|
Groundhog Technologies is a privately held company founded in 2001 and is headquartered in Cambridge, Massachusetts, USA. As a spin-off of MIT Media Lab,〔MIT Media Lab#Spin-offs〕〔() MIT Media Lab Spin-Offs〕 it was a semi-finalist in MIT's $50k Entrepreneurship Competition in 2000 and was incorporated the following year.〔(15 of the Top Companies Launched— More than 80 companies, 1600 employees, $4 billion in value ), MIT Sloan Management〕〔(Groundhog's Day ), Boston Business Journal, Feb 2005〕 The company received the first round of financing from major Japanese corporations and their venture capital arms in November 2002: Marubeni, Yasuda Enterprise Development and Japan Asia Investment Co.〔(Investors and Funding History ) ChubbyBrain〕 It received second round of financing in 2004 and since then has become self-sustainable.〔(Groundhog's Day ), Boston Business Journal, Feb 2005〕 The company’s products are built on top of its Mobility Intelligence Platform, which analyzes the locations, Quality of Experience,〔() Bloomberg Businessweek, May 2014〕 context, and lifestyles of subscribers in mobile operator’s network.〔(Groundhog Technologies (MIT) selected by China Unicom )〕 The intelligence about geolocation is then applied to improve subscribers’ experience 〔(Groundhog Boasts 3G/4G OSS Deal ) LightReading〕 and enable applications such as geomarketing and geotargeting.〔() MIT Digital Shingle Project〕 ==Core Technologies== Groundhog Technologies launched its Mobility Intelligence platform based on Chaos Theory and multi-dimensional modeling. The application of Chaos Theory gave rise to the company’s mathematical models of subscribers' mobility and usage behavior, which can be used for different applications such as by mobile operators to optimize networks according to the user demands. According to Chaos Theory, some seemly random or chaotic signals may be converted to analyze in phase space which can reveal the patterns behind it. The cases of most interest arise when the chaotic behavior shows patterns around an attractor in the phase space. Based on the attractor in the phase space, data can be utilized from different space, time, and individuals for modeling and indoor geolocation. It is also found that the dimensional structure and characteristics of phase space can naturally neutralize the bias of positioning (based on techniques such as triangulation or trilateration) caused by reasons such as multipath. That is, although each input is biased in some way, the observation from different dimensions and angles are biased in different ways. Combining multi-dimensional input in the phase space, based on the Law of Large Numbers it can average out the bias with different samples through dimensions, time, and individuals. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Groundhog Technologies」の詳細全文を読む スポンサード リンク
|