Crowdsourcing

About: Crowdsourcing is a research topic. Over the lifetime, 12889 publications have been published within this topic receiving 230638 citations.

A crowdsourcing platform for the construction of accessibility maps

Abstract: We present in this article a crowdsourcing platform that enables the collaborative creation of accessibility maps. The platform provides means for integration of different kind of data, collected automatically or with user intervention, to augment standard maps with accessibility information. The article shows the architecture of the platform, dedicating special attention to the smartphone applications we developed for data collection. The article also describes a preliminar experiment conducted on field, showing how the analysis of data produced by our solution can bring novel insights in accessibility challenges that can be found in cities.

Crowdsourcing as a model for problem solving: Leveraging the collective intelligence of online communities for public good

Abstract: As an application of deliberative democratic theory in practice, traditional public participation programs in urban planning seek to cultivate citizen input and produce public decisions agreeable to all stakeholders. However, the deliberative democratic ideals of these traditional public participation programs, consisting of town hall meetings, hearings, workshops, and design charrettes, are often stymied by interpersonal dynamics, special interest groups, and an absence of key stakeholder demographics due to logistical issues of meetings or lack of interest and awareness. This dissertation project proposes crowdsourcing as an online public participation alternative that may ameliorate some of the hindrances of traditional public participation methods. Crowdsourcing is an online, distributed problem solving and production model largely in use for business. It leverages the collective intelligence of online communities by soliciting ideas and solutions for an organization from these communities through the form of an open call. The mechanism of one type of crowdsourcing, the peer-vetted creative production approach, aligns with the goals of public participation programs. In light of this, Next Stop Design was launched in 2009 in an attempt to test crowdsourcing in a public participation context for transit planning. Next Stop Design was an online competition where users submitted bus stop shelter designs and voted on the designs of peers to determine a best design. This study examines the effectiveness of the Next Stop Design project as an online deliberative democratic process, as perceived by Next Stop Design participants,

A Probabilistic Radio Map Construction Scheme for Crowdsourcing-Based Fingerprinting Localization

Abstract: Fingerprinting localization using received signal strength (RSS) has been considered as a promising solution for indoor localization systems, due to its ease of use in deployed wireless networks. A major bottleneck is the difficult trade-off between localization accuracy and site survey costs. Crowdsourcing-based fingerprint collection is cost efficient because of user participation, but its accuracy is questioned due to the noisy sample locations. In this paper, we present a probabilistic radio map construction scheme with crowdsourcing collection, considering both accuracy and survey costs. In particular: 1) based on further studies of RSS properties, we introduce a concept of unfixed data collection—in which sample locations are estimated by an additional localization mechanism—and verify its effectiveness, although sample locations are noisy; 2) we present a modified parametric fitting method to better describe location signatures by transforming RSS into signal envelope; and 3) we propose a clustering-based space partitioning algorithm to improve the fitting effect by reducing the number of multimodal distributions. Extensive simulations and experiments show the proposed method can construct an accurate radio map at a low cost, and achieve a localization accuracy of about 2.5 m, 20% improvement compared to using the classical radio map in our experimental scenario.

CrowdOracles: Can the Crowd Solve the Oracle Problem?

Abstract: Despite the recent advances in test generation, fully automatic software testing remains a dream: Ultimately, any generated test input depends on a test oracle that determines correctness, and, except for generic properties such as “the program shall not crash”, such oracles require human input in one form or another. CrowdSourcing is a recently popular technique to automate computations that cannot be performed by machines, but only by humans. A problem is split into small chunks, that are then solved by a crowd of users on the Internet. In this paper we investigate whether it is possible to exploit CrowdSourcing to solve the oracle problem: We produce tasks asking users to evaluate CrowdOracles - assertions that reflect the current behavior of the program. If the crowd determines that an assertion does not match the behavior described in the code documentation, then a bug has been found. Our experiments demonstrate that CrowdOracles are a viable solution to automate the oracle problem, yet taming the crowd to get useful results is a difficult task.