Browse Prior Art Database

Distributed framework on wireless smart network for early control of disaster

IP.com Disclosure Number: IPCOM000235826D
Publication Date: 2014-Mar-26
Document File: 5 page(s) / 47K

Publishing Venue

The IP.com Prior Art Database

Abstract

The disclosed technique focuses on to design the distributed framework (DF) that will be built on wireless smart network namely wireless sensor network (WSN) termed as the predictive environmental sensor network (PESN). This is a three step design procedure.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 26% of the total text.

Page 01 of 5

Distributed framework on wireless smart network for early control of disaster

Introduction:

This distributed framework (DF) provides complex engineering and system challenges. This system must endure with the event of interest, remains functional over longer periods when no events occur, covers larger geographical regions of interest to the event, and supports the variety of sensors needed to detect the disaster like river flooding, tsunami, cyclonic phenomenon, etc.

This solution will give a new architecture (PESN), distributed framework (DF), and real time

prediction of the disaster (flood, etc.) and data collection. The challenges lie in the design and,

proto-type development and the implementation of (PESN), distributed framework (DF) and real time disaster (flood, etc.) prediction and data collection. Proposed solution method in

prediction model/data collection in distributed framework is a multivariate statistical model that will predict and collect data at real time in PESN.

The goal of this work to design DF on PESN is to:

1) Develop an algorithm for disaster (e.g., monsoon flood, cyclonic flood, etc.,) prediction that uses data from the spatially distributed sensors of PESN

2) Design of PESN to support distributed, robust, real-time data collection, transmission, and, eventually, processing around large geographic regions

3) Test the disaster prediction algorithm and demonstrate long-term data collection of river flow (e.g.) data with PESN, and


4) Test the networking capabilities of PESN in a rural/remote settings

Briefly, the goal is to develop DF with these functional blocks that can turn PESN effective and robust so that it will provide a platform to monitor and communicate over larger areas like river basins, predict flooding autonomously.

Merits of this technique include complex engineering and systems challenges of the solution of

practical and deployment interest to design DF on PESN. This DF would use to control environmental phenomena like earthquake, tsunami, cyclone, etc.

Earlier work:

Recent research work in WSNs highlighted the growing applicability of networks to everyday

problems. In the area of monitoring and detecting environmental phenomena, work on habitat monitoring of birds [1], zebras [2], [3], and a redwood tree [4] exemplified the usefulness of these systems. In each of these domains, the use of low-power wireless sensors offers the

potential to collect data at spatial and temporal scales that are not feasible with existing system architecture. Despite increased interest in this area, little has been done to evaluate the ability of sensor networks to provide meaningful data to cater everyday problems users encountered. A number of challenges confound such an effort, including node failure, message loss, sensor calibration, and inaccurate time synchronization. To successfully aid these studies, sensor

1


Page 02 of 5

networks must be held to the high standards of real-world applications. One can be...