a survey on tracking methods for a wireless sensor network taylor flagg, beau hollis & francisco...
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A Survey on Tracking A Survey on Tracking Methods for a Wireless Methods for a Wireless
Sensor NetworkSensor Network
Taylor Flagg, Beau Hollis & Taylor Flagg, Beau Hollis & Francisco J. Garcia-Ascanio Francisco J. Garcia-Ascanio
OverviewOverview
Sensor Network TrackingSensor Network Tracking Hierarchical Approach Hierarchical Approach Hidden Markov Model with Binary SensorsHidden Markov Model with Binary Sensors Compare and ContrastCompare and Contrast
Pursuit Evasion Games Pursuit Evasion Games Two-Tier Approach Two-Tier Approach Multi-Hop ApproachMulti-Hop Approach Ant-Based ApproachAnt-Based Approach Compare and ContrastCompare and Contrast
ConclusionConclusion
Sensor Network TrackingSensor Network Tracking
Tracking an object moving through a field Tracking an object moving through a field of sensorsof sensors Smart HouseSmart House Air Traffic ControlAir Traffic Control Fleet MonitoringFleet Monitoring SecuritySecurity
Many sensor types can be usedMany sensor types can be used
Hierarchical ApproachHierarchical Approach
STUN: Scalable Tracking Using STUN: Scalable Tracking Using Networked sensorsNetworked sensors Sensor network described as a hierarchical Sensor network described as a hierarchical
graphgraph Each node has a detection setEach node has a detection set Object positions are queried from the root Object positions are queried from the root
using detection setsusing detection sets
Detection SetsDetection Sets
Nodes broadcast detected objectsNodes broadcast detected objects
Parents broadcast set of objects detected Parents broadcast set of objects detected by their child nodesby their child nodes
Only broadcast when set changesOnly broadcast when set changes
Redundant massages are prunedRedundant massages are pruned
Graph weightsGraph weights
The sensor graph is weighted based on The sensor graph is weighted based on movement patternsmovement patterns
Higher weight means more objects Higher weight means more objects transition between those two nodestransition between those two nodes
Communication CostCommunication Cost
Depends on number of messages Depends on number of messages transmittedtransmitted
Tree structure affect costTree structure affect cost
DAB – Drain and BalanceDAB – Drain and Balance
IdeaIdea Imagine flooding a mountain rangeImagine flooding a mountain range At each step water level is lowered and visible At each step water level is lowered and visible
peaks are added to the treepeaks are added to the tree
Actual AlgorithmActual Algorithm Set a weight thresholdSet a weight threshold Add balanced sets of with weights above the Add balanced sets of with weights above the
thresholdthreshold Iteratively lower threshold and reapplyIteratively lower threshold and reapply
Using Hidden Markov Model to Track Using Hidden Markov Model to Track with Binary Sensorswith Binary Sensors
Binary sensors only report if an object is Binary sensors only report if an object is detected or notdetected or not
Reduces affect of calibration and error Reduces affect of calibration and error
Sensor location is not neededSensor location is not needed
Object paths are based on statistical Object paths are based on statistical analysisanalysis
GraphGraph
Sensor graph with links for adjacent sensorsSensor graph with links for adjacent sensors
Graph forms Hidden Markov Model (HMM)Graph forms Hidden Markov Model (HMM)
HMM is used to calculate probable object pathsHMM is used to calculate probable object paths
Path prediction uses the Path prediction uses the Viterbi Viterbi AlgorithmAlgorithm
ImplementationImplementation
Each node stores 3 values required for the Each node stores 3 values required for the path calculationpath calculation Probability of an object starting at that nodeProbability of an object starting at that node Probability that objects will be accurate Probability that objects will be accurate
detected (accounts for sensor error)detected (accounts for sensor error) Matrix of probabilities for transition to another Matrix of probabilities for transition to another
node in the node’s neighborhood node in the node’s neighborhood
SimilaritiesSimilarities
Avoid localization issues by graphing Avoid localization issues by graphing sensor topologysensor topology
Communicate in between nodes rather Communicate in between nodes rather than flooding the networkthan flooding the network
Pruning redundant informationPruning redundant information
Use pre-computed probabilities and Use pre-computed probabilities and weights to gain efficiencyweights to gain efficiency
DifferencesDifferences
HMMHMM Operates on binary Operates on binary
sensorssensors Processes all Processes all
necessary necessary information in each information in each individual node, individual node, distributes trackingdistributes tracking
Communicates back Communicates back and forth among and forth among neighbors neighbors
STUNSTUN Made for non-uniform Made for non-uniform
movementmovement Leaves actual Leaves actual
tracking to a tracking to a centralized query-centralized query-pointpoint
Only communicates Only communicates up hierarchy tree up hierarchy tree
Pursuit Evasion GamesPursuit Evasion Games
Autonomous agents (Pursuers) pursue Autonomous agents (Pursuers) pursue one or more non-cooperative agents one or more non-cooperative agents (evaders)(evaders)
Sensor networks are used to detect Sensor networks are used to detect evadersevaders
Pursuit Evasion GamesPursuit Evasion Games
In traditional PEG’s In traditional PEG’s The evaders attempt to avoid detection and The evaders attempt to avoid detection and
capture by varying speed and directioncapture by varying speed and direction
Different forms of PEG’s consist ofDifferent forms of PEG’s consist of Rescue operationsRescue operations SurveillanceSurveillance Localization and tracking of moving parts in a Localization and tracking of moving parts in a
warehouse, etc.warehouse, etc.
Lower TierLower Tier Numerous nodesNumerous nodes Handles simple detectionHandles simple detection Limited resourcesLimited resources Provide basic informationProvide basic information Power conservationPower conservation Results gathered don’t need to be perfectResults gathered don’t need to be perfect Leader election algorithm based on strongest Leader election algorithm based on strongest
detectiondetection
Two-Tier Approach Two-Tier Approach
Two-Tier Approach Two-Tier Approach
Higher TierHigher Tier Fewer nodesFewer nodes Nodes are more complex (e.g. sophisticated Nodes are more complex (e.g. sophisticated
camera nodes.)camera nodes.) Handles processing and initiates actionsHandles processing and initiates actions Resulting actions sent to the pursuerResulting actions sent to the pursuer
Pursuer has its own onboard software Pursuer has its own onboard software service for interception and navigationservice for interception and navigation Receives detection events from the networkReceives detection events from the network Determines if event was caused by the Determines if event was caused by the
evader, another pursuer, or noiseevader, another pursuer, or noise Pursuer only needs data from the network Pursuer only needs data from the network
every few secondsevery few seconds Uses GPS to calculate an interception Uses GPS to calculate an interception
destinationdestination
Pursuer in Two Tier System Pursuer in Two Tier System
Multi-Hop ApproachMulti-Hop Approach
Sensor nodes estimate evader positions Sensor nodes estimate evader positions and push their data to other nodes and to and push their data to other nodes and to the pursuerthe pursuer
Super nodes Super nodes Receive data and do processing to get a Receive data and do processing to get a
composite estimatecomposite estimate Collaborate with neighbors to further improve Collaborate with neighbors to further improve
the estimates the estimates Broadcast final estimate to pursuerBroadcast final estimate to pursuer
Multi-Hop ProblemsMulti-Hop Problems
Cost effective sensors are problematicCost effective sensors are problematic Small power supplySmall power supply Low detection probabilityLow detection probability High false alarm rateHigh false alarm rate
With each hop, likelihood of transmission With each hop, likelihood of transmission failure and packet delays increasefailure and packet delays increase
Ant-Based ApproachAnt-Based Approach
Based on how ants gather foodBased on how ants gather food Ants leave trail of pheromones Ants leave trail of pheromones Other ants follow the direction in which Other ants follow the direction in which
pheromones are most intensepheromones are most intense
Sensors store a timestamp of evader Sensors store a timestamp of evader detectiondetection
Pursuer looks compares timestamps in a Pursuer looks compares timestamps in a region to derive the evaders directionregion to derive the evaders direction
Ant-Based ImplementationAnt-Based Implementation
Ant-Based approach is broken down into Ant-Based approach is broken down into three phases:three phases: Reporting the Initial PositionReporting the Initial Position Initiation of TrackingInitiation of Tracking TrackingTracking
Reporting the Initial PositionReporting the Initial Position
Starts when first sensor detects evader. Starts when first sensor detects evader. This node will do the followingThis node will do the following Contacts pursuerContacts pursuer Broadcast to entire network about the evader Broadcast to entire network about the evader
and suppresses other nodes from contacting and suppresses other nodes from contacting the purser with redundant informationthe purser with redundant information
Subsequent nodes will send new information to Subsequent nodes will send new information to the purser but not the entire networkthe purser but not the entire network
Initiation of TrackingInitiation of Tracking
Pursuer heads toward the first node to Pursuer heads toward the first node to detect the evaderdetect the evader
Pursuer queries nearby nodes for Pursuer queries nearby nodes for timestampstimestamps
These timestamps are used to determine These timestamps are used to determine the velocity vectorthe velocity vector
TrackingTracking
Pursuer intelligently queries only nodes in Pursuer intelligently queries only nodes in the direction of the velocity vectorthe direction of the velocity vector
Compares timestamps and looks for larger Compares timestamps and looks for larger timestamp valuetimestamp value
Cuts down on communication costsCuts down on communication costs
The velocity vector is updated and the The velocity vector is updated and the process is repeated until the evader is process is repeated until the evader is captured or leaves the networkcaptured or leaves the network
SimilaritiesSimilarities
Sensor nodes are pre-established in the Sensor nodes are pre-established in the region that the evader will occupyregion that the evader will occupy
Systems provide a lower tier of nodes Systems provide a lower tier of nodes that only collect evader datathat only collect evader data
DifferencesDifferencesTwo-TierTwo-Tier
Higher tier contain processing and Higher tier contain processing and tracking algorithmstracking algorithms
Dedicated software services located on Dedicated software services located on the pursuerthe pursuer
Elect a leader node to distribute Elect a leader node to distribute informationinformation
Results don’t need to be perfectResults don’t need to be perfect
Leader election based on strongest Leader election based on strongest detectiondetection
Multi-HopMulti-HopHigher tier nodes contain Higher tier nodes contain processing and tracking algorithmsprocessing and tracking algorithms
Collaborates with neighboring super Collaborates with neighboring super nodes to improve estimatesnodes to improve estimates
Super node similar to leader Super node similar to leader election to propagate information to election to propagate information to pursuerpursuer
Ant-BasedAnt-BasedNodes collect timestamp of evaderNodes collect timestamp of evader
Pursuer uses timestamp to get velocity vector and which node to contact nextPursuer uses timestamp to get velocity vector and which node to contact next
Nodes communicate only with pursuerNodes communicate only with pursuer
ConclusionsConclusions
The tiers systems can benefit from The tiers systems can benefit from hierarchal topologyhierarchal topology Super nodes are at the root of the treeSuper nodes are at the root of the tree
Ant based approachAnt based approach Use HMM to shift processing from the pursuer Use HMM to shift processing from the pursuer
to sensor networkto sensor network Pursuers queries the sensorsPursuers queries the sensors