Crowd Density Computation and Diffusion via Internet of Things

Abstract

In smart city services, information systems can provide efficient and effective support during an emergency, and an emergency management system can make use of any available infrastructure network, such as the Internet of Things. However, ordinary communication infrastructures can be prone to disruptions or even failures during emergencies. Hence, it is necessary to present a fallback system in case of such failures. In this article, we propose such a fallback design for emergency management that relies on short-range multihop wireless communications. Specifically, we model the crowd by a multihop ad hoc network consisting of nodes (i.e., civilians with smartphones or wearable devices) that are capable of short-range communications, and address the problem of how to “diffuse” the crowd in an efficient and distributed fashion. The problem is subdivided into crowd density computation and crowd diffusion . We treat the area as a grid that is divided into square cells. Crowd density computation is to compute the density of each cell, for which we present efficient distributed algorithms that compute the density of each grid cell exactly. With the computed densities, crowd diffusion is to design a load-balancing strategy (to direct local movements of individual civilians) such that in a short time the nodes/civilians will become evenly distributed over the entire area. We present a distributed diffusion algorithm that has good performance. We conduct extensive simulations to evaluate the proposed algorithms, and the results corroborate our theoretical analyses.