Visualizing anomalies in sensor networks

Coverage Quality in Visual Sensor Networks

Detecting Anomalies in Sensor Data using Neural Networks

There exists a need within the Department of Defense (DoD) to provide a highly responsive and costeffective anomaly detection capability for satellite health monitoring. The solution must address current Battle Management Command and Control (BMC2) deficiencies. A soft-computing solution is robust in that it could be engineered to detect anomalies without requiring pre-set thresholds and thus e...

An Efficient and Scalable Approach to Visualizing Sensor Networks

Sensor networks offer the potential to provide timely information in an untethered and unattended real-world domain. Dynamic (real-time) visualization of sensor network data is needed in order to fully harvest that potential, allowing the users to see the patterns and trends – both spatial and temporal – inherent in the sensor data. Such visualization is the goal of this paper. Our approach to ...

Visualizing Sensor Data

Visualizing sensor data is not a trivial task. This work tries to find a matching between sensor data and visualizations. Sensors became very popular over the last decade, they got smaller, more efficient and cheaper, that is why they spread in many fields of applications. Sensor taxonomy and the dependency of space and time will help to find visualizations for sensor data. Besides this there a...

Visualizing Sensor Data

As costs and size of microprozessors and sensors decrease, interest in using sensor networks for various applications of the most different kinds grows. According to this fact rises the need of exploring best ways of sensor deployement, data acquisition from a network as well as visualizing the sensed data. This paper deals with the last of this needs through the contemplation of sensors and th...