Investigate IoT Time Series Applications

[antoinecarme]

Investigate IoT Time Series Applications

[antoinecarme]

Similar work
https://developer.ibm.com/recipes/tutorials/timeseries-data-analysis-of-iot-events-by-using-jupyter-notebook/

[antoinecarme]

And a Watson sample notebook : https://github.com/ibm-watson-iot/predictive-analytics-samples/blob/master/Notebook/TimeseriesDataAnalysis.ipynb

coming from

https://github.com/ibm-watson-iot/predictive-analytics-samples/

thanks to @ibm-watson-iot

[antoinecarme]

(by @cityzendata)

Warp 10 Platform
Introduction

Warp 10 is an Open Source Geo Time Series® Platform designed to handle data coming from sensors, monitoring systems and the Internet of Things.

Geo Time Series® extend the notion of Time Series by merging the sequence of sensor readings with the sequence of sensor locations. If your data have no location information, Warp 10 will handle them as regular Time Series.

https://github.com/cityzendata/warp10-platform

[antoinecarme]

Gorilla: A Fast, Scalable, In-Memory Time Series Database

http://www.vldb.org/pvldb/vol8/p1816-teller.pdf

[antoinecarme]

Time Series DBMS

http://db-engines.com/en/ranking
http://db-engines.com/en/article/Time+Series+DBMS

[antoinecarme]

http://renesd.blogspot.fr/2017/02/is-postgresql-good-enough.html
https://github.com/tgres/tgres

[antoinecarme]

https://code.facebook.com/posts/952820474848503/beringei-a-high-performance-time-series-storage-engine/

Beringei: A high-performance time series storage engine

[antoinecarme]

Prophet: forecasting at scale

https://research.fb.com/prophet-forecasting-at-scale/?

Today Facebook is open sourcing Prophet, a forecasting tool available in Python and R. Forecasting is a data science task that is central to many activities within an organization. For instance, large organizations like Facebook must engage in capacity planning to efficiently allocate scarce resources and goal setting in order to measure performance relative to a baseline. Producing high quality forecasts is not an easy problem for either machines or for most analysts. We have observed two main themes in the practice of creating a variety of business forecasts: