Title: ISS Students’ Lifestyle & Rental Recommendation
Team Member: Huang Wei, Li Huangxing, Li Quiqi, Lim Chong Wui, Liu Huan
- ISS students behaviour analysis
- Rental recommendation and comparison
2.0 Data Preparation
- combine Moves & Openpath data
- remove duplicated spatial-temporal data
- remove outliers
- group data into time periods of the day
- identify and extract student home geolocations
- find geolocations of places of interest using Google Map APIs
2.1 Public domain data source
3.0 ISS Students Behaviour Analysis
This video shows the movement of ISS students during 3 weeks and can be viewed from the following link: https://youtu.be/ZF0_LR_Di0Q
- Blue points represents the movement of each person
- Red triangle shows the home of ISS students.
- Green square indicates as ISS
As shown in the video, the moving points are too rambling and disorganized to easily identify the behavior of each student. That’s why we involve static maps like supermarket that student would frequently go, together with ISS students’ movement data to conduct behavior analysis.
3.1 How we conduct behavior analysis?
3.2 A typical Day of ISS Students
4.0 Rental Recommendation
4.1 Why Use Hexagon?4.2 How we rank these hexagons?
4.3 Density maps for 5 factors and overall recommendation:
4.4 Top 10 recommendations:
suitable for students who prefer short travel time to school
– short distance to school
– do not have much sports facilities and amenities
suitable for students who want to balance travelling time and living convenience
– moderate distance to school
– rental is comparable
– more facilities compared to Red areas
suitable for students who have budget concerns
– rental price is less expensive
– plenty of facilities and public transports
4.5 Student Home vs Recommendation
The No.1 hexagon (the nearest one to ISS) has highest density of students’ homes, followed by No.3 hexagon and No.7 hexagon.
Many students’ choices do not match the other top 10 hexagons. It may due to students’ lack of information of their amenities, convenient transportation, and good infrastructure.
Student behavior analysis:
We studied only a typical day of ISS students, and assumed 4 kinds of places students normally go (amenities, parks, sports and healthcare).
Most students go to healthcare places or do sports between 3pm and 6pm, and go to amenities and parks between 6pm and 10pm
Rental recommendation model:
We assumed most ISS students live in either condo or HDB, and data collected are all from foreign students who are renting houses.
Our top 10 recommendations provide an overall evaluation, and add value to students who are going to make new choices
You can access our online map: http://arcg.is/2poQoTS