Optimizing pervasive sensor data acquisition utilizing missing values substitution

Acquisition of pervasive sensor data can be often unsuccessful due to power outage at nodes, time synchronization issues, interference, network transmission failures or sensor hardware issues. Such failures can lead to inadequate data delivery to the monitoring applications resulting in erroneous conclusions. This paper presents a missing values substitution framework that addresses the aforementioned issue. The presented framework has been evaluated within a pervasive sensor monitoring environment that collects and transmits patient health related data and results are presented. Categories and Subject Descriptors H.4.3 [Communications Applications], J3.3 [Medical information systems] General Terms Algorithms, Measurement, Performance, Reliability, Experimentation. Keywords Pervasive Sensors, Healthcare Data Transmission, Missing Values Substitution.

• Type: Conference
• Year: 2010
• Where: PETRA
• Authors: M. Michalopoulos, Christos Anagnostopoulos, Charalampos Doukas, Ilias Maglogiannis, Stathes Hadjiefthymiades
• Keywords: Emerging Technology, Pervasive Sensor Data, Pervasive Sensors, PETRA 2010, Values Substitution