Title :
A Multi-platform Sensor Coordinated Earth Observing Missions Scheduling Method for Hazard Monitoring
Author :
Li Jun ; Jing Ning ; Hu Weidong ; Chen Hao
Author_Institution :
Coll. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
The earth observing mission scheduling problem is an important real-world problem that impacts the opportunity of dealing with emergencies and the collection of hazard monitoring research data. The period of traditional data acquisition cycle for earth science research is often too long to receive some important observation data in time. Besides, with rapid developing of sensor web techniques, the envisioned future earth scientists and emergency workers would like to investigate the natural phenomenon by using large numbers of sensors based on different platforms, such as satellite, balloon, aircraft and ground-based. How to schedule these sensors that are frequency agile and capable of multi-scene observations for completing a hazard monitoring research mission is a difficult task. In this paper, we focus on solving two problems above. The active observation model based on hazard monitoring domain knowledge is proposed for reducing responsive time of abnormal phenomenon. And then information gain model is introduced for evaluating observation schedule. On this basis, multi-platform sensor optimization scheduling model is constructed. Simulation and analysis show that the proposed model can solve the problem effectively. Moreover, the normal requests are also taken into account during these events for maximizing the value of various sensors.
Keywords :
Earth; geophysics computing; hazards; monitoring; optimisation; remote sensing; scheduling; data acquisition cycle; earth observing missions scheduling method; earth science research; hazard monitoring; multi-scene observations; multiplatform sensor optimization scheduling; Data models; Earth; Fires; Monitoring; Satellites; Volcanoes; active observation model; hazards monitoring; information gain model; multi-platform; remote sensing; scheduling; sensor cloud; sensor web;
Conference_Titel :
Cluster, Cloud and Grid Computing (CCGrid), 2013 13th IEEE/ACM International Symposium on
Conference_Location :
Delft
Print_ISBN :
978-1-4673-6465-2
DOI :
10.1109/CCGrid.2013.97