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Wireless sensor networks Overview

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Wireless sensor networks Overview & applications Murat Demirbas ... Network topology (single-hop vs multihop) Coverage (sparse vs dense) Connectivity ... – PowerPoint PPT presentation

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Title: Wireless sensor networks Overview


1
Wireless sensor networks Overview applications
  • Murat Demirbas

2
Wireless sensor networks
  • A sensor node (mote)
  • 8K RAM, 4Mhz processor
  • magnetism, heat, sound, vibration, infrared
  • wireless (radio broadcast) communication up to
    100 feet
  • costs 10 (right now costs 200)?

3
Outline
  • Vision
  • Ubiquitous pervasive proactive computing
  • Design space
  • Challenges
  • Applications
  • Ecology monitoring
  • Precision agriculture
  • Asset management
  • Military surveillance

4
Ubiquitous computing
  • Mark Weiser, PARC, 1991
  • The most profound technologies are those that
    disappear
  • E.g., Writing does not require active attention,
    but the information to be conveyed is ready for
    use at a glance (Periphery / calm technology)?
  • We should not be required to live in computers
    world (OS, virtual reality), computers should
    become invisible and ubiquitous (disappear in
    background) in our physical world
  • Already computers in light switches, thermostats,
    stereos and ovens help to activate the world
  • For such a technology, localization scalability
    are critical
  • Location-aware devices
  • Wireless communication
  • Micro-kernel OS
  • Distributed computing

5
Ubiquitous computing
  • Ubiquitous PC
  • Tab post-it sized e.g., badge, shrink/store
    window on a tab
  • Pad A4/letter sized e.g., scrap computer, edit
    each window on a pad
  • Board yard sized e.g., long-distance meetings,
    bulletin boards
  • Ubiquitous computers to overcome information
    overload
  • There is more information available at our
    fingertips during a walk in the woods than in any
    computer system, yet people find a walk among
    trees relaxing and computers frustrating.
    Machines that fit the human environment, instead
    of forcing humans to enter theirs, will make
    using a computer as refreshing as taking a walk
    in the woods.

6
iComp
Ubiquitous Computing Lab _at_ Furnas 210
7
Proactive computing
  • David Tennenhouse, Intel VP, 2000
  • Moving from human-centered to human-supervised
    computing
  • 150 million PCs versus 8 billion embedded
    computers
  • Only 2 of computers are PCs
  • Getting physical
  • embedded computers
  • Getting real
  • real-time, fast responses from computers need to
    be arbitrated
  • Getting out
  • human above the loop (hidden Markov models)?
  • Reinventing computer science

8
Next century challenges Scalable coordination in
sensor networks
Embedded
Networked
Exploitcollaborative Sensing, action
Control system w/ Small form factor Untethered
nodes
Sensing
Tightly coupled to physical world
  • Distributed local algorithms are needed for
    scalability!

9
New Class of Computing
log (people per computer)?
streaming information to/from physical world
year
10
Technology Push
  • CMOS miniaturization
  • Micro-sensors (MEMS, Materials, Circuits)?
  • acceleration, vibration, gyroscope, tilt,
    magnetic, heat, motion, pressure, temp, light,
    moisture, humidity, barometric
  • chemical (CO, CO2, radon), biological,
    microradar, ...
  • actuators too (mirrors, motors, smart surfaces,
    micro-robots)?
  • Communication
  • short range, low bit-rate, CMOS radios
  • Power
  • batteries remain primary storage, fuel cells 10x
  • solar, vibration, flow

11
Design space
  • Deployment (random vs manual)?
  • Mobility (static vs mobile occasional vs
    continuous active vs passive)?
  • Cost, Size, Resources (brick vs matchbox vs
    grain)?
  • Heterogeneity (homogenous vs heterogeneous)?
  • Communication modality (radio vs light vs
    inductive)?
  • Infrastructure (ad hoc vs infrastructure)?

12
Design space
  • Network topology (single-hop vs multihop)?
  • Coverage (sparse vs dense)?
  • Connectivity (connected vs intermittent vs
    sporadic)?
  • Network size (10 vs 100 vs 1000 vs 10,000 vs
    100,000)?
  • Lifetime (day vs month vs year vs decade)?
  • QOS requirements (none vs real-time)?

13
Challenges in sensor networks
  • Energy constraint
  • Unreliable communication
  • Unreliable sensors
  • Ad hoc deployment
  • Large scale networks
  • Limited computation power
  • Distributed execution
  • Nodes are battery powered
  • Radio broadcast, limited bandwidth, bursty
    traffic
  • False positives
  • Pre-configuration inapplicable
  • Algorithms should scale well
  • Centralized algorithms inapplicable
  • Difficult to debug get it right

14
Assignment 1
  • Present in class one WSN or smartphone
    application
  • Outline the overall function of the WSN or
    smartphone in this application. What is the
    improvement it offers?
  • Specify the design parameters and challenges for
    the proposed system
  • Enumerate the system requirements and challenges
  • Time for your presentation should be around 7
    minutes

15
References for assignment
  1. Great Duck island
  2. Agricultural applications
  3. Analysis of a habitat monitoring application
  4. NASA SensorWeb
  5. Meteorology and Hydrology in Yosemite
  6. Monitoring redwoods
  7. ZebraNet
  8. Virtual fences
  9. Active visitor guidance system
  10. UVA flock control

16
References for assignment
  1. Counter-sniper system
  2. Self-healing land mines
  3. Damage detection in civil structures
  4. Smart-tag based data dissemination
  5. Continuous medical monitoring
  6. Elder care
  7. Aware home
  8. Smart kindergarten
  9. Media production
  10. Factory floor monitoring

17
Assignment 2
  • Summarize one of the following
  • Some computer science issues in ubiquitous
    computing (Weiser)?
  • Proactive computing (Tennenhouse)?
  • Next century challenges (Estrin.)?

18
Outline
  • Vision
  • Ubiquitous pervasive proactive computing
  • Design space
  • Challenges
  • Applications
  • Ecology monitoring
  • Precision agriculture
  • Asset management
  • Military surveillance

19
WSN applications
  • a new "scope" to a scientific endeavor
  • a new approach to an engineering problem
  • a new capability to a computing environment
  • a new form of entertainment
  • a new product opportunity

20
Ecology monitoring
  • Monitoring nesting behavior of birds
  • Great Ducks experiment
  • Detecting forest fires
  • Detecting chemical or biological attacks
  • Monitoring Redwood trees

21
Dense Self-Organized Multihop Network
22
10m
20m
34m
30m
36m
2003, unpublished
23
Precision agriculture
  • Wireless sensor networks can be placed on farm
    lands to monitor temperature, humidity,
    fertilizer and pesticide levels
  • Pesticide and fertilizer can only be applied when
    and where required
  • Pesticide and fertilizer per one acre costs 20
  • Considering 100,000 acres savings of 2 million
    possible

24
Equipment Health Monitoring in Semiconductor Fab
  • Equipment failures in production fabs is very
    costly
  • Predict and perform preemptive maintenance
  • Typical fab has 5,000 vibration sensors
  • Pumps, scrubbers,
  • Electricians collect data by hand few times a
    year
  • Sample 10s kilohertz, high precision, few
    seconds

Fab Equipment
Intranet
Intranet isolation
Ad Hoc Mote Network
Root Node
802.11 Mesh
Mote Vibration Sensors
25
Project ExScal Concept of operation
Put tripwires anywherein deserts, other areas
where physical terrain does not constrain troop
or vehicle movementto detect, classify track
intruders
26
Envisioned ExScal customer application
Convoy protection
Detect anomalous activity along roadside
Hide Site
IED
Border control
Canopy precludes aerial techniques
Gas pipeline
Rain forest mountains water environmental
challenges
27
ExScal summary
  • Application has tight constraints of event
    detection scenarios long life but still low
    latency, high accuracy over large perimeter area
  • Demonstrated in December 2004 in Florida
  • Deployment area 1,260m x 288m
  • 1000 XSMs, the largest WSN
  • 200 XSSs, the largest 802.11b ad hoc network

28
Line in the sand project
  • Thick line allows detection classification as
    intruders enter the protected region also allows
    fine grain intruder localization
  • Grid of thin lines allows bounded uncertainty
    tracking

29
ExScal sample scenarios
  • Intruding person walks through thick line
  • (pir) detection, classification, and fine-grain
    localization
  • Intruding vehicle enters perimeter and crosses
    thick line
  • (acoustic) detection, classification, and
    fine-grain localization
  • Person/ATV traverses through the lines
  • coarse-grain tracking
  • Management operations to control signal chains,
    change parameters, and programs dynamically
    query status and execute commands
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