Analytics for IoT

Predicting system failure, extra power consumption and others

Hours total

1640

Technical Stack

Python, VHDL, Embedded C, AWS, SPI

Services Involved

Dedicated Team

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OVERVIEW

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.

CHALLENGE

To predict the goods consumption for the office supply chain optimization.

Solution

To develop a predicting model, the sensor data was analyzed as time series using the autoregression approach combined with neural networks.

Results

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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