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Recent research has demonstrated the feasibility of detecting human respiration rate non-intrusively leveraging commodity WiFi devices. However, is it always possible to sense human respiration no matter where the subject stays and faces? What affects human respiration sensing and what's the theory behind? In this paper, we first introduce the Fresnel model(More)
Data quality and budget are two primary concerns in urban-scale mobile crowdsensing applications. In this paper, we leverage the spatial and temporal correlation among the data sensed in different sub-areas to significantly reduce the required number of sensing tasks allocated (corresponding to budget), yet ensuring the data quality. Specifically, we(More)
The original version missed one reference and thus resulted in errors in references. Abstract. Fall is one of the major health threats and obstacles to independent living for elders, timely and reliable fall detection is crucial for mitigating the effects of falls. In this paper, leveraging the fine-grained Channel State Information (CSI) and multi-antenna(More)
This paper presents the design and implementation of RT-Fall, a real-time, contactless, low-cost yet accurate indoor fall detection system using the commodity WiFi devices. RT-Fall exploits the phase and amplitude of the fine-grained Channel State Information (CSI) accessible in commodity WiFi devices, and for the first time fulfills the goal of segmenting(More)
The opportunity to leverage crowd sourcing-based model to facilitate software requirements acquisition has been recognized to maximize the advantages of the diversity of talents and expertise available within the crowd. Identifying well-suited participants is a common issue in crowd sourcing system. Requirements acquisition tasks call for participants with(More)
Defining proper process is an important way of improving software quality and development productivity. However, software process design is a common issue faced by many organizations. The introduction of process patterns provides an effective solution to the challenge. In previous studies, natural language is commonly employed to describe the context of(More)
Despite its importance, walking direction is still a key context lacking a cost-effective and continuous solution that people can access in indoor environments. Recently, device-free sensing has attracted great attention because these techniques do not require the user to carry any device and hence could enable many applications in smart homes and offices.(More)
People living in big cities often suffer from long queuing time waiting for checking out in supermarkets when the crowd density is high. This paper develops QTime, an application to inform queuing time in nearby supermarkets to help people make time-efficient plan about when and which store to go. QTime uses participatory sensing data collected by commodity(More)