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  1. 1. Hitesh Lodha, Dipti Sakhare / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue4, July-August 2012, pp.1091-1096 Energy Efficient & Optimum Path Selective Techniques For Flood Monitor System In WSN Hitesh Lodha*1, Dipti Sakhare*2 # Department of Electronics Engineering University of pune Maharashtra Academy of Engineering, Alandi, Pune‖Abstract Natural disasters such as , flooding An important aspect of flood management is theearthquakes results in massive loss of life and issuing of timely flood alerts. The spatial, as well asproperty .To optimize loss due to such natural temporal, scale of these warnings is important. Suchdisasters Warning communities of the incoming situations include issuing warnings for small groupsdisaster provides an effective solution to this by of outlying houses or key infrastructure locationsgiving people sufficient time to evacuate and such as power sub-stationsprotect their property. The aim of project is to In a Rainy climate, the water level rise todesign the event driven Flood Monitoring System high level due to heavy rain and it is normal levelwith wireless sensor networks. This system due to sunshine throughout the year. In aMeasures River and weather conditions through conventional flood monitoring system the sensorwireless sensor nodes equipped with different data would be collected on constant rate throughoutsensors. An event driven system support its operation period.multirate sampling . To design system we selected This approach monitor data rate constantlyCC2530ZNP mini kit as hardware platform. It is which gives huge data which is constant & does notZigBee network processor which is based upon show change occurred in envir onmental conditionMSP430F2274 controller; this kit has battery so better approach is to develop a system which isoperated sensor node with low power shown in fig 1 support for change in data samplingconsumption & event driven system gives energy rate according environment condition. The main aimefficiency in node We simulated the routing behind this project is expand functionality ofmetric which is designed to find path efficiency wireless sensor network which continuously monitorbetween single hop transmissions as well as for parameter like rain fall, weather condition & watermultiple path efficiency calculation. The routing level.metric is designed considering residual energy of 1. System developmenteach node and required delay The routing metricconsider connectivity between nodes andretransmission of data; hence guaranteedtransmission of data from source to destination isassured with minimum energy path utilizationthis increases lifetime of the network.Keywords— wireless sensor network, Event driven,rain fall sensor, CC2530ZNP, MSP430F2274. Fig 1 Block Diagram for flood Alert Monitor system.I. Introduction Monitoring subsystem:- This project is aimed at helping the In this project various parameter like waterpopulation large amounts of property loss and level, light intensity, battery voltage (node battery)casualties caused by flash-floods. A flash-flood is a are monitored & system is designed with multiratesudden discharge of large amounts of water. Usually, sampling. In normal days when water level atheavy rainfall increases the level of rivers; at the normal level (below the position of sensor 1), nodesame time, a dam-forming effect occurs, triggered of slaves send data with low sampling rate & whenby other phenomena like ice jams or landslides. The event of flood occur node send data with high dataaim of this paper is to describe the design and sampling to coordinator.implementation of a system that will collect the Wireless communication:-environmental data like rain fall, weather condition Communication between slaves && water level with least human monitoring. coordinator is wireless ZigBee module of CC2530ZNP kit is used for wireless communication purpose. 1091 | P a g e
  2. 2. Hitesh Lodha, Dipti Sakhare / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue4, July-August 2012, pp.1091-1096Data collecting & Processing:-  The network processor is a SW image on Reading of different sensor of each node is the CC2530 device, allows upgrade tosend to coordinator & which is updated at GUI. GUI future ZigBee status of all sensor of all slaves or nodes which  The source code for the network processoris designed at coordinator side. is provided as a sample code in the Z- Stack software package .  The network processor code is flexible to allow support of custom configurations.  Support for both non-secure and secure ZigBee communication.  Small 6x6mm package .Fig 2 system Deployment Fig 4 Magnetic Reed Liquid Level Sensors In Flood monitor system theimplementation of Wireless sensor network with low In magnetic reed liquid sensors When thepower consuming node is interfaced with Sensorwhich monitoring environmental parameter is shown float ball rises or falls with the liquid to the level ofin fig 2. Selected CC2530ZNP node is low power the switch, the magnetic force of magnet whichconsuming which itself has ZigBee architecture. The inside of the float ball will cause the reed switch togiven slaves (slave1 & slave2) monitor parameter turn ON. When the float ball move away from the reed switch, the reed switch will turn OFF.regularly with different sampling rate as peroccurrence of event. In a WSN, every node acts as adata acquisition device, a data router, and a data 3 .Low power mode architectureaggregator. Such architecture maximizes the In event triggered, multirate sampling floodredundancy and consequently, the reliability of the monitoring system for designing low samplingentire flash-flood monitoring system. architecture we are using low power mode 3 (LPM3) of MSP430F2274 microcontroller.2. Event driven motes Architecture of LPM is shown in fig 5. This LPM3 To design event driven system we selected minimize power consumption of mote, increaseCC2530ZNP as mote which shown in fig 3 & energy efficiency of node & increase life time ofMagnetic Reed Liquid Level Sensor which shown in node.fig 4. Mote itself consists of light intensity sensor. Configuration of LPM3 is given by,The hardware consists of a CC2530 ZigBee devicepreprogrammed with ZigBee software and an (LPM3), I ≈ 1uAMSP430F2274 microcontroller that controls the a. CPU is disabledZigBee device. b. MCLK and SMCLK disabled c. ACLK remains active d. DCO’s dc-generator is disabledFig 3 CC2530ZNP mote Advanced Features of CC2530ZNP:- Fig 5 Low power architecture of MSP430F2274 1092 | P a g e
  3. 3. Hitesh Lodha, Dipti Sakhare / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue4, July-August 2012, pp.1091-1096 4. Flow charts of flood monitor system Proposed flood monitor system consists of START two slaves (slave1 & slave2) & coordinator which are shown in fig 2. Flow chart which is shown in fig 6 gives detailed working flow of slaves & Flow chart which is shown in fig 7 gives detailed Check Frame is NO working flow of coordinator. received from slave 1&2 START 1 YES Display status of battery condition of slave 1 & slave2 on GUI. Check LOW SLAVE 1 / 2 working on low sampling output of rate & send low level message to Display status of Light intensity sensor of sensor1 coordinator slave 1 & slave2 on GUI. 1 Check output LOW Display message on GUI HIGH of sensor1 of Sensor1 :”Low level” Both slaves sensor2 “under control”SLAVE 1 / 2 working on high sampling 1 HIGHrate & send high level message tocoordinator Display message on GUI Sensor1 :”High level” sensor2 “under control” Check LOW Send message “Flood under control” to output of coordinator Display message on GUI Check output LOW sensor2 of sensor2 of Sensor1 :”High level” 1 Both slaves sensor2 “under control” HIGH 1 HIGH Display message on GUI Send message “Flood warning” to Sensor1 :”High level” coordinator & ON buzzer sensor2 “Flood warning ” & ON buzzer. STOP Fig 7 Flow chart for coordinator 5. Routing Matrix Model for simulation of STOP optimum Path Fig 6 Flow chart for slave1 & slave2 1093 | P a g e
  4. 4. Hitesh Lodha, Dipti Sakhare / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue4, July-August 2012, pp.1091-1096 Now consider another node not included in previously formed cluster and again find a node with high path efficiency and at distance less than d2 consider the node as another CH after selection of CH form cluster by step II Continue this step until all nodes at distance d2 are selected in clusters formed Step IV: CH Based Cluster Head Selection Consider any Previous selected CH set Now calculate path efficiency between each node and CH. Node with high path efficiency and at distance less than rc is selected as cluster head Fig 8 Routing Matrix Model Step V: CH Based Cluster formation For optimum path purpose, We adopt the After cluster head selection the clustermodel shown in fig 8. This model captures the formationphase starts. Path efficiency betweenpacket reception rate (PRR) between two nodes as neighbor nodeand cluster head is calculated. Iffollows. Nodes have full connectivity if they have a Neighbour’s pathefficiency is greater with clusterdistance less than D1. They are disconnected if they head then associateeach node as CM of cluster withare separated by a distance greater than D2. The CH.expected PRR decreases smoothly in the transitiveregion between D1 and D2. The behaviour is Step VI: Repeat Step IV and V to form clustermodelled by equ (1)s until each node is associated with a cluster. Result of optimum path algorithm shown in fig 12 & fig 13 6. Result:- In this paper we are discussing result in two section ; one for flood monitor system & another is simulation result for optimum pathWhere X ~ N(0, ) is a gaussian variable with algorithmvariance . 6.1 Result for Flood monitoring system(This equation is modified, in numerator, d – D1 isreplaced by D2 – d to find 1 when d = D1)5.1 Proposed Solution for optimum path The proposed approach consists of followingsteps Phase-I: Cluster head selection and clusterformation Step I: Base Station based First Cluster HeadSelection: All the deployed nodes send their energylevels to the Base Station. Then on the basis ofenergy level and delay path efficiency is calculatedbetween each node and BS. Node with high pathefficiency and at distance less than d2 is selected ascluster head. Fig 9 GUI of Flood monitoring system Step II: Cluster Formation Flood monitoring system monitoring After First cluster head selection the cluster parameter water level of Dam, light intensity offormation phase starts. Path efficiency between surrounding of Dam & voltage of node. In givenneighbor node and cluster head is calculated. If system we are monitoring parameter of two DamNeighbor’s path efficiency is greater with cluster which are on same riverhead then associate each node as CM of cluster with Dam1 reading (slave 1 ) :- It monitor water level &CH. light intensity of surrounding. Sensor 1 kept at position which sense 55% of height of dam from itsStep III: Base station based Selection Of Another base . It sense water level which is less than its levelCluster Head level of flood is low & low level massage is send to co coordinator . 1094 | P a g e
  5. 5. Hitesh Lodha, Dipti Sakhare / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue4, July-August 2012, pp.1091-1096 In this ― low level‖ position sampling rate 6.2 Result of Optimum path algorithm:- of node is low because node goes in low power We have already discussed mode (LPM3) It send data after every 45 optimum path Algorithm in section 5; corresponding second to coordinator . In this mode node consume results are Shown below 3.5mA current which is shown in fig 10. 6.2.1 Node deployment & PRR calculationFig10 Current consumption of node duringabsent of flood (Low sampling rate) When flood occur & water level rise above 55% then ―high level ― message is send by sensor Fig 12 Deployment of node & PRR node to coordinator in which controller of node calculation wake up from LPM & comes into active mode & send data to coordinator after every 4 second In this 6.2.2Optimum path calculation between mode node consume Current around 6.7mA . node 5&9 Fig 11 Current consumption during occurrence of event Flood (High sampling rate) Sensor 2 is kept above the sensor 1 which gives indication of actual situation of flood in normal case it send message flood ―under control ― & When flood level goes on increasing & it Fig 13Optimum path calculation between crosses 80 % of height sensor2 send message node5 &9 ― flood warning ― to coordinator & buzzer get on. Finally Node is also transmitting status of battery 7 Conclusion voltage which is shown in GUI for monitoring In this project we presented energy efficient battery condition. flood monitoring system which monitoring parameter water level, light intensity and battery Dam2 reading (slave 2 ) :- voltage of slave node . We have designed system Slave 2 working as same as slave 1 . such that nodes support multi rate sampling So combining both reading (which is according to environmental condition & occurrence shown on GUI ) one take decision that how many of event which gives energy efficiency in node. So plates of dam should open for controlling flood & due to this multisampling algorithm life time of node its cause . is getting around doubled.& further we simulated 1095 | P a g e
  6. 6. Hitesh Lodha, Dipti Sakhare / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue4, July-August 2012, pp.1091-1096optimum path algorithm that considers residual Rahayfeh―Performance evaluation ofenergy of each individual node and selects energy routing protocols in wireless sensorefficient optimal path for data transmission networks‖dec2007. [10] Adeel Akhtar, Abid Ali Minhas, and Sohail8 Future Work: Jabbar,‖ Energy Aware Intra Cluster 1. Test proposed optimum path algorithm for Routing for Wireless Sensor Networks‖ designed flood monitor system by International Journal of Hybrid increasing number of node in WSN. Information TechnologyVol.3, No.1, 2. Congestion control mechanism can improve January, 2010 existence flood monitor system [11] Joe-Air Jiang , Chia-Pang Chen , Cheng- performance. Long Chuang , Tzu-Shiang Lin , Chwan- 3. This event driven system is designed for Lu Tseng 2, En-Cheng Yang 3 and Yung- flood monitor is further implemented by Chung Wang, ―CoCMA: Energy- using solar sensor node to increase life Efficient Coverage Control in Cluster- span of mote Based Wireless Sensor Networks Using a Memetic Algorithm‖, journal, Sensors 2009,References 9, 4918-4940 [1] Alvindarjit Singh, Lee Sheng Chyan, Patrick Sebastian‖ Sensor [12] Neeraj Kumar, Manoj Kumar, R.B. Patel, Integration in a Wireless Sensor Network ―Coverage and Connectivity Aware Neural System for Environmental Network Based Energy Efficient Monitoring System‖ Universiti Technology Routing in Wireless Sensor Networks‖, PETRONAS.2010 International Journal on application of [2] Mauricio Castillo-Effen, Daniel H. Quintela, graph theory nwireless ad-hoc networks Ramiro Jordan, Wayne and sensor networks (Graph-hoc), Westhoff‡ and Wilfrido Moreno‖ Wireless Vol 2, No1, March 2010. Sensor Networks for [13] I.F. Akyildiz, W. Su, Y. Flash Flood Alerting‖2004 Sankarasubramaniam, E. Cayirci,―Wireless [3] Paul J. Smith,a, Danny Hughes,b Keith ,. sensor networks: a survey‖, Published by Beven,a Philip Cross,a Elsevier Science Computer Networks 38 Wlodek Tych, Geoff Coulsonb and (2002) 393–422. Gordon Blairb ―Towards the [14] Wilson, ―Wireless Sensor Networks: provision of site specific flood warnings Principles and Applications‖, Chapter 22, using wireless sensor Chris Townsend, Steven Arms MicroStrain, networks‖2010. Inc, 439-449. [4] [15] Andr´e G¨unther and Christian Hoene,‖ Measuring Round Trip Times to Determine rface_Specification.pdf the Distance between WLAN [5] Elizabeth Basha, Member, IEEE, and Nodes‖,inproc.ofnetworking2005,waterloo, Daniela Rus, Member, IEEE,‖ Design of Canada, may 2005. Early Warning Flood Detection System for [16] David Culler Deborah, Estrin Mani Developing Srivastava, “Overview of Sensor Countries‖2008. Networks”, Published by the IEEE [6] Najet Boughanmi and YeQiong Song ―A Computer Society August New routing metric for Satisfying both 2004. energy and delay constraints in wireless [17] Rachid Ennaji and Mohammed Boulmalf, sensor Networks‖.2007 ―Routing in Wireless Sensor Networks‖, [7] M. Busse, T. Haenselmann, and W. IEEE September 3, 2009. Effelsberg, ―An Energy-Efficient Forwarding Scheme for Wireless Sensor Networks‖, Technical report 13, University of Mannheim, Dec. 2005. [8] Head Selection‖; M.J. Handy, M. Haas, D. Timmermann; ―Low Energy Adaptive Clustering Hierarchy with Deterministic Cluster‖ 2002; WCN2002.pdf [9] Laiali Almazaydeh, Eman Abdelfattah, Manal Al- Bzoor, and Amer Al- 1096 | P a g e