Localization in Wireless Sensor Networks Poorya Ghafoorpoor Yazdi 105003 Mohammad Zerrat Talab 105081 Masoud Toughian 115089 Maziar Movahedi 085131

Outlines Definition about sensor node Comparison of WSN with Ad Hoc Network General Application of the wireless sensor networks Manufacturing Application of WSN Definition about Localization of WSN Specific application of localization in manufacturing

Outline Definition about wireless sensors Wireless Sensor Networks Application of WSN Application of WSN in Manufacturing Localization – What? Why? Classification of Localization Algorithms Examples of Localization Techniques

Energy Harvesting System Node Hardware 1Kbps - 1Mbps, 3-100 Meters, Lossy Transmissions 128KB-1MB Limited Storage Transceiver 8-bit, 10 MHz Slow Computations Memory Embedded Processor Sensors Battery 66% of Total Cost Requires Supervision Limited Lifetime Energy Harvesting System

Wireless sensor network VS Ad Hoc Network Wireless Sensor Networks are networks that consists of sensors which are distributed in an ad hoc manner. These sensors work with each other to sense some physical phenomenon and then the information gathered is processed to get relevant results. Wireless sensor networks consists of protocols and algorithms with self-organizing capabilities.

Wireless sensor network VS Ad Hoc Network Wireless sensor networks mainly use broadcast communication while ad hoc networks use point-to-point communication. Unlike ad hoc networks wireless sensor networks are limited by sensors limited power, energy and computational capability. Sensor nodes may not have global ID because of the large amount of overhead and large number of sensors.

Fields of application of wireless sensor networks

Applications of sensor networks Military applications: Monitoring friendly forces, equipment and ammunition Exploration of opposing forces and terrain Battlefield surveillance Battle damage assessment Nuclear, biological and chemical attack detection

Applications of sensor networks Health applications: Tele-monitoring of human physiological data Tracking and monitoring patients and doctors inside a hospital Drug administration in hospitals

Example of Products Applicable for Health care Pulse Oximeter Glucose Meter Electrocardiogram (ECG) Social Alarm Devices

Smart Buildings Sensors and sensor networks are used in multiple smart building applications: Heating, ventilation, and air conditioning systems Lightning  Air quality and window control Systems switching off devices  Standard household applications (e.g. televisions, washing machines) Security and safety (access control)

Example of Smart buildings The headquarters of the New York Times is an example of how different smart building technologies can be combined to reduce energy consumption and to increase user comfort. Overall, the building consumes 30 % less energy than traditional office skyscrapers.

Environmental Monitoring This sensor measures light, temperature, and humidity, and can be equipped to do soil- moisture measurements. The system takes measurements every second and transmits over 40 meters.(about 3cm diameter) It was developed for planetary monitoring by the Jet Propulsion Laboratory.

Some Interesting Applications MIT d'Arbeloff Lab – The ring sensor Monitors the physiological status of the wearer and transmits the information to the medical professional over the Internet Oak Ridge National Laboratory Nose-on-a-chip is a MEMS-based sensor It can detect 400 species of gases and transmit a signal indicating the level to a central control station

iBadge - UCLA Investigate behavior of children/patient Features: Speech recording / replaying Position detection Direction detection / estimation(compass) Weather data: Temperature, Humidity, Pressure, Light

Wireless Sensor Networks Applications In manufacturing WSNs can be used advantageously for rare event detection or periodic data collection for manufacturing applications. In rare event detection, sensors are used to detect and classify rare and random events, such as alarm and fault detection notifications due to important changes in machine, process, plant security or operator actions. On the other hand, periodic data collection is required for operations such as tracking of the material flows, health monitoring of equipment/process. Such monitoring and control applications reduce the labor cost and human errors.

End-User View of Manufacturing WSN Likes Mobility Compactness Flexibility Low cost Capability to monitor rotating equipment Short range (security) Ease of installation High reliability Impetus to enhance electronics support Dislikes Change to status quo Complexity High cost for coverage in large plants Security issues Portability issues (power) Unproven reliability Too risky for process control Lack of experience in troubleshooting (staff) Restricted infrastructure flexibility once implemented Lack of analysis tools

Manufacturing Application Inventory Tracking In-Process Parts Tracking Customer Tracking Plant Equipment Maintenance and Monitoring

Example of Manufacturing Applications

Localization in Wireless Sensor Networks What? To determine the physical coordinates of a group of sensor nodes in a wireless sensor network (WSN) Due to application context, use of GPS is unrealistic, therefore, sensors need to self-organize a coordinate system Why? To report data that is geographically meaningful Services such as routing rely on location information; geographic routing protocols; context-based routing protocols, location-aware services Low cost of nodes allows massive scale & highly parallel computation Each node has limited power, limited reliability, and only local communication with neighbors

Localization in Wireless Sensor Networks In general, almost all the sensor network localization algorithms share three main phases DISTANCE ESTIMATION POSITION COMPUTATION LOCALIZATION ALGHORITHM

Obtain a Vague Position End Start Exist an Unknown Node which has at least three reference node in its coverage area End Select an Unknown Node Unknown Nod Selection Obtain a Vague Position Select Reference Node Drive local Position for reference Node Distance Estimation Estimate the Distance to the Reference Node Any Selected Reference Node Without Estimated Distance Calculate the Position of the Selected Unknown Node Position Computation

Localization in Wireless Sensor Networks The distance estimation phase involves measurement techniques to estimate the relative distance between the nodes. The Position computation consists of algorithms to calculate the coordinates of the unknown node with respect to the known anchor nodes or other neighboring nodes. The localization algorithm, in general, determines how the information concerning distances and positions, is manipulated in order to allow most or all of the nodes of a WSN to estimate their position. Optimally the localization algorithm may involve algorithms to reduce the errors and refine the node positions.

Distance Estimation There are four common methods for measuring in distance estimation technique: ANGLE OF ARRIVAL (AOA) TIME OF ARRIVAL (TOA) TIME DIFFERENT OF ARRIVAL (TDOA) THE RECEIVED SIGNAL STRENGH INDICATOR (RSSI)

Distance Estimation ANGLE OF ARRIVAL method allows each sensor to evaluate the relative angles between received radio signals TIME OF ARRIVAL method tries to estimate distances between two nodes using time based measures TIME DIFFERENT OF ARRIVAL is a method for determining the distance between a mobile station and nearby synchronized base station THE RECEIVED SIGNAL STRENGTH INDICATOR techniques are used to translate signal strength into distance.

Position Computation The common methods for position computation techniques are: LATERATION ANGULATION

Position Computation LATERATION techniques based on the precise measurements to three non collinear anchors. Lateration with more than three anchors called multilateration. ANGULATION or triangulation is based on information about angles instead of distance.

Classifications of Localization Methods According to the ways of Sensors implementation, we classify the current wireless sensor network localization algorithms into several categories such as: Centralized vs Distributed Anchor-free vs Anchor-based Range-free vs Range-based Mobile vs Stationary

Centralized vs Distributed All computation is done in a central server Distributed Computation is distributed among the nodes

Anchor-Free vs Anchor-Based Anchor Nodes: Nodes that know their coordinates a priori By use of GPS or manual placement For 2D three and 3D four anchor nodes are needed Anchor-free Relative coordinates Anchor-based Use anchor nodes to calculate global coordinates Disadvantages of anchor nodes: GPS receivers are expensive. cannot typically be used indoors GPS receivers also consume significant battery Alternative to GPS is preprogramming nodes with their locations, which can be impractical (for instance, when deploying 10,000 nodes with 500 beacons) or even impossible (for instance, when deploying nodes from an aircraft).

Range-Free vs Range-Based Local Techniques Hop-Counting Techniques Range-Based Received Signal Strength Indicator (RSSI) Attenuation RF signal Time of Arrival (ToA) time of flight Time Difference of Arrival (TDoA) requires time synchronization electromagnetic (light, RF, microwave) sound (acoustic, ultrasound) Angle of Arrival (AoA) Range-free: Only use connectivity information Not very accurate Range-based: require extra hardware therefore have a higher cost, Much more accurate

Proposed Method Range Based Centralized Localization using Neural Networks

Training

Experiment

(1,1) (4,3) (2,7) (5,5) (7.5,7.3) (9,5) Anchor node 1 -47 -66 -73 -72 -70 -69 Anchor Node 2 -74 -75 -63 Anchor Node 3 -71 Anchor Node 4