A Framework for Mobile Crowd Sensing and Computing based Systems
Arpita Ray, Sakil Mallick, Sukanta Kumar Mondal, Soumik Paul, Chandreyee Chowdhury, Sarbani Roy · 2018
These days mobile phones are having advanced onboard sensors embedded in it which makes connecting and computing much easier. This has led to realizing novel application paradigms such as crowd sensing and crowd computing. Crowd sensing relies on the sensing capabilities of the mobile devices as well as its communication efficiency to send collected sensed data to the cloud for further processing. On the other hand, mobile crowd computing is an amalgamation of the machine and human intelligence to achieve a given set of tasks in a distributed manner. Thus, crowd computing utilizes the computation and communication capability of the devices. Here in our work, we have come up with a novel approach integrating these two paradigms in a framework that have addressed both the issues of mobile sensing and crowd computing at the same time and utilized the ability of the crowd to solve problems without involving cloud servers in the backend. We have implemented our framework using 4 smart handheld devices for a route-finding application. The devices are connected to each other through BLE (Bluetooth Low Energy) technology. The results obtained can be received both online (using the machine intelligence) and offline (using human intelligence) when no devices are connected to the internet. The device hence receiving the information, in turn, can itself be a contributor in the crowd for other route-finding queries solicited by another user in the crowd.