Wsn sarada-univ-02-03-13-final-2


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Basic architecture of Wireless Sensor Node, and the sensors available on the SmartPhone

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Wsn sarada-univ-02-03-13-final-2

  1. 1. Dr. SRN Reddy, Email id:rammallik@yahoo.comOverview of WSNImplementationsAnd role of Smart Phones
  2. 2. AgendaDr. SRN Reddy, Email id:rammallik@yahoo.comWSN in Education and R&D –MekWSN and its typesSmart Phone as a Sensor(s)Demo –A practical ImplementationOther ImplementationsConclusions
  3. 3. Mobile Education Kit- MekPresented By: Mek Team ,IGIT DelhiDr. SRN Reddy, Email
  4. 4. IntroductionMobile Devices are used for several purpose Calling SMS Entertainment Social Networking InternetUse of Mobile for learning teaching and R&D is a new experienceDr. SRN Reddy, Email
  5. 5. Existing SystemDr. SRN Reddy, Email Lack of quality practical technical education. More focus on the theoretical knowledge Need Immense training to make the students productive Lack of practical training on emerging technologies like MobileArchitecture, RTOS, WSN etc Leads the problem to the industry for training and more time tomarket 5,50,000 engineering graduates passing out every year butunfortunately only 10% to 25% of them are readily employed byany Technology firm while it is roughly 15% for back-office jobs.[1] Stronger coordination between campuses and companies isneeded.[1]
  6. 6. Mobile Education Kit-MekDr. SRN Reddy, Email id:rammallik@yahoo.comMobile Education Kit – Mek is a platform which bridgesthe gap between theory and practices among the studentthrough a set of experiment related to ICT subjects taught inthere undergraduate and post-graduate program.We provide them resources in term of – Ebooks Web-links Blogs, technical papers and Mobile appsDevelopment Platforms - Linux Nokia OS (S 40 series) Windows Phone
  7. 7. ObjectivesVISIONTo impact quality of technical education by bridging the gapbetween theory and practice in teaching/learning of variousICT subjects using the ubiquitous mobile devices as the newpedagogical platform.[2]MISSIONDevelop a practical teaching and learning environment thatprovides comprehensive set of guides and experiments,catering to the needs of Computer Science, Electronics andInformation & Telecommunication technologies, by makinguse of modern computing platforms and make it freelyaccessible through : [2]Dr. SRN Reddy, Email
  8. 8. Subject ConsideredDr. SRN Reddy Email id:rammallik@yahoo.comExperiments for Mobile Computing Image Processing Embedded System Sensor and Sensor’s Network Computer Graphics Database Management System
  9. 9. Experiment Design TemplateDr. SRN Reddy Email id:rammallik@yahoo.comName of Experiment: Exp No:Background:Summary:Target Platform:Procedure:Source Code CommentScreenshotsObservation:
  10. 10. Experiment Design Template -ExampleDr. SRN Reddy Email
  11. 11. Sensor & Sensor’s NetworkDr. SRN Reddy Email id:rammallik@yahoo.comDone To be DoneDisplay Accelerometer ProximityGPS GyroscopeCompass
  12. 12. WNN Node:Radio ComponentsProcessorsStorageSensing UnitDr. SRN Reddy Email
  13. 13. Basic Components of a SensorNodeDr. SRN Reddy Email
  14. 14. Types of Sensor NetworksBased on the location: Terrestrial WSN Underground WSN Underwater WSN Multi-media WSN Mobile WSNDr. SRN Reddy Email
  15. 15. Terrestrial WSNA network consists of hundreds to thousands of sensor nodes deployed onlandChallenges : Finding the optimal route Distributing energy consumption Maintaining network connectivity Eliminating redundancy Reduce the amount of data communicationApplications :Environmental sensing and monitoringIndustrial monitoringSurface explorationsDr. SRN Reddy Email
  16. 16. Underground WSNDr. SRN Reddy Email id:rammallik@yahoo.comA network consists of wireless sensor nodes deployed in caves or mines orundergroundChallenges : Expensive deployment Maintenance Equipment costApplications : Agriculture Monitoring Landscape Management Underground Structural Monitoring Underground Environment Monitoring of Soil, Water or Mineral Military Border Monitoring
  17. 17. Underwater WSNDr. SRN Reddy Email id:rammallik@yahoo.comNetwork consists of wireless sensor and vehicles deployed into theocean environmentChallenges: Expensive underwater sensors Hardware failure due to environment effects (e.g., corrosion) Battery power cannot easily be replaced Sparse deployment and Limited bandwidthApplications: Pollution monitoring Undersea surveillance and exploration Disaster prevention monitoring Seismic monitoring Equipment monitoring Underwater robotics
  18. 18. Multi-media WSNA network consists of wireless sensor devices that have the ability to store,process, and retrieve multi-media data such as video, audio, and images.Challenges: In-network processing, filtering, and compressing of multi-mediaHigh energy consumption and bandwidth demandDeployment based on multi-media equipment coverageFlexible architecture to support different applicationsMust integrate various wireless technologiesQoS provisioning is very difficult due to link capacity and delaysEffective cross-layer designApplications :Enhancement to existing WSN applications such as tracking and monitoring.Dr. SRN Reddy Email
  19. 19. Mobile WSNDr. SRN Reddy Email id:rammallik@yahoo.comA network consists of mobile sensor nodes with ability to moveChallenges: Navigating and controlling mobile nodes Must self-organized Localization with mobility Minimize energy cost Maintaining network connectivity In-network data processing Data distribution and Mobility management Minimize energy usage in locomotion Maintain adequate sensing coverageApplications : Environmental and Habitat monitoring Military surveillance and Target tracking Underwater monitoring
  20. 20. WNS Applications[2]Dr. SRN Reddy Email id:rammallik@yahoo.comThanking You
  21. 21. Issues in WSN[1]Dr. SRN Reddy Email id:rammallik@yahoo.comThanking You
  22. 22. Protocol ArchitectureDr. SRN Reddy
  23. 23. WSN vs MANETDr. SRN Reddy Email:rammallik@yahoo.comWSN MANETSimilarity Wireless Network Multi-hop wirelessnetworkingSecurity Symmetric Key Cryptography Public Key CryptographyRoutingProtocolsSupport specialized trafficpattern. Cannot afford to havetoo many node states andpacket overheadSupport any node pairsSome source routing anddistance vector protocolincur heavy control trafficUse ofResourceTighter resources (power,processor speed, bandwidth)Not as tight.
  24. 24. Sensors in a Smart Phone• Compass• Image sensor• Fingerprint sensor• Moisture sensor• Tactile sensor• Temperature sensor• Proximity sensor• Accelerometer sensor• Light sensorDr. SRN Reddy
  25. 25. Need of On device Sensors•Satisfies the needs of the customers•All the relevant information required for me•More intelligent and has morecomputational and communication power•More services•Cheaper solutions with integration•More AppsDr. SRN Reddy
  26. 26. Mobile Phone Worked as a Sensornode in Health Monitoring[2]Dr. SRN Reddy
  27. 27. Nokia Lumia 800Windows PhoneSensorsDr. SRN Reddy
  28. 28. Accelerometer•The accelerometer is a built-in electronic component that measures tiltand motion.•The Accelerometer sensor detects the force of gravity along withreference to the movement of the phone.•It can detect the rotation and motion gestures such as swinging orshaking.•Applications:―Screen rotation from portrait to landscape or vice-versa.―Enriching the game controls.―Controlling the mobile device music player with gesture:-Mute an incoming callSilence an alarm or pause the mobile music player simply byturning the device face down.Dr. SRN Reddy
  29. 29. Demo on Accelerometer• Display the motion of device in 3D plane represented by threelines (Red, Blue, Green) along x, y, z axis.– Red color line represents the movement along x-axis.– Green color line represents the movement along y-axis.– Blue color line represents the movement along z-axis.• Get the values of changing coordinates, in each x, y and z planebased on the Accelerometer.• Major function-– TimeBetweenUpdates=TimeSpan.FromMilliseconds(20);– CurrentValueChanged+=newEventHandler<SensorReadingEventArgs<AccelerometerReading>>– Vector 3 acceleration=e.SensorReading.Accleration;– X=acceleration.X.ToString();– Y=acceleration.Y.ToString();– Z=acceleration.Z.ToString();Dr. SRN Reddy
  30. 30. Compass (Magnetometer)• Compass or magnetometer sensor used to determine theangle by which the device is rotated relative to the Earth’smagnetic north pole.• Use raw magnetometer readings to detect magneticforces around the device.• It senses orientation relative to the Earths magnetic fieldusing the Hall Effect.• To measure strength, orientation, and direction ofmagnetic field.Devices: Nokia N97, Nokia E72, Lumia 800 etcApplications : - Auto rotate your digital maps depending onyour physical orientation and helps to thefind direction in an easy way.Dr. SRN Reddy
  31. 31. Demo on Compass• Display the Magnetic Heading values in terms ofradian.• Red line represents the movement of device alongthe Earth’s magnetic field.• Needle is always pointing towards the Northdirection.• Major Function:– DispatcherTimer.Interval=TimeSpan.FromMilliseconds(30);– CurrentValueChanged+=newEventHandler<SensorReadingEventArgs<CompassReading>>– magneticHeading=e.SensorReading.MagneticHeading;– trueHeading=e.SensorReading.TrueHeading;Dr. SRN Reddy
  32. 32. Proximity• A proximity sensor in a mobile phone detects the presence ofusers’ body and deactivates the display and touch pad of phonewhen it is brought near the face during a call.Applications:Save battery power by switching off the display.• Prevent unintentional touch during call progress.• Proximity Sensor can turn off the screen to avoid accidentaltouch of the screen by ear.• Pause the activity in the middle, when mobile is brought nearto the face/ear and resume previous activity when it broughtaway from the human body.Devices: Lumia 800Dr. SRN Reddy
  33. 33. GPS• GPS sensor detects the location of smartphone.• Work on the triangulation method.• Connection of 3 satellites is required 2Dfix(longitude, latitude) and 4 satellite for 3Dfix(altitude).• Precision: 20-50m, Maximum precision: 10mApplication:Locating the own position on the digital map.Finding the way to desired destination.Navigation by following the GPS navigator.Dr. SRN Reddy
  34. 34. Demo on GPS• This demo gives you the latitude, longitude andaltitude information in text.• This experiment shows the actual geo-location ofthe device.• Major Function:– GeoCoordinateWatcher geoWatcher=newGeoCoordinateWatcher;– PositionChanged+=newEventHandler<GeoPositionChangedEventArgs<GeoCoordinate>>– Latitude=e.Position.Location.Latitude;– Longitude=e.Position.Location.Longitude;– Altitude=e.Position.Location.Altitude;Dr. SRN Reddy
  35. 35. Techtile Sensor• Tactile sensor is a device that is sensitive totouch, force, and pressure.• Capacitive touch screen phones use touchswitch, one of the kinds of tactile sensors.• Touch switches detect the presence offinger or hand as well as stylus.Dr. SRN Reddy
  36. 36. Temperature Sensor• Temperature sensor senses the heat level.• It is mainly for the safety of the devicecomponent.• On exceeding the threshold value for theheating, the sensors automatically warneda user and shutdown the device.Dr. SRN Reddy
  37. 37. Image Sensor• Image sensor converts an optical image into an electricsignal.• Two types of Image Sensor– charge-coupled device (CCD)– metal-oxide-semiconductor active pixel sensor (CMOS APS)• CMOS APS is mostly used in a mobile phone camera tosense images.• CCD is very good for digital imaging and is mainly usedin professional, medical, and scientific applications,where there is need of high quality image.Example-Spice Mobiles has launched S-1200 withprofessional CCD sensorDr. SRN Reddy
  38. 38. Future Sensors• Biometrics SensorsFingerprint recognitionFace recognitionIris pattern recognitionVoice recognitionExample- Motorola Atrix will be the firstphone to come with finger printtechnology.Dr. SRN Reddy
  39. 39. GSM-Bluetooth enabled RemoteMonitoring and Control SystemDr. SRN Reddy
  40. 40. GSM-Bluetooth enabled RemoteMonitoring and Control SystemDr. SRN Reddy
  41. 41. Irrigation system usingGSM-BluetoothDr. SRN Reddy
  42. 42. Implementation of Wireless SensorNetwork by using Mobile DeviceDr. SRN Reddy
  43. 43. HumanSense: Towards context awaresensing, inference and actuation forapplications in Energy and HealthcareDr. SRN Reddy
  44. 44. ConclusionsDr. SRN Reddy, EmailMek can be used as a tool for WNSOn Device Sensor(s) can be adopted forPractical implementations Low cost sensing solutionsHumanSense
  45. 45. References1. Jennifer Yick, Biswanath Mukherjee, Dipak Ghosal, “Wireless sensornetwork survey”, Computer Networks 52 (2008) 2292–23302. I.F. Akyildiz, W. Su*, Y Sankarasubramaniam, E Cayirci , “Wirelesssensor networks: a survey”, Computer Networks 38 (2002) 393–4223. National Programme on Technology Enhanced (NPTEL)Learning Virtual Labs MIT SRN Reddy
  46. 46. Dr. SRN Reddy Email:rammallik@yahoo.comThankingYouRequires Your Feed Back&Support for