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The importance of incorporating human grouping into mobile crowdsensing, a process described by Lane [122] as community-aware sensing, has been emphasised in several studies, including [123, 124].
The idea behind human grouping, for purpose of designing effective incentive mechanisms, is that participants in each group will share similar social and economic goals, different from other groups and hence would be motivated differently.
However, several research challenges still need to be adequately addressed in order to fully maximise the potential of using human grouping to improve the outcomes of decision making related to appropriateness of incentive mechanism.
For a start, the concept of human grouping which has emerged as a way to simplify the process of understanding and utilising socioeconomic factors in selecting an appropriate incentive is yet to be fully explored in the context of mobile crowdsensing [1].
In my experience, the only human grouping that makes a bigger deal are the inhabitants of Melbourne, Australia.
Similar(55)
All human groups are equally old, being descended from the same ancestral population.
"In early human groups, women typically collected plants and turned them into food while men hunted.
Human groups that depended on Stone Age technologies also depended on mutual caring.
But a key component of the theory is that early human groups were closely related.
As human groups got bigger, more social tolerance is what they had to have.
And the existing genetic data testify that known DNA variations do not respect the boundaries of human groups.
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