Towards Sensor Database Systems
MDM '01 Proceedings of the Second International Conference on Mobile Data Management
IEEE Internet Computing
SemSOS: Semantic sensor Observation Service
CTS '09 Proceedings of the 2009 International Symposium on Collaborative Technologies and Systems
Ontology-Based Integration of Sensor Web Services in Disaster Management
GeoS '09 Proceedings of the 3rd International Conference on GeoSpatial Semantics
Use of Data Warehouse to Manage Data from Wireless Sensors Networks That Monitor Pollinators
MDM '10 Proceedings of the 2010 Eleventh International Conference on Mobile Data Management
Sensor data integration for indoor human tracking
Robotics and Autonomous Systems
Expanding sensor networks to automate knowledge acquisition
BNCOD'11 Proceedings of the 28th British national conference on Advances in databases
Optimizing queries for web generated sensor data
ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115
| Hi-index | 0.00 |
Recent advances in sensor technology have led to a rapid growth in the availability of accurate, portable and low-cost sensors. In the Sport and Health Science domains, this has been used to deploy multiple sensors in a variety of situations in order to monitor participant and environmental factors of an activity or sport. As these sensors often output their data in a raw, proprietary or unstructured format, it is difficult to identify periods of interest, such as events or actions of interest to the Sport and Exercise Physiologists. In our research, we deploy multiple sensors on horses and jockeys while they engage in horse-racing training exercises. The Exercise Physiologists aim to identify events which contribute most to energy expenditure, and classify both the horse and jockey movement using basic accelerometer sensors. We propose a metadata driven approach to enriching the raw sensor data using a series of Profiles. This data then forms the basis of user defined algorithms to detect events using an Event-Condition-Action approach. We provide an Event Definition interface which is used to construct algorithms based on sensor measurements both before and after integration. The result enables the end user to express high level queries to meet their information needs.