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Poor air quality has been responsible for millions of premature deaths. Acknowledging the critical role air quality plays in the future of their populations, governments across the world have been installing networks of fixed location air quality ...

Crowd sensing effectively solves the dilemma of massive data collection faced by most data-driven applications. Recently, mobile edge computing (MEC) is proposed to extend the frontier of cloud to the network edge so that it is quite suitable to integrate ...

In urban transit systems, discovering anomalous bus-driving behaviors in time is an important technique for monitoring the safety risk of public transportation and improving the satisfaction of passengers. This paper proposes a two-phase approach ...

Accurately profiling potholes on road surfaces not only helps eliminate safety related concerns and improve commuting efficiency for drivers, but also reduces unnecessary maintenance cost for transportation agencies. In this paper, we propose a ...

IoT sensors for measuring various sea water parameters, are explored here, aiming towards an educational context, in order to lead to a deeper understanding of the use of aquatic environments as natural resources, and towards the adoption of ...

The Crowd Sensing(CS)1 system includes a sensing platform with several back-end servers and a lot of smartphone users embedded in different types of sensors. First, the platform announces multiple tasks, and then the users voluntarily join the the task ...

With the proliferation of sensor-rich mobile devices, crowd sensing has emerged as a new paradigm of collecting information from the physical world. However, the sensory data provided by the participating workers are usually not reliable. In order to ...

Crowd-centric research is receiving increasingly more attention as datasets on crowd behavior are becoming readily available. We have come to a point where many of the models on pedestrian analytics introduced in the last decade, which have mostly not ...

In an era characterized by unprecedented levels of digital human communication, the educational process at a university campus lacks proper tools for cooperation between instructors and students. On the other hand, students may not always know how to ...

This paper presents Wi-Crowd, a system for visualizing the crowd level based on Wi-Fi usage data on campus by presenting it on an interactive 3D graphics, including map rotation, zoom-in/out, and display selections. The system uses animation to display ...

Researchers from different disciplines have examined crowd behavior in the past by employing a variety of methods including ethnographic studies, computer vision techniques and manual annotation based data analysis. However, because of the inherent ...

In this study, we propose a crowd sensing framework with the existence of execution uncertainty and a given budget. Our framework consists of three stages: Task Selection, Task Allocation, and Payment. Within each stage, we define the design problems ...

Recent studies have introduced co-location attacks as a powerful way to extract social information from location traces. However, these attacks all rely by some means on the position of targeted users. This requires the attacker to be able to locate ...

The recent advances of mobile devices, online social networks, and the emergence of the Internet of Things have driven the corresponding data collection and analytics to planetary scale. It is, thus, essential to provide a forum to discuss the technical ...

Researchers have examined crowd behavior in the past by employing a variety of methods including ethnographic studies, computer vision techniques and manual annotation based data analysis. However, because of the resources to collect, process and ...

The recent proliferation of human-carried mobile devices has given rise to mobile crowd sensing (MCS) systems that outsource the collection of sensory data to the public crowd equipped with various mobile devices. A fundamental issue in such systems is ...

Mobile devices and their sensors facilitate the development of a large range of environment-sensing applications and systems. Crowd sensing is used to feed smart city applications with anonymous but still relevant data. The quality and success of smart ...

The recent proliferation of human-carried mobile devices has given rise to the crowd sensing systems. However, the sensory data provided by individual participants are usually not reliable. To identify truthful values from the crowd sensing data, the ...

With the popular usage of mobile devices and smartphones, crowd sensing becomes pervasive in real life when human acts as sensors to report their observations about entities. For the same entity, users may report conflicting information, and thus it is ...

Understanding crowd dynamics of large-scale events is crucial to deliver a pleasant experience for the participants. In this paper, we propose a novel hybrid participatory sensing approach to capture large group dynamics. Specifically, our approach is ...