of huge data over a variety of networks. It is important to understand the needs of the management and monitoring of such data over a long distance and among a huge population especially among a big crowd like that of temples and other public places. Hence integration of network technologies has to be considered for effective attainment of data transfer with high speed and better performance that includes latency. The paper conducts analytics of various collaborated network technologies that was utilised to handle huge data from a crowdsourced network. The network technologies considered for the reviews are Edge computing, Fog computing, IoT based sensors, mobile technologies and cloud-based platforms. After significant analysis of all the research works, it was identified that edge computing has been the chief network technology used to transmit crowdsourced data with speed and efficiency. Cloud platforms assist the transferred data to be stored with privacy and security. The IoT sensors and Fog computing helped in detecting the data and also to increase the bandwidth and improve latency problems. The research gap identified was to enhance the speed and efficiency of transmission in public related problems like surveillance and handling public or social media database which seemed to be more challenging and encouraging future research works.