Vittalis Ayu, Sanata Dharma University, Indonesia
Mobile crowdsensing has become a new paradigm that enables citizens to participate in the sensing process by voluntarily gathering data from their smartphones to accomplish some given task. However, performing the sensing task generate lots of data resulting in various quality of the sensed data and high sensing cost in term of resource consumption. This matter became a significant concern in mobile crowdsensing as the mobile nodes which act as crowd sensors have limited resources. Moreover, an opportunistic mobile crowdsensing mechanism does not require user involvement, so the data collection process must be autonomous and intelligent to sense the data in the proper context. That is why context-awareness is also essential in opportunistic crowdsensing to maintain the sensed data quality. In this mini-review, we revisit the possibility of enhancing the mobile crowdsensing mechanism. We argue that improving the data collection process, including context-awareness, can optimize in-node data availability and sensed data quality. Besides, we also argue that finding optimization on inter-node data exchange mechanisms will increase the quality of the in-node data. Furthermore, smartphones that are related to humans as their owners reflect humans' physical and social behavior. We believe that considering contexts such as human social relationships and human mobility patterns can benefit the optimization strategies.
Mobile Crowdsensing, Data Quality, Context-awareness, Social Relation, Mobility Pattern.