Data is collecting from crowded users (approx. 10.000 to 1 million users.).
Data processing and visualization is done in real-time.
Such predicts and estimations can be done by ML algorithms.
Estimations and data by itself can be visualized with some charts in real.
Thanks to the recent advances in IoT technologies, there is continuous flow of data from
various devices and sensors across homes. This data is currently collected in the cloud, and
by analyzing this data, a variety of new services will be created.
The aim is to design and implement a tool to process and analyze in real-time (on-line) data
streams coming from devices and appliances across smart homes. In real life, several
thousands of IoT enabled home appliances are connected to a centralized computing facility
and these devices send streams of data at different speeds and intervals. The incoming data
is processed on-line not in batch, though it could be stored for further use. For Arçelik which
is one of the leading home appliance manufacturing companies in Europe and in the world,
it is essential to apply data analytics for the stream data originating from home appliances for
several tasks such as finding anomalies, detecting concept drifts and for creating new
services.