Communications of the ACM
Fighting Crime Through Crowdsourcing
Researchers at the University of Miami are working on a computer model that takes advantage of crowdsourcing to combine and optimize human efforts and machine-computing elements.
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University of Miami (UM) researchers are developing a computing model that uses crowdsourcing to combine and optimize human efforts and machine-computing elements.
The model uses social networks to perform complex tasks of face recognition and could be a formal part of the criminal investigation process, according to UM vice provost Brian Blake. "The breadth of the Internet and popularity of smartphones have facilitated the onset of online crowdsourcing platforms," Blake says. "Our project attempts to leverage the power of the crowd to solve complex problems, on demand."
He notes by combining the efforts of both machine-computing and human-computing elements in performing the same task, there was an overall average certainty of 69.13 percent.
Blake says the system is unique because of its elasticity, enabling it to adapt to changes in the workload of a task. He notes the model also allows the machine- and human-computing resources to change, when and where needed and without disrupting the operations.
"Elastically, we would like to decide who is best for a specific task, or what concentration of people or machines could be mixed for a specific task," Blake says.
From University of Miami
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