Related papers: Smartphone-based crowdsourcing for estimating the …
Internet-connected smart devices are increasing at an exponential rate. These powerful devices have created a yet-untapped pool of idle resources that can be utilised, among others, for processing data in resource-depleted environments. The…
The increasing practice of engaging crowds, where organizations use IT to connect with dispersed individuals for explicit resource creation purposes, has precipitated the need to measure the precise processes and benefits of these…
The location of Internet hosts is frequently used in distributed applications and networking services. Examples include customized advertising, distribution of content, and position-based security. Unfortunately the relationship between an…
Fingerprinting is a popular indoor localization technique since it can utilize existing infrastructures (e.g., access points). However, its site survey process is a labor-intensive and time-consuming task, which limits the application of…
Crowdsourcing provides a popular paradigm for data collection at scale. We study the problem of selecting subsets of workers from a given worker pool to maximize the accuracy under a budget constraint. One natural question is whether we…
Crowd mobility has been paid attention for the Internet-of-things (IoT) applications. This paper addresses the crowd estimation problem and builds an IoT service to share the crowd estimation results across different systems. The crowd…
Rapid urbanization places increasing stress on already burdened transportation systems, resulting in delays and poor levels of service. Billions of spatiotemporal call detail records (CDRs) collected from mobile devices create new…
We propose a streaming algorithm for the binary classification of data based on crowdsourcing. The algorithm learns the competence of each labeller by comparing her labels to those of other labellers on the same tasks and uses this…
Smartphones sensors are now commonly used by a worldwide audience thanks to their availability, high connectivity, and versatility. Here, we present a methodology to use a collection of smartphones, namely a fleet, as a distributed network…
Social Media provides researchers with an unprecedented opportunity to gain insight into various facets of human life. Health practitioners put a great emphasis on pinpointing socioeconomic status (SES) of individuals as they can use to it…
This white paper is the outcome of the W\"urzburg seminar on "Crowdsourced Network and QoE Measurements" which took place from 25-26 September 2019 in W\"urzburg, Germany. International experts were invited from industry and academia. They…
In recent years, the rapid development of high-precision map technology combined with artificial intelligence has ushered in a new development opportunity in the field of intelligent vehicles. High-precision map technology is an important…
Crowdsourcing has been successfully applied in many domains including astronomy, cryptography and biology. In order to test its potential for useful application in a Smart Grid context, this paper investigates the extent to which a crowd…
Crowdsourcing wireless energy services is a novel convenient alternative to charge IoT devices. We demonstrate peer-to-peer wireless energy services sharing between smartphones over a distance. Our demo leverages (1) a service-based…
Nowadays, massive urban human mobility data are being generated from mobile phones, car navigation systems, and traffic sensors. Predicting the density and flow of the crowd or traffic at a citywide level becomes possible by using the big…
Adaptive bitrate (ABR) streaming enables video users to adapt the playing bitrate to the real-time network conditions to achieve the desirable quality of experience (QoE). In this work, we propose a novel crowdsourced streaming framework…
Crowdsourcing provides a flexible approach for leveraging human intelligence to solve large-scale problems, gaining widespread acceptance in domains like intelligent information processing, social decision-making, and crowd ideation.…
In this article, we propose a simulated crowd counting dataset CrowdX, which has a large scale, accurate labeling, parameterized realization, and high fidelity. The experimental results of using this dataset as data enhancement show that…
In this paper, we propose to design an automated service discovery process to allow mobile crowdsourcing task requesters select a small set of devices out of a large-scale Internet-of-things (IoT) network to execute their tasks. To this…
Mobile crowdsensing allows data collection at a scale and pace that was once impossible. One of the biggest challenges in mobile crowdsensing is that participants may exhibit malicious or unreliable behavior. Therefore, it becomes…