The generalized use of the Internet and social network platforms has changed the way human beings establish relations, collaborate and share resources. In this context, crowdsourcing (or crowd computing) is becoming a common solution to provide answers to complex problems by automatically coordinating the potential of machines and human beings working together. Several challenges still separate crowdsourcing from its generalized acceptance by industry. For instance, the quality delivered by the workers in the crowd is crucial and depends on different aspects such as their skills, experience, commitment, etc. Trusting the individuals in a social network and their capacity to carry out the different tasks assigned to them becomes essential in speeding up the adoption of this new technology in industrial environments. Capacity to deliver on time, cost or confidentiality are just some other possible obstacles to be removed. In this paper, we discuss some of these issues, provide solutions to improve the quality in systems based on the use of crowdsourcing and present a real industrial problem where we use the crowd to leverage the work capacity of geographically distributed human beings © Springer-Verlag Berlin Heidelberg 2013.
CITATION STYLE
Muntés-Mulero, V., Paladini, P., Manzoor, J., Gritti, A., Larriba-Pey, J. L., & Mijnhardt, F. (2013). Crowdsourcing for industrial problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7685 LNAI, pp. 6–18). https://doi.org/10.1007/978-3-642-36074-9_2
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