Mobile Crowd‐Sensing for Smart Cities

This chapter reviews the literature of mobile crowd‐sensing (MCS) for smart cities is reviewed thoroughly including motivation, possible applications, and issues that are key to successful deployment of such services. It discusses the challenges of crowd‐sensing in the context of smart city followed by a brief overview of existing frameworks. The chapter also discusses the issues regarding task assignment, user profiling and trustworthiness, design of incentive mechanisms, localized analytics, and security and privacy. While crowd‐sourcing is aimed to utilize collective intelligence of the crowd to solve complex tasks by breaking them down to smaller tasks, crowd‐sensing splits the responsibility of gathering correct information to the crowd. Toward this, a geo‐social model of MCS is proposed. This model is based on a distributed architecture for task design, assessment, and execution. McSense is a framework that is also proposed for MCS. This framework talks about monetary or service incentives given to users.