IoT : Crowd-Sensing

IoT : Crowd-Sensing

One very interesting aspect to the development of IoT when it comes to machine learning is the emergence of crowd-sensing. Crowd-sensing exists under two different forms: voluntary, when users voluntarily contribute information, and opportunistic, when data is collected automatically without explicit user intervention. This is one way that IoT data can contribute not only to the development or the improvement of IoT applications, but can also be used as input for other, non-IoT, applications.

IoT actually allows collection of very unique datasets in a way that has never been achieved before. Because the data generated by each device is usually at a human-scale, it becomes feasible for a user to label or validate it. It also becomes possible to gather data closest to where the users are: this is what Google does when they ask users to take a picture of a restaurant they are currently dining at, or to answer a few questions regarding the amenities. This is the first time that organizations can collect human-generated data at Big Data scale.