Brief description: 

QROWDSmith is a standalone crowdsourcing platform designed to engage with crowdsourcing volunteers or workers, or citizens to run crowdsourcing activities aimed in data creation and curation for applications developed for mobility purposes. QROWDSmith makes use of gamification techniques such as leaderboards, badges, and scores to enhance contributors engagement to engage with users leveraging on hedonic aspects.

A typical example of a task that can be offered by QROWDsmith is the image tagging. In such a task, the goal of two contributors play together consist of writing tags that better describe an image, and their reward will be computed based on the similarities between the tags they provided. Such labelled images can then be used to train a machine learning algorithm for example to automatic classify new sets of images.

Qrowdsmith's user can be crowdworkers that receive money for the complement of tasks, or volunteer contributors, or citizens then local knowledge is required.

Main Features: 
  • Support for real time competitive and collaborative tasks.
  • Gamified components such as leaderboards, badges, and scores to enhance contributors engagement.
  • Support for plugins: QROWDSmith comes with a few default plugins, but it can be extended with additional ones.
  • Customization: Some components or the platform are customisable, to offer personalized experience.
  • The platform is standalone, so it can be installed in independent instances.
Areas of Application: 

Smart Cities, Urban mobility, Transport logistics

Market Trends and Opportunities: 

QROWDSmith is a solution for smart cities that  aim to include human computation.

Customer Benefits: 

Enable the gamification of crowdsourcing tasks; therefore increase engagements if contributors are citizens or optimising budget if contributors are crowdworkers.

Technological novelty: 
  • Real time crowdsourcing
  • Leveraging on gamified incentives to improve workers motivation
Workflow: 
Published
Platform / Framework

Owner

University of Southampton
Southampton
United Kingdom of Great Britain and Northern Ireland
Type: 
Project
Project: 
QROWD
BDV Reference categories: 
Data Analytics
Data Visualisation and Interaction
Markets: 
Urban Mobility
Readiness Level: 
Licensing: 
Apache Public License (https://www.apache.org/licenses/LICENSE-2.0)
Keywords: 
crowdsourcing platform
crowdsourcing activities
crowdworkers
human computation