Analytics for IoT
Python, VHDL, Embedded C, AWS, SPI
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IoT devices generate huge amount of data every day. It is streamed to a cloud and stored in data warehouse, where it can be easily accessed and manipulated using big data tools. This, in turn, creates perfect conditions to use data science tools for detecting and predicting specific events, including system failure, extra power consumption and others.
To predict the goods consumption for the office supply chain optimization.
To develop a predicting model, the sensor data was analyzed as time series using the autoregression approach combined with neural networks.
Simple, intuitive and accurate algorithm was developed to predict which goods should ordered and at what time. It was implemented as a separate service and integrated into the existing customer ERP system.
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