Enhancing data quality in data warehouse environments
Communications of the ACM
ACM Computing Surveys (CSUR)
Information quality benchmarks: product and service performance
Communications of the ACM - Supporting community and building social capital
Modern Information Retrieval
Performance Evaluation of Object Detection Algorithms
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Performance Evaluation Metrics for Motion Detection and Tracking
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Confidence-driven early object elimination in quality-aware sensor workflows
DMSN '05 Proceedings of the 2nd international workshop on Data management for sensor networks
A Technique for Adaptive Scheduling of Soft Real-Time Tasks
Real-Time Systems
Performance evaluation in visual surveillance using the F-measure
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
Beyond accuracy: what data quality means to data consumers
Journal of Management Information Systems
Detecting social interactions of the elderly in a nursing home environment
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Performance evaluation of a real time video surveillance system
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
Timeliness-Accuracy Balanced Collection of Dynamic Context Data
IEEE Transactions on Parallel and Distributed Systems
On Sensor Sampling and Quality of Information: A Starting Point
PERCOMW '07 Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications Workshops
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
Data quality and query cost in pervasive sensing systems
Pervasive and Mobile Computing
Representing Data Quality for Streaming and Static Data
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Modeling Quality of Information in Multi-sensor Surveillance Systems
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Performance evaluation of object detection algorithms for video surveillance
IEEE Transactions on Multimedia
Confidence Evolution in Multimedia Systems
IEEE Transactions on Multimedia
Quality-Based Fusion of Multiple Video Sensors for Video Surveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Image change detection algorithms: a systematic survey
IEEE Transactions on Image Processing
Effective multimedia surveillance using a human-centric approach
Multimedia Tools and Applications
Modeling the information completeness of object tracking systems
The Journal of Strategic Information Systems
Adaptive interaction support in ambient-aware environments based on quality of context information
Multimedia Tools and Applications
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Current sensor-based monitoring systems use multiple sensors in order to identify high-level information based on the events that take place in the monitored environment. This information is obtained through low-level processing of sensory media streams, which are usually noisy and imprecise, leading to many undesired consequences such as false alarms, service interruptions, and often violation of privacy. Therefore, we need a mechanism to compute the quality of sensor-driven information that would help a user or a system in making an informed decision and improve the automated monitoring process. In this article, we propose a model to characterize such quality of information in a multisensor multimedia monitoring system in terms of certainty, accuracy/confidence and timeliness. Our model adopts a multimodal fusion approach to obtain the target information and dynamically compute these attributes based on the observations of the participating sensors. We consider the environment context, the agreement/disagreement among the sensors, and their prior confidence in the fusion process in determining the information of interest. The proposed method is demonstrated by developing and deploying a real-time monitoring system in a simulated smart environment. The effectiveness and suitability of the method has been demonstrated by dynamically assessing the value of the three quality attributes with respect to the detection and identification of human presence in the environment.