On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms
Data Mining and Knowledge Discovery
An online support vector machine for abnormal events detection
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Online outlier detection in sensor data using non-parametric models
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Distributed Event Detection in Sensor Networks
ICSNC '06 Proceedings of the International Conference on Systems and Networks Communication
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Air Quality Monitoring with SensorMap
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
The Rise of People-Centric Sensing
IEEE Internet Computing
Proceedings of the 7th international conference on Mobile systems, applications, and services
Evaluation of streaming aggregation on parallel hardware architectures
Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems
Performance Issues in Cloud Computing for Cyber-physical Applications
CLOUD '11 Proceedings of the 2011 IEEE 4th International Conference on Cloud Computing
Decentralized detection in sensor networks
IEEE Transactions on Signal Processing
Towards a discipline of geospatial distributed event based systems
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Dynamic QoS-aware event sampling for community-based participatory sensing systems
Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems
Information system monitoring and notifications using complex event processing
Proceedings of the Fifth Balkan Conference in Informatics
Energy efficient GPS sensing with cloud offloading
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
Efficient event detection by exploiting crowds
Proceedings of the 7th ACM international conference on Distributed event-based systems
Hi-index | 0.00 |
The paper presents theory, algorithms, measurements of experiments, and simulations for detecting rare geospatial events by analyzing streams of data from large numbers of heterogeneous sensors. The class of applications are rare events - such as events that occur at most once a month - and that have very high costs for tardy detection and for false positives. The theory is applied to an application that warns about the onset of shaking from earthquakes based on real-time data gathered from different types of sensors with varying sensitivities located at different points in a region. We present algorithms for detecting events in Cloud computing servers by exploiting the scalability of Cloud computers while working within the limits of state synchronization across different servers in the Cloud. Ordinary citizens manage sensors in the form of mobile phones and tablets as well as special-purpose stationary sensors; thus the geospatial distribution of sensors depends on population densities. The distribution of the locations of events may, however, be different from population distributions. We analyze the impact of population distributions (and hence sensor distributions as well) on the efficacy of event detection. Data from sensor measurements and from simulations of earthquakes validate the theory.