Street lights in Singapore is valuable but expensive assets for the city. However, according to a recent study published by Science Advances (Jun 2016) – Singapore was named the country with the worst level of light pollution in the world with a pollution level of 100 per cent. The use of artificial light here far exceeds the level of light pollution tolerable per capita.

Today’s street lights are a lot to manage, and tend to function inefficiently by wasting energy when they are on. Hence, Remote Control Monitoring System (RCMS) was designed with energy savings as the goal. Although RCMS presents opportunities for saving energy cost, street lighting can be further optimize by taking into account, the trend of people who are outdoor at night. With the advantage of geospatial analytics, we would like to introduce: Street LightTime + Weather +Flow rate of Pedestrians

Picture1

 

Geospatial Analysis Techniques Used  :

  1. Points to Line
  2. Buffering
  3. Overlaying
  4. Clipping

Geospatial Analysis Used:

  1. Heat Map
  2. Cluster and Outlier Analysis
  3. Hot Spot Analysis
  4. Directional Distribution Analysis (for movement data)

Summary of Findings:

Recommendation

  • Light up in the presence of a person or car, and remain dim the rest of the time.
  • Autonomous dimming when no movement detected.
  • Predict the movement pattern and light up ahead.
  • Consider the distance between each lamppost through geo analysis

Goal

  • Improve the quality of life by reducing artificial light
  • Reduce light pollution level
  • Significant energy saving

Welcome to have a full view of the ArcGIS Map Journal from here.

The presentation slide is also available from this link .

Presented to you by: Team GEOSPIES

 

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