Multimedia information retrieval and environmental monitoring: Shared perspectives on data fusion
| Autor: | Alan F. Smeaton, Edel O'Connor, Fiona Regan |
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| Rok vydání: | 2014 |
| Předmět: |
Ecology
Data stream mining Computer science Applied Mathematics Ecological Modeling media_common.quotation_subject Multimedia information retrieval Sensor fusion computer.software_genre Data science Computer Science Applications Ranking (information retrieval) Computational Theory and Mathematics Modeling and Simulation Environmental monitoring Data mining Parallels Wireless sensor network computer Ecology Evolution Behavior and Systematics Reputation media_common |
| Zdroj: | Ecological Informatics. 23:118-125 |
| ISSN: | 1574-9541 |
| Popis: | Computer-based remote monitoring of our environment is increasingly based on combining data derived from in-situ-sensors with data derived from remote sources, such as satellite images or CCTV. In such deployments it is necessary to continuously monitor the accuracy of each of the sensor data streams so that we can account for sudden failures of sensors, or errors due to calibration drive or biofouling. In multimedia information retrieval (MMIR), we search through archives of multimedia artefacts like video programs, by implementing several independent retrieval systems or agents, and we combine the outputs of each retrieval agent in order to generate an overall ranking. In this paper we draw parallels between these seemingly very different applications and show how they share several similarities. In the case of environmental monitoring we also need some mechanism by which we can establish the trust and reputation of each contributing sensor, though this is something we do not need in MMIR. In this paper we present an outline of a trust and reputation framework we have developed and deployed for monitoring the performance of sensors in a heterogeneous sensor network. |
| Databáze: | OpenAIRE |
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