Energy Data Visualization
This paper presents an integrated energy monitoring and visualization system aimed at supporting the development of Smart Green Cities. It outlines the design of a spatial information model that manages massive data using web-based platforms. The system provides real-time monitoring and visualization of energy usage at varying scales, utilizing location-based sensor data. With interfaces to Google Earth and Google Maps, this project introduces innovative middleware technologies and strategies that enhance user interaction and facilitate effective energy management.
Energy Data Visualization
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Presentation Transcript
Energy Data Visualization Bill-Jinsong Wang CS Kent Sate Fall 2013
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
Key Words • Energy monitoring • Data visualization • Smart Green City • Spatial information model • EnerISS (Energy Integrated Urban Planning & Managing Support System) • Social sensing
Background • IoT, Web.o.t • Smart City(Sensor Networking/Senor Data) • Smart Grid • SCADA (supervisory control and data acquisition)/ICS
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
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
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
Urban data structure model • The existing GIS system and diverse Building Information Model (BIM) technologies can represent the 3D geological environment • Pre-Made
Data optimization for 3D city representation • Modeler • Parametric Building • Google Earth Plugin • KML
Visualization strategy • easy-to-use interface and a suitable representation method • Color, Height, 3d Geometry, Alpha Value
Implementation – LODs • 4 LOD: Grid < Block < Building < Floor
Implementation – Middleware • Due to Web Base Requirement • Client Vis Comp & DB Comp Sensor & CIS
Implementation – Data Structures • Advantages: • 1. Strong Accurate • 2. More Kinds of Data • To enhance System performance and Information Visualization Method
Implementation – Addition • Large Data Treatment • Diversity Representations • Socials
ANY QUESTION? Then…
