Eylem Seç
Data Mining, Inference, and Predictive Analytics for the Built Environment with Images, Text, and WiFi Data
Başlık:
Data Mining, Inference, and Predictive Analytics for the Built Environment with Images, Text, and WiFi Data
Yazar:
Villalon, Rachelle B., author.
Yazar Ek Girişi:
Genel Not:
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: A.
Advisors: Takehiko Nagakura.
Özet:
What can campus WiFi data tell us about life at MIT? What can thousands of images tell us about the way people see and occupy buildings in real-time? What can we learn about the buildings that millions of people snap pictures of and text about over time? Crowdsourcing has triggered a dramatic shift in the traditional forms of producing content. The increasing number of people contributing to the Internet has created big data that has the potential to 1) enhance the traditional forms of spatial information that the design and engineering fields are typically accustomed to; 2) yield further insights about a place or building from discovering relationships between the datasets. In this research, I explore how the Architecture, Engineering, and Construction (AEC) industry can exploit crowdsourced and non-traditional datasets. I describe its possible roles for the following constituents: historian, designer/city administrator, and facilities manager - roles that engage with a building's information in the past, present, and future with different goals. As part of this research, I have developed a complete software pipeline for data mining, analyzing, and visualizing large volumes of crowdsourced unstructured content about MIT and other locations from images, campus WiFi access points, and text in batch/real-time using computer vision, machine learning, and statistical modeling techniques. The software pipeline is used for exploring meaningful statistical patterns from the processed data. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs mit.edu).
Notlar:
School code: 0753
Tüzel Kişi Ek Girişi:
Mevcut:*
Yer Numarası | Demirbaş Numarası | Shelf Location | Lokasyon / Statüsü / İade Tarihi |
---|---|---|---|
XX(687499.1) | 687499-1001 | Proquest E-Tez Koleksiyonu | Arıyor... |
On Order
Liste seç
Bunu varsayılan liste yap.
Öğeler başarıyla eklendi
Öğeler eklenirken hata oldu. Lütfen tekrar deneyiniz.
:
Select An Item
Data usage warning: You will receive one text message for each title you selected.
Standard text messaging rates apply.