Difference between revisions of "Project Groups"
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Revision as of 20:42, 15 November 2017
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Project Groups
Please change Your Team name to your project topic and change student name to your own name
Project Team | Project Title/Description | Project Artifacts | Project Member |
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Understanding traffic patterns using network graph visualisations The project aims to illustrate the power of visual analytics in highlight patterns exhibited by vehicles when traversing through various traffic corridors. By linking the information captured in RFID tags when vehicles move through checkpoints, an interactive application is designed. This will help to unravel insights such as frequently travelled corridors, preferred routes amongst vehicles, traffic density, etc. The application will be primarily developed using R, and specifically the versatile ggraph package, which helps to develop powerful network visualisations. ggraph has been chosen as it is a recent release (Feb 2017), that exhibits the power of R and the ggplot architecture in incorporating network visualisations. Though ggplot tools have existed to visualise network patterns previously, the use of this package helps in making neater visualisations that help the user understand better. The motivation for this project stems from the traffic accumulation key problem found in most cities. Though the dataset pertains to a set of vehicles travelling through a wildlife preserve, the ideology can be applied to planning of roads and associated establishments. Urban planning needs to cater to robust planning of vehicle corridors to minimise disruptions in flow, and improve productivity. The interactive application helps the user understand linkages between various points in a predefined vicinity. The timestamp information of vehicle passages present in the data helps to understand various parameters such as traffic density, preferred corridors for vehicles and their speeds. The application devised here is also aimed to support the traffic authorities to identify what other alternative corridors might exist for reaching from Point A to point B. In addition, network measures such as the betweenness, the connectivity and closeness of various nodes, are also provided. |
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Environmental Criminology: The Missing "W" in Whodunnit Environmental Criminology, an approach first developed in the 1980s, involves the study of geospatial and contextual elements in relation to crime. These elements could involve aspects such as victim movement, and spatial-temporal patterns in the occurrence of crimes. Through the exploration of a crime record dataset provided by the Los Angeles Poice Department (LAPD), this project aims to provide a layman's view of criminology through the lens of geospatial-themed and statistical visual analytics. <motivation> <features> |
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Ever wonder how far bitcoin value could go? Read on Bitcoin has recently garnered mixed reviews from two extreme ends. From China banning bitcoin to Chicago Mercantile Exchange supporting the futures trading of bitcoin. And there are plenty more remarks from big investment banks as well as regulators. The value of bitcoin has rose more than 700% since the start of January 2017. If for any reason why people are excited or agitated about bitcoin, it has to do with its volatile value.
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Use the air quality indicators to save us On Nov 4th, Beijing Environmental Protection Agency released the news, owing to the adverse weather conditions and early winter heating as well as other factors, it is expected that there will be a continuous 4-day regional heavily polluted air quality in Beijing-Tianjin-Hebei and surrounding areas on November 4th, in addition, the air quality in some cities may reach serious pollution level….
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Team | Members | |||||||||||||||||
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Group 1 | GE BIN | LIM LIANG DANNY | RYAN CHIA | |||||||||||||||
Group 2 | Rachel Tong | Nurul Asyikeen Binte Azhar | Matilda Tan Ying Xuan | |||||||||||||||
Group 3 | CHEN ZHENGJIAN | XIAO ZHENYU | ZHENG MIANYI | |||||||||||||||
Group 4 | Yau Hon Tak | Deng Yuetong | ||||||||||||||||
Group 5 | Wang Rui | Wu Yuqing | Xing Siyuan | |||||||||||||||
Group 6 | Wang Yizhou | Zhou Chen | Zhang Lidan | |||||||||||||||
Group 7 | Zhang Peng | Wang Shang | ||||||||||||||||
Group 8 | Fam Guo Teng | Wang Yuchen | Xu Yanru | |||||||||||||||
Group 10 | Ma Xiaoliu | Deng Chunling | AISHWARYA MOHAN | |||||||||||||||
Group 11 | FOO CELONG RAYMOND | GOH JUN JIE ANTHONY | KARAN JYOTI KHANNA | |||||||||||||||
Group 12 | HE ZIWEN | GONGQIANG | KYONG HWAN KIM |