Research of Beacon Sensors and Open Data used in Smart Community

• Main Authors: Web, Ping-Sang, 溫秉善
• Other Authors: Wu, Jung-Gen
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/3t9m3r

碩士 === 國立臺灣師範大學 === 資訊工程學系 === 105 === In recent years, the development of technologies has enforced the world's advanced cities to develop intelligent community-related applications for their citizens. Governments also actively organize their public information and publish them on the Internet to encourage civil and business use these open materials to create new intelligent services. In addition, citizens’ smart phones almost all have access to Internet and many sensor functions, which can be used to support the intelligent community applications in their daily life. This study includes the application of beacon sensors and government open information to develop intelligent community services. The system consists of three subsystems to provide the application of intelligent community: public facilities subsystem, information push subsystem, and residential evaluation subsystem. First, the public facilities subsystem uses the GPS global positioning technology combined with government information on the electronic map to show the Taipei City’s various educational institutions, universities, libraries, and sports centers. This subsystem allows users to immediately locate and know what services around. Second, information push subsystem using beacon technology to push information when pedestrians walk through educational institutions or community businesses. This subsystem allows advertisings and promotion events to be pushed to the user's mobile phone, so that the messy signs or advertising flyers can be reduced. This subsystem also provides a community store to calculate the man-flow and customer habits statistics for marketing promotion. Third, the residential assessment subsystem uses real estate open data from the Ministry of Interior combined with Taipei City’s educational institutions open data. This subsystem uses a residential convenience score which is derived by user’s weight preferences, so that users have more convenient considerations choosing their homes. The three subsystems can be integrated to create more services such as event promotion and map guidelines, the statistics of the man-flow in the vicinity of the shopping district, and the study of the advertising effectiveness of the man-flow. This study allows users to use smartphones to connect with the smart community to create a more convenient community environment.