Time Series Data Generated by IoT By @Trendalyze | @ThingsExpo #IoT

We will be speaking at IoT conference ThingsExpo  in New York City. June 6-8.

Analytics for Motif Discovery and Deep Learning in Time Series Data Generated by IoT

IoT generates lots of temporal data. But how do you unlock its value? You need to discover patterns that are repeatable in vast quantities of data, understand their meaning, and implement scalable monitoring across multiple data streams in order to monetize the discoveries and insights. Motif discovery and deep learning platforms are emerging to visualize sensor data, to search for patterns and to build application that can monitor real time streams efficiently.

In his session at @ThingsExpo, Dave Watson, CTO and Co-Founder of Trendalyze, will discuss real world IoT projects from UK environmental monitoring using Mosquitto, Node-RED, Kafka, Spark, MLlib and R.

Speaker Bio
Dave Watson is CTO and Co-Founder of Trendalyze and works on developing the database search and analytics platform for various IoT projects. He holds number of UK and US patents and has led engineering in database middleware, OLAP and time series databases in the past.

Speaking Experience: Speaker at number industry events including NoSQL Now, MongoDB Europe, Gartner, IDC, TDWI, VLDB, DB/EXPO, Google, Bearingpoint, Fujitsu and IBM/Informix user groups. Holds first class honours degree in Computer Systems Engineering from University of Bristol. Holds patents in UK and USA.

By | 2016-12-28T00:21:14+00:00 April 12th, 2016|Time Series Analysis|Comments Off on Time Series Data Generated by IoT By @Trendalyze | @ThingsExpo #IoT