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大同大學資訊經營學系
演講公告
演講題目：Discovering Big Value from Sensing Data
演講者：交通大學資訊工程系 彭文志 教授
『雲端、物聯網和大數據』系列演講
演講分類：
邀請老師: 廖文華
日期：2016/03/28
時間：15:10~17:00
地點：北設工 11F 1115 教室
演講者簡介：
Wen-Chih Peng was born in Hsinchu, Taiwan, R.O.C in 1973. He received the BS and MS degrees
from the National Chiao Tung University, Taiwan, in 1995 and 1997, respectively, and the Ph.D.
degree in Electrical Engineering from the National Taiwan University, Taiwan, R.O.C in 2001.
Currently, he is a professor at the department of Computer Science, National Chiao Tung
University, Taiwan. Dr. Peng published some papers in several prestigious conferences, such as
ACM International Conference on Knowledge Discovery and Data Mining (ACM KDD), IEEE
International Conference on Data Mining (ICDM) and ACM International Conference on
Information and Knowledge Management (ACM CIKM) and prestigious journals (e.g., IEEE
TKDE, IEEE TMC, IEEE TPDS). Dr. Peng has the best paper award in ACM Workshop on
location-based social network 2009 and the best student paper award in IEEE International
Conference on Mobile Data Management 2011. His research interests include mobile data
management, sensor data management and data mining. He is a member of IEEE.
演講摘要(或大綱)：
Recent advances in wireless and embedded technologies usher in a new era for our lives. It is
expected that an increasing number of small and inexpensive wireless devices (referred to as sensor
nodes) are deployed for monitoring various measurements. Many applications of wireless sensor
networks have been proposed such as field data collection, remote monitoring and control, smart
home, factory automation and security. In this talk, there are three types of sensing data mentioned
in this talk: Sensing data from sensor networks, sensing data from social media and sensing data
from smart devices. According to three types of sensor data, I will briefly present some frameworks
of mining user behaviors. These frameworks aim at discovering trajectory patterns, mobile apps.
usage patterns and appliance usage patterns.