Title :
Big Data Sensing and Service: A Tutorial
Author :
Gao, Jerry ; Lihui Lei ; Shui Yu
Author_Institution :
Comput. Eng. Dept., San Jose State Univ., San Jose, CA, USA
fDate :
March 30 2015-April 2 2015
Abstract :
As the advance of the Internet of Things (IoT), more M2M sensors and devices are connected to the Internet. These sensors and devices generate sensor-based big data and bring new business opportunities and demands for creating and developing sensor-oriented big data infrastructures, platforms and analytics service applications. Big data sensing is becoming a new concept and next technology trend based on a connected sensor world because of IoT. It brings a strong impact on many sensor-oriented applications, including smart city, disaster control and monitor, healthcare services, and environment protection and climate change study. This paper is written as a tutorial paper by providing the informative concepts and taxonomy on big data sensing and services. The paper not only discusses the motivation, research scope, and features of big data sensing and services, but also exams the required services in big data sensing based on the state-of-the-art research work. Moreover, the paper discusses big data sensing challenges, issues, and needs.
Keywords :
Big Data; Internet; Internet of Things; Big Data service; Big data sensing; Internet of Things; IoT; M2M sensor; sensor-oriented application; Big data; Cloud computing; Data analysis; Data models; Monitoring; Sensors; Wireless sensor networks; Big Data Sensing; Internet of Things; Sensor Big Data; Sensor Cloud; Sensor-Based Big Data Analytics;
Conference_Titel :
Big Data Computing Service and Applications (BigDataService), 2015 IEEE First International Conference on
Conference_Location :
Redwood City, CA
DOI :
10.1109/BigDataService.2015.45