From Sensors to Sensor Networks

Transcription

1 From Sensors to Sensor Networks Giuseppe Anastasi Head of Department Dept. of Information Engineering, University of Pisa Website:

2 Introduction This demonstration class is part of my course (graduate) course on Networked Embedded Systems This course is intended to provide the theoretical background and the basic methodologies for developing networked embedded systems and applications. It enables students to design and implement applications, based on networked embedded devices, in several application domains, such as smart cities, smart mobility, smart buildings, smart energy, etc. Wireless Sensor Networks Giuseppe Anastasi 2

3 Overview Sensors Passive Sensors Semi-passive Sensors Sensor Nodes Sensor Platforms Wireless Sensor Networks Networking Issues Wireless Sensor Networks Giuseppe Anastasi 3

4 Sensors

5 Sensors: Classification Passive Sensors RFID Semi-passive Sensors Data loggers Active Sensors Sensor nodes ibeacons Wireless Sensor Networks Giuseppe Anastasi 5

6 Sensors: Classification Temperature Humidity Light intensity Infrared (Presence) Sound (Noise) Accelerometer Compass (direction) Speed Pressure Seismic Chemical Sensors Optical Sensors Pollution CO, CO 2, NO 2, O 3, Benzene PM10, PM2.5, PM1 Smart Meters Power Consumption Energy Consumption Gas Consumption Water Consumption Wireless Sensor Networks Giuseppe Anastasi 6

7 Passive Tags RFID, QR-codes

8 QR codes Quick Response (QR) Code Two dimensional barcode that stores information in black and white dots (data pixels or QR code modules ) Wireless Sensor Networks Giuseppe Anastasi 8

9 QR code generation Many online generators available e.g., URL (Website) Text Vcard Sms Phone Call Geolocation Event WiFi Wireless Sensor Networks Giuseppe Anastasi 9

10 Using RFID Wireless Sensor Networks Giuseppe Anastasi 10

11 Application Areas Supply chain management Baggage/Animal tagging Library information systems Parcel tracking (postal services) Smart cities Access control Ticketing (public transport, parking, etc.) Parking area management Augmented reality... Wireless Sensor Networks Giuseppe Anastasi 11

12 Supply Chair Management

13 Baggage Tagging Wireless Sensor Networks Giuseppe Anastasi 13

14 Animal Tagging

15 Smart Cities Automatic Access/Tolling Wireless Sensor Networks Giuseppe Anastasi 15

16 Smart Cities Augmented Reality Points of interest in the city (touristic point of interest, shops and public places) can be tagged through RFIDs or QR codes Information about the tagged point are made available to the user (tourist, citizen, )

17 Active Tags Beacons

18 Introduction ibeacon is a technology originally developed by Apple ibeacon-compatible hardware transmitters -typically called Beacons - available also for non-apple devices Enablesdevices to perform actions when in close proximity to a Beacon Beacons emit periodic signals Mobile devices understand their location based on the received signal and perform a specific action Wireless Sensor Networks Giuseppe Anastasi 18

19 Basic Idea ibeacon uses Bluetooth Low Energy (BLE) to transmit Advertisement(ADV) messages The ADV message is received by a smartphone and forwarded toaserver(e.g.,onthecloud) The server localizes the device (user) and sends appropriate information to the smartphone Wireless Sensor Networks Giuseppe Anastasi 19

20 How BLE works BLE communication mainly consists in Advertisement (ADV) messages small data packets broadcast at a regular interval by enabled devices via radio waves one-waycommunication Typical parameter values for ibeacons Broadcast interval of 100 ms Broadcast range of up to 100 meters Wireless Sensor Networks Giuseppe Anastasi 20

21 Beacon Advertisement Message UUID (Universal Unique IDentifier) 16 byte string used to differentiate a large group of related Beacons In its canonical form, a UUID is represented by 32 lowercase hexadecimal digits, displayed in five groups separated by hyphens, in the form for a total of 36 characters E.g., ebefd083-70a2-47c e7b5634df524 Major 2-byte string distinguishing a subset of Beacons within the larger group Minor 2-byte string used to identify individual Beacons TxPower Used to determine proximity (distance) from the beacon TX power is defined as the strength of the signal at exactly 1 meter from the device. This has to be calibrated and hardcoded in advance. Devices can then use this as a baseline to give a rough distance estimate. Wireless Sensor Networks Giuseppe Anastasi 21

22 Example Application for locating people within the University of Pisa UUID (Universal Unique IDentifier) Allows to recognize that ADV messages are emitted from Beacons belonging to the University of Pisa Major Identifies ADV messages emitted from Beacons inside a specific building belonging to the University of Pisa (e.g., Building F) Minor Identifies a specific room in that Building (e.g., Room F02) Wireless Sensor Networks Giuseppe Anastasi 22

23 Application Areas Localizationin Buildings Wireless Sensor Networks Giuseppe Anastasi 23

24 Application Areas Retails: coupons delivered via Beacons to customer phone (e.g., special offers) Wireless Sensor Networks Giuseppe Anastasi 24

25 Application Areas Tracking: locate museum artworks, shop products, or cargo containers Wireless Sensor Networks Giuseppe Anastasi 25

26 Applications Areas Indoor Navigation: path discover inside a building and user localization Wireless Sensor Networks Giuseppe Anastasi 26

27 Application Areas SmartTagging: allows to give more information about artworks (also in many languages) Wireless Sensor Networks Giuseppe Anastasi 27

28 Semi-Passive Sensors

29 Semi Passive Sensors Also called data loggers Powered by a battery Measures and stores physical quantities Temperature Humidity Shock Can be attached to goods to track their history Low-cost solution Wireless Sensor Networks Giuseppe Anastasi 29

30 System Architecture Semi-passive Tag Reader Server Data manager Tag management Data retrieval and archival Data visualization Table, plots Wireless Sensor Networks Giuseppe Anastasi 30

31 Application Areas Ice cream, Frozen Products Distribution Temperature monitoring Wine Transport Temperature monitoring Shock tracking Blood Bags Transport Bag Identification Temperature tracking Wireless Sensor Networks Giuseppe Anastasi 31

32 Sensor Nodes

33 Sensor Node Architecture Battery powered devices Usually negligibleshort range Local wireless data processing communication Batteries cannot be changedpower nor recharged consumption Radio is the most and data power storage hungry component 33 Wireless Sensor Networks Giuseppe Anastasi 33

34 ZolertiaFireFly Wireless Sensor Networks Giuseppe Anastasi 34

35 Telos/Tmote Sky Mote Wireless Sensor Networks Giuseppe Anastasi 35

36 Mica Motes Mica2 Mica2dot Sensor Board for Mica light, temperature, accelerometer, magnetometer, microphone, tone detector, 4.5 Khz sounder Wireless Sensor Networks Giuseppe Anastasi 36

37 The TinyOS Operating System Specifically targeted to WSNs Component-based architecture Event-based concurrency Split-phase operation Wireless Sensor Networks Giuseppe Anastasi 37

38 TinyOS development environment nesclanguage extension to the C language definition of interfaces abstraction between definition and composition of components nesccompiler and OS source composition of the component graph (at compilation time) TinyOScomputational model (additional checks) TOSSIM simulator same code runs in actual nodes and simulator flexible models for radio and sensors scripting (Tython), graphical interface (TinyViz) Wireless Sensor Networks Giuseppe Anastasi 38

39 Tutorials on TinyOS Programming Environment TinyOS/TOSSIM Tutorial, TinyOSReference Manual, 2.x/doc/pdf/tinyos-programming.pdf D. Gay et al., "The nesclanguage: A Holistic Approach to Networked Embedded Systems", nescreference Manual, /tinyos-2.0.0beta1/doc/nesc/ref.pdf Wireless Sensor Networks Giuseppe Anastasi 39

40 ContikiOperating System Limited Memory Footprint Event-driven Kernel Portability Many different platform supported TmoteSky, Zolertia, RedBee, etc C Programming Academic and Industrial support Cisco and Atmel are part of the Contikiproject Wireless Sensor Networks Giuseppe Anastasi 40

41 ContikiOperating System Protothread(optional multi-threading) Dynamic Memory Allocation TCP/IP stack (uip) Both IPV4 and IPv6 Power profiling Dynamicloadingand over-the-airprogramming IPsec On-nodedatabase Antelope Coffee file system Wireless Sensor Networks Giuseppe Anastasi 41

42 References A. Dunkels, B. Gronvall, T. Voigt, Contiki-a lightweight and flexible operating system for tiny networked sensors,ieee International Conference on Local Computer Networks, November 2004 Contiki: The Open Source OS for the Internet of Things, Contiki, Processes. Available Online at: Wireless Sensor Networks Giuseppe Anastasi 42

43 Application Areas Environmental Monitoring Temperature, Humidity, Light Intensity, Presence Detection Home security systems Energy efficiency in buildings Location Detection Anti-theft systems Activity Detection Fall detection Athlete monitoring Wireless Sensor Networks Giuseppe Anastasi 43

44 Very Special Sensor Nodes N. Lane, E. Miluzzo, H. Lu, D. Peebles, T. Choudhury, A. Campbell, A Survey of Mobile Phone Sensing, IEEE Communication Magazine, Sept Wireless Sensor Networks Giuseppe Anastasi 44

45 Mobile Phone Sensing Applications Personal Sensing personal tracking Sensing surrounding noise E-health Fall detection, Activity detection Well-being support CenceMe Captures what the user is doing and the information on their surrounding context (collectively called sensing presence) Pushes collected information to social networks EyePhone Allows to activates your mobile phone using only your eyes Wireless Sensor Networks Giuseppe Anastasi 45

46 Participatory Sensing Citizens utilize their mobile phones to send physical sensing information to a data collection center Sensing information can be used for various applications

47 Wireless Sensor Networks From Sensors to Sensor Networks 47

48 Wireless Sensor Networks (WSNs) A large number of tiny sensor nodes deployed over a geographical area Sensor nodes integrate three different capabilities Sensing, computing, and wirelesscommunication Distributed Sensing Infrastructure Sensor nodes sense physical information e.g., temperature, pressure, vibrations, pollution level process the data locally and/or send them to one or more collection points Sink nodes or base stations Wireless Sensor Networks Giuseppe Anastasi 48

49 Architecture: Flat Multi-hop Wireless Sensor Networks Giuseppe Anastasi 49

50 WSN Application Areas Military Applications Environmental Monitoring Precision Agriculture Location/Tracking Industrial applications Health Monitoring Smart Buildings Smart Grid Smart Cities Smart * Wireless Sensor Networks Giuseppe Anastasi 50

51 Military Applications Monitoring friendly forces, equipment, ammunition Battlefield surveillance Reconnaissance of opposite forces sniper detection Targeting Battle damage assessment Attack detection nuclear, biological, chemical

52 Environmental Monitoring Environmental Monitoring Temperature, humidity, pollution level Habitat monitoring monitoring of petrel habitat (Great Duck Island project) Microclimate monitoring Berkeley botanical garden Alert systems fire detection flood detection seismic events Wireless Sensor Networks Giuseppe Anastasi 52

53 Precision Agriculture Temperature Humidity Wind Speed and Direction Soil moisture Wireless Sensor Networks Giuseppe Anastasi 53

54 Location/Tracking Location/Tracking of moving objects Surveillance Presence assessment Animals movements Inventory Control easy localization of items smart management of items Vehicles tracking and detection car theft detection remote monitoring of parking places Wireless Sensor Networks Giuseppe Anastasi 54

55 E-Health Remote monitoring chronicle patients physiological data monitoring elderly people falldetection Hospital monitoring of patients tracking of doctors and attendants drug administration minimize adverse drug events (e.g., allergies to a specific medicine) Wireless Sensor Networks Giuseppe Anastasi 55

56 Smart Factory Distributed Intelligent Sensing System for Factory automation Process Control Real-time monitoring of machinery s health Detection of liquid/gas leakage Remote monitoring of contaminated areas Real time inventory management Wireless Sensor Networks Giuseppe Anastasi 56

57 Smart Buildings Building Automation temperature and air flow control light level control energy efficiency Smart Home Smart appliances sensors and actuators inside appliances easy management of home devices both local and remote Wireless Sensor Networks Giuseppe Anastasi 57

58 Smart Cities Environmental Monitoring Temperature, Noise, Pollution Parks and Gardens Irrigation Parking Area Management Guidance to free Parking Slots Traffic Intensity Monitoring Intelligent traffic management Mobile Environmental Monitoring Better coverage than static monitoring Wireless Sensor Networks Giuseppe Anastasi 58

59 Environmental Monitoring Measured Parameters Temperature Light Noise CO Light intensity can be used for smart lighting If some critical parameters goes above a threshold the system sends an alarm. Wireless Sensor Networks Giuseppe Anastasi 59

60 Mobile Environmental Monitoring Sensors deployed in strategic (fixed) points Crosses, bus stops, homes, schools, Measured Parameters Temperature Humidity Air Pollution (PM10, CO, O3, NO2) Data collection through mobile elements public buses, taxis people Wireless Sensor Networks Giuseppe Anastasi 60

61 Mobile Environmental Monitoring Sensors deployed also on mobile carriers public buses, police cars, taxis people robots Measured Parameters Temperature Humidity Air Pollution (PM10, CO, O3, NO2) Better coverage in a more efficient way Wireless Sensor Networks Giuseppe Anastasi 61

62 Parks and Gardens Irrigation Goal to control and make more efficient the irrigation in certain parks and gardens Sensors Anemometer, pluviometer. Atmospheric pressure, solar radiation, air humidity and temperature sensors. Soil temperature and humidity sensors. Evaluation of water consumption sensor Wireless Sensor Networks Giuseppe Anastasi 62

63 Parking Area Management Parking areas equipped with sensors based on ferromagnetic technology buried under the asphalt in the main parking areas. provided with one transceiver send their parking state (free or occupied), to a gateway through the repeaters. Wireless Sensor Networks Giuseppe Anastasi 63

64 Guidance to Free Parking Slots Data collected from parking sensors are used to guide drivers towards free slots, using an architecture divides in two parts: Panel: Receives information from the Central Station and shows the number of places available in a determined parking zone. CentralStation: It receives, from the Portal Server, all data retrieved by the sensors already deployed to detect parking lots availability.

65 Traffic Intensity Monitoring Sensors buried under the asphalt at the main entrance of the city Measure traffic parameters: Traffic volumes Vehicle Speed Queue length Architecture: Traffic Sensors Repeaters Gateway Wireless Sensor Networks Giuseppe Anastasi 65

66 Readings P. Baronti, P. Pillai, V. Chook, S. Chessa, A. Gotta, Y. Hu, Wireless sensor networks: A survey on the state of the art and the and ZigBee standards, Computer Communications, Vol. 30 (2007), pp Wireless Sensor Networks Giuseppe Anastasi 66

67 Questions From Sensors to Sensor Networks 67