IoT Analytics


IoT big data storage

IoT large scale event processing

On-demand analytics with R

Integration with Azure ML

Integration with Amazon ML

Data is normally collected in an IoT system in order to perform some analyses of the data. Typical needs are to find patterns in the historical data collected or unknown relationships, detecting anomalies in data and forecast values.

The main problem for developers is that IoT Analytics requires deep knowledge of sophisticated algorithms for statistical analysis or machine learning techniques.

To simplify IoT Analytics CNet are developing a number of tools to support developers in integrating analytical functions as part of their solutions. These tools are available as extensions to Linksmart .net Open Source.

The main features of Analytics Extensions are

On-demand analytics using the R programming language for computational statistics and data science

Integration with Microsoft Azure Machine learning services

Integration with Amazon Machine learning services

Visit the IoTWorldServices to learn more and download.

Application areas


Lifestyle management

Industrial automation

Home automation


Smart Cities

Environmental monitoring


Energy management

Vivian EsquiviasIoT Analytics