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Energy Data Visualization Bill-Jinsong Wang CS Kent Sate Fall 2013.

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Presentation on theme: "Energy Data Visualization Bill-Jinsong Wang CS Kent Sate Fall 2013."— Presentation transcript:

1 Energy Data Visualization Bill-Jinsong Wang CS Kent Sate Fall 2013

2 Paper Information  Title: Integrated energy monitoring and visualization system for Smart Green City development - Designing a spatial information integrated energy monitoring model in the context of massive data management on a web based platform  Authors: Sung Ah Kim, Dongyoun Shin, Yoon Choe Thomas Seibert, Steffen P. Walz  Date: 2011

3 Key Words  Energy monitoring  Data visualization  Smart Green City  Spatial information model  EnerISS (Energy Integrated Urban Planning & Managing Support System)  Social sensing

4 Background  IoT, Web.o.t  Smart City(Sensor Networking/Senor Data)  Smart Grid  SCADA (supervisory control and data acquisition)/ICS

5 Abstraction  U-Eco City is a research and development project initiated by the Korean government.  Objectives: monitoring and visualization of aggregated and real time states of various energy usages represented by location-based sensor data accrued from city to building scale.  Middleware: browser-based client  interfaces with the Google Earth and Google Maps plug- ins

6 EnerISS Architecture  Modeler: 3D Modeling, Transfer to Solver (by E-GIS)  Viewer-Solver: Energy Demand (by E-GIS & Spatial)  Viewer-Evaluator: Analyzes Strategies (by SEE)  Viewer-EMS: does interactions (Inside Viewer or SCADA)  5 DBs for E-GIS, Spatial, SEE, SCADA, Sensors

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8 Challenges & Characteristics  Real-World Challenge (Sensor Signal, Large Scale Data)  Functionality – Game Like (interface)  Web based platform  Intuitive statistical data visualization  Real-time based sensor data collection and data aggregation  Dynamic data loading and visualization  Extensible city information  Energy Saving  CO2

9 Urban data structure model  The existing GIS system and diverse Building Information Model (BIM) technologies can represent the 3D geological environment  Pre-Made

10 Data optimization for 3D city representation  Modeler  Parametric Building  Google Earth Plugin  KML

11 Visualization strategy  easy-to-use interface and a suitable representation method  Color, Height, 3d Geometry, Alpha Value

12 Implementation – LODs  4 LOD: Grid < Block < Building < Floor

13 Implementation – Strategy

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15 Implementation – Middleware  Due to Web Base Requirement  Client  Vis Comp & DB Comp  Sensor & CIS

16 Implementation – Data Structures  Advantages:  1. Strong Accurate  2. More Kinds of Data  To enhance System performance and Information Visualization Method

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18 Implementation – Testing

19 Implementation – Addition  Large Data Treatment  Diversity Representations  Socials

20 Conclusion & Future

21 ANY QUESTION? Then…

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