Debris-flow Hazard Forecast and Alert System Based on Real- Time Wireless Communications

††† Summary This paper developed a Real-time Mobile debris-flow Disaster Prevention and Alert system (RMD2PA), which is the three-tier architecture composed of the mobile node, the multimedia server, and the decision support system based on the wireless/mobile and Internet communications. Mobile clients use handheld devices, e.g., PDA combining a cellular phone, to transmit and receive multimedia debrisflow information via the GSM/GPRS network. The case-based reasoning mechanism is embedded in the handheld device to achieve the simple debris-flow prevention and decision when the mobile communication fails. The multimedia server provides the customized information for mobile users and effectively reduces the bandwidth consumption of the mobile network. Based on the database of the preanalyzed 181 potential debris-flows in Taiwan, we build the accurate prediction models to achieve the effective debris-flow prevention by case-based reasoning scheme in the decision support server.

[1]  C. B. Hare.  Redefining user input on handheld devices , 2002 .

[2]  R. Vahidov.  Intermediating user-DSS interaction with autonomous agents , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[3]  Jens Meggers,et al.  A multimedia communication architecture for handheld devices , 1998, Ninth IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (Cat. No.98TH8361).

[4]  Leonid Churilov,et al.  A hybrid decision support system model for disaster management , 2004, Fourth International Conference on Hybrid Intelligent Systems (HIS'04).

[5]  T. Fujiwara,et al.  A framework for data collection system with sensor networks in disaster circumstances , 2004, International Workshop on Wireless Ad-Hoc Networks, 2004..

[6]  Krishna R. Pattipati,et al.  Real-time agent-based decision support system to facilitate effective organizational adaptation , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[7]  Rafael Bello,et al.  A model and its different applications to case-based reasoning , 1996, Knowl. Based Syst..

[8]  Efraim Turban,et al.  Decision support systems and intelligent systems , 1997 .

[9]  Lizy Kurian John,et al.  Reducing server data traffic using a hierarchical computation model , 2005, IEEE Transactions on Parallel and Distributed Systems.

[10]  Gang Wu,et al.  Applying case-based reasoning to multi-attribute e-purchasing decision , 2005, 2005 International Conference on Machine Learning and Cybernetics.

[11]  Les Gasser,et al.  AI on the WWW : Supply and Demand Agents , 1995, IEEE Expert.

[12]  M. Jalili-Kharaajoo.  Mobile information and consultation support system (MICSS): a new m-business service , 2004, Proceedings. 2004 International Conference on Information and Communication Technologies: From Theory to Applications, 2004..

[13]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..