Forest Fire Detection System based on Wireless Sensor Network Vel Pratheesh Sankar #35190979.

Slides:



Advertisements
Similar presentations
Why do people live in tectonic areas 1.Why do people live near volcanoes? 2.What can be done to reduce the damage from a volcanic eruption?
Advertisements

A Distributed Security Framework for Heterogeneous Wireless Sensor Networks Presented by Drew Wichmann Paper by Himali Saxena, Chunyu Ai, Marco Valero,
Presentation: Energy Efficient Communication Protocol for Wireless Microsensor Networks Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan.
Fault Tolerant Routing in Tri-Sector Wireless Cellular Mesh Networks Yasir Drabu and Hassan Peyravi Kent State University Kent, OH
Forest Fire Detection Economics David L. Martell Faculty of Forestry University of Toronto Robert S. McAlpine Ontario Ministry of Natural Resources Fire.
Monitoring the hydrologic cycle in the Sierra Nevada mountains.
OTHER RECOMMEDATIONS. Increasing Spatial Resolution (Low bandwidth) Increasing Spatial Coverage (High bandwidth) Collective and Local Processing per-node,
Autonomous Localization in Wireless Sensor Networks Michael Allen Cogent Applied Research Centre Coventry University.
Optimal Data Compression and Forwarding in Wireless Sensor Networks Bulent Tavli, Mehmet Kayaalp, Ibrahim E. Bagci TOBB University of Economics and Technology.
May 14, Organization Design and Dynamic Resources Huzaifa Zafar Computer Science Department University of Massachusetts, Amherst.
Surge: A Network Analysis Tool Crossbow Technology.
Temperature Application based on Directed Diffusion Ke Liu September 2003.
Optimizing Lifetime for Continuous Data Aggregation With Precision Guarantees in Wireless Sensor Networks Xueyan Tang and Jianliang Xu IEEE/ACM TRANSACTIONS.
Wireless Sensor Networks
B.C. Forest Service FIRE DETECTION PROGRAM. FIRE HISTORY 1998 To 2002 BC experienced 8440 fires. Average of 1688/year. Considerably reduced from 10 year.
Introduction To Wireless Sensor Networks Wireless Sensor Networks A wireless sensor network (WSN) is a wireless network consisting of spatially distributed.
LOGO Intelligent Video Monitoring Solutions in Wireless Sensor Networks BY Rasha Sayed Negm Pre-Master Cairo University.
Energy Saving In Sensor Network Using Specialized Nodes Shahab Salehi EE 695.
Presented by Amira Ahmed El-Sharkawy Ibrahim.  There are six of eight turtle species in Ontario are listed as endangered, threatened or of special concern.
CS 712 | Fall 2007 Using Mobile Relays to Prolong the Lifetime of Wireless Sensor Networks Wei Wang, Vikram Srinivasan, Kee-Chaing Chua. National University.
M-GEAR: Gateway-Based Energy-Aware Multi-Hop Routing Protocol
Wireless Sensor Network Jing (Selena) He Department of Computer Science Kennesaw State University.
Power Save Mechanisms for Multi-Hop Wireless Networks Matthew J. Miller and Nitin H. Vaidya University of Illinois at Urbana-Champaign BROADNETS October.
On Renewable Sensor Networks with Wireless Energy Transfer IEEE INFOCOM 2011 Yi Shi, Liguang Xie, Y. Thomas Hou, Hanif D. Sherali.
A Review by Raghu Rangan WPI CS525 September 19, 2012 An Early Warning System Based on Reputation for Energy Control Systems.
Efficient Deployment Algorithms for Prolonging Network Lifetime and Ensuring Coverage in Wireless Sensor Networks Yong-hwan Kim Korea.
Maximum Lifetime Routing in Wireless Sensor Networks by Collins Adetu Nicole Powell Course: EEL 5784 Instructor: Dr. Ming Yu.
Research Overview Sencun Zhu Asst. Prof. CSE/IST, PSU
/42 Does Wireless Sensor Network Scale? A Measure Study on GreenOrbs Yunhao Liu, Yuan He, Mo Li, Jiliang Wang,Kebin Liu, Lufeng Mo, Wei Dong,
AF3 is a collaborative project carried out by a consortium of nineteen members from ten countries. Among the members there are universities, research technology.
Climate, fire & some other bits Scott Goodrick USDA Forest Service Southern Research Station Athens, GA.
A new Ad Hoc Positioning System 컴퓨터 공학과 오영준.
Dr. Sudharman K. Jayaweera and Amila Kariyapperuma ECE Department University of New Mexico Ankur Sharma Department of ECE Indian Institute of Technology,
1 Dynamic Sleeping Scheduling for Real-time Wireless Sensor Networks Department of EECS University of Tennessee, Knoxville Xiaodong Wang, Yanjun Yao.
Lecture 8: Wireless Sensor Networks
The Problem of Location Determination and Tracking in Networked Systems Weikuan Yu, Hui Cao, and Vineet Mittal The Ohio State University.
Modeling In-Network Processing and Aggregation in Sensor Networks Ajay Mahimkar The University of Texas at Austin March 24, 2004.
Presented by : Rashmy Balasubramanian.  Aimed at saving endangered species of turtle in Ontario  The WSN gathers information regarding risks factors.
An Energy-Efficient Geographic Routing with Location Errors in Wireless Sensor Networks Julien Champ and Clement Saad I-SPAN 2008, Sydney (The international.
Adaptive Tracking in Distributed Wireless Sensor Networks Lizhi Yang, Chuan Feng, Jerzy W. Rozenblit, Haiyan Qiao The University of Arizona Electrical.
Cross-Layer Scheduling for Power Efficiency in Wireless Sensor Networks Mihail L. Sichitiu Department of Electrical and Computer Engineering North Carolina.
Group Members Usman Nazir FA08-BET-179 M.Usman Saeed FA08-BET-173
Wireless Ad Hoc Networks
TOPICS INTRODUCTION CLASSIFICATION CHARACTERISTICS APPLICATION RELATED WORK PROBLEM STATEMENT OBJECTIVES PHASES.
Hierarchical Trust Management for Wireless Sensor Networks and Its Applications to Trust-Based Routing and Intrusion Detection Wenhai Sun & Ruide Zhang.
Prolonging the Lifetime of Wireless Sensor Networks via Unequal Clustering Stanislava Soro Wendi B. Heinzelman University of Rochester IPDPS 2005.
Wireless Sensor Network Layout Stefka Fidanova 1, Pencho Marinov 1 Enrique Alba 2 1 Institute of Information and Communication Technologies – BAS 2 University.
I-Hsin Liu1 Event-to-Sink Directed Clustering in Wireless Sensor Networks Alper Bereketli and Ozgur B. Akan Department of Electrical and Electronics Engineering.
Younghwan Yoo† and Dharma P. Agrawal‡ † School of Computer Science and Engineering, Pusan National University, Busan, KOREA ‡ OBR Center for Distributed.
1 Terrain-Constrained Mobile Sensor Networks Shu Zhou 1, Wei Shu 1, Min-You Wu 2 1.The University of New Mexico 2.Shanghai Jiao Tong University IEEE Globecom.
Unpredictable Software-based Attestation Solution for Node Compromise Detection in Mobile WSN Xinyu Jin 1 Pasd Putthapipat 1 Deng Pan 1 Niki Pissinou 1.
An Application-Specific Protocol Architecture for Wireless Microsensor Networks 컴퓨터 공학과 오영준.
Wireless sensor and actor networks: research challenges Ian. F. Akyildiz, Ismail H. Kasimoglu
A Secure Routing Protocol with Intrusion Detection for Clustering Wireless Sensor Networks International Forum on Information Technology and Applications.
Ing-Ray Chen, Member, IEEE, Hamid Al-Hamadi Haili Dong Secure and Reliable Multisource Multipath Routing in Clustered Wireless Sensor Networks 1.
How to minimize energy consumption of Sensors in WSN Dileep Kumar HMCL 30 th Jan, 2015.
Lecture 8: Wireless Sensor Networks By: Dr. Najla Al-Nabhan.
Patent technology for USN Jinho Son Real-Time System Lab.
Wireless Sensor Network for pipeline Leak Detection
Ioana Apetroaei Ionuţ-Alexandru Oprea Bogdan-Eugen Proca
Diagnosing Wireless Sensor Networks through Wireless Mobile Nodes
Weikuan Yu, Hui Cao, and Vineet Mittal The Ohio State University
Wireless Sensor Network Architectures
Energy-Efficient Communication Protocol for Wireless Microsensor Networks by Wendi Rabiner Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan Presented.
Net 435: Wireless sensor network (WSN)
Wireless sensor network & Private mobile computer
SEP routing protocol in WSN
Lecture 3: Wireless Sensor Networks
Presentation by Andrew Keating for CS577 Fall 2009
Wireless Sensor Networks: nodes localization issue
Presentation transcript:

Forest Fire Detection System based on Wireless Sensor Network Vel Pratheesh Sankar #

Overview  Forest is one of the most indispensable resource  Causes of forest fire:  Natural  Uncontrolled human behavior  Occurs occasionally, but recently the due to climatic fluctuations and human activities there is a increased risk

Conventional Methods  Ground patrolling  Watching tower  Aerial prevention

Forest fire detection using WSN 

Data flow  Sensor nodes  Base station  Network coordinators  “Data Transmitted in a multi-hop manner”

Data flow  Data is not transmitted by every node to the base station, rather is aggregated and is transmitted through few nodes  This is done to optimize the energy consumption

Prediction  Spread of forest fire is strongly related to weather conditions, terrain, vegetation etc  Proper prediction model is selected to estimate the spread

Thank You