Apache: Big Data 2016

In this session, the presenter will share the experience on how to use the hadoop based big data technology with huge cellular signal data, RFID, and GPS data to analyze and predict people and vehicles trails, to support the precision urban planning. This whole architecture includes,
11) Data ingestion kafka+streaming to collect and preprocessing the real-time generated cellular signal data, RFID and GPS data(200G+ per day)
2) Algorithm model with spatial data computation using Spark core and MLib to analyze and predict people and vehicles trails on the data collected
3) SQL on Hadoop technology to provide the interactive query and analysis for frontend applications
4) Spatial data visualization with GIS and grid technology to render the heatmap, people residency distribution, real traffic road status, OD map etc