SenDe 2012 - The 1st Workshop on Sensor Networks & Data Engineering (SenDe2012)

Data becomes more and more critical in our daily life. Two types of online data bring big challenges to data engineering: (1) discrete records of human activities, such as banking, business transactions, consumption through credit cards; (2) continuous sensor data for monitoring the physical worlds (including human body). The latter is more challenge because of data uncertainties due to discrete sampling and sampling errors.

However, to discuss both types of data together will bring exciting new vision to understand about our society and business activities related to the physical worlds. From one hand, wireless sensor networks bring new information from physical world to the process of the traditional data engineering for discovering useful knowledge from virtual world (e.g., electronic records). From the other hand, data engineering in business intelligence has pioneered advance data mining/processing methods that can push the sensor data engineering to develop faster.

Thus, this workshop (SenDe2012) focuses on two main topics:
(1) Wireless sensor networks and sensor data mining/processing;
(2) Data science aspects of banking & financial risk management, social network that relate to business intelligence.

We welcome papers addressing challenges in the sensor networks due to the constraint resources of sensor nodes and the costs for large number of sensor nodes in an application network. Also, we welcome papers that will tackle new challenges in the sensor data engineering, such as to fuse heterogeneous sensor data, to ensure the reliability and security of sensor data, and to discover useful knowledge from uncertain sensor stream data. This workshop (SenDe 2012) would have special focus on sensor networks and data engineering for environment monitoring, health care and oil/gas pipeline surveillance and safety, and any other applications. Nevertheless, we welcome papers that are related to all aspects of business intelligence and data mining.

Published by Springer LNCS: Indexed by EI/ISTP
The main conference APWeb2012 URL: http://www.apweb2012.org