WSN Wireless Sensor Networks and Applications - PowerPoint PPT Presentation

Loading...

PPT – WSN Wireless Sensor Networks and Applications PowerPoint presentation | free to view - id: 7700f-NGU1Z



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

WSN Wireless Sensor Networks and Applications

Description:

WSN Wireless Sensor Networks and Applications – PowerPoint PPT presentation

Number of Views:15599
Avg rating:5.0/5.0
Slides: 114
Provided by: occs2
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: WSN Wireless Sensor Networks and Applications


1
WSNWireless Sensor Networksand Applications
Dwight Borses Member of the Technical
Staff National Semiconductor, Irvine, CA
1
2
Wireless Sensor NetworksDescription
  • Consists of a large number of sensor nodes
  • Nodes are extremely small, low-cost, low-power
  • Nodes communicate over RF or lasers
  • Network collect environmental data which they
    forward to infrastructure processing nodes
  • Acoustics
  • Light
  • Humidity
  • Temperature
  • Imaging
  • Seismic, etc

3
Deployment and Applications
  • WSNs may monitor or control
  • Consist of thousands of nodes deployed in very
    high density
  • homes, buildings,
  • highways, cities,
  • infrastructures
  • Applications range from
  • Monitoring/warning of natural disasters effects
  • Protecting homeland security
  • Conducting military surveillance

4
Making Systems Long-lived
  • Consider energy the scarce system resource
  • Minimize communication (esp. over long distances)
  • Computation costs much less, so
  • In-network processing aggregation, summarization
  • Adaptivity at fine and coarse granularity
  • Maximize lifetime of system, not individual nodes
  • Exploit redundancy design for low duty-cycle
    operation
  • Exploit non-uniformities when you have them
  • Tiered architecture

5
Making Systems Long-lived
  • Robustness to dynamic conditions
  • Make system self-configuring and
    self-reconfiguring
  • Avoid manual configuration
  • Empirical adaptation (measure and act)
  • Localized algorithms prevent single points of
    failure
  • Helps to isolate scope of faults
  • Also crucial for scaling purposes

6
Possible Applications for WSN
Environmental Monitoring
7
Mars WSN
Scott Burleigh JPL / Cal Tech 19 Jan 2004
8
UCLA Wildlife Habitat Monitoring
  • Instrumented with cameras and microphones
  • Task is to detect presence of bird and photograph
    it
  • One approach
  • Use microphones to detect birdcall and estimate
    location
  • Then, select a camera that has the bird in field
    of view

Species Detection and Tracking
9
Integrated Sensing, Computing, Communication
  • WSNs are driven by
  • Technological convergence of MEMS
  • Microelectromechanical sensors
  • Microelectronics
  • Signal processing
  • Communication
  • Enabled by
  • Algorithms, network protocols, software, for
    applications conformance (mostly still under
    development)
  • Power management technology for operational
    endurance
  • Resulting in
  • Useful, long-lasting, reliable, survivable,
    programmable systems

10
Sensor Technology
10
11
Microsensor Network Technology
  • Significant impact on 21 Century lives
  • Range in size from mm2 to in2
  • Multiple miniaturized sensors for light,
    temperature, humidity, acoustics, imaging, etc
  • Considerable processing power
  • Positional ability from GPS or local methods
  • Short range RF and/or optical communication
  • Cheap and Smart
  • Deployable in small or very large quantities
  • Instrument homes, highways, buildings, bodies,
    cities, infrastructures
  • Monitoring and control for security and defense

12
Nanotechnology
  • Nanosensors
  • Extremely small devices with dimensions on the
    order of 10-9 m. (one billionth of a meter)
  • Capable of detecting and responding to physical
    stimuli
  • Characterized as nanostructured particles,
    nanoparticles, and nanodevices
  • Future products
  • Based on Nano Electro-Mechanical Systems (NEMS)
  • Molecular switches currently under development

13
J. Storrs Halls Utility FogA Swarm of Nanobot
Foglets
Foglets can take the shape of virtually anything,
and change shape on the fly.
14
Nanosensors Myth or Reality
  • Garnered attention of scientists, venture
    capitalists, government officials, industry
    analysts
  • Revenues expect to reach 200B by 2006
  • Future depends on expenditures and application
    emergence
  • Industry Alliance
  • NanoBusiness Alliance (www.nanobusiness.org)
  • Extensive library of white papers

15
NanotechnologyThe Challenges
  • Applications interface
  • Between nanoscale devices and real world
    microsystems and macrosystems
  • Funding to develop and introduce competitive
    products into the marketplace
  • US Government spent 2B on nanotechnology
    world-wide over past two years
  • Over 1,200 nanotechnology start-up companies
    exist in the United States
  • 250-350 nanotechnology start-up companies exist
    in the rest of the world

16
Nanosize MachinesNASA Ames Research Center
17
Emerging Sensor Network Example Automobiles
  • Stringent safety, reliability, and cost
    requirements drive sensor technology
  • TREAD Transportation Recall Enhancement,
    Accountability, and Documentation Act
  • Tire pressure monitoring
  • Electronic Stability Systems
  • Vehicle Dynamic control (VDC)
  • Airbag Control
  • Antilock Breaking Systems (ABS)

18
Indirect Tire Monitoring
  • E.g., Infineon Technologies AG)
  • Wired connectivity, 2-wire with current interface
  • Least costly (lt15 per wheel)
  • Least precise
  • Utilize existing ABS wheel speed sensors
  • Underinflated tires increases wheel speed
  • Overinflated tire decreases wheel speed
  • Separate sensor and uP, packaged together

19
Direct Tire Monitoring
  • E.g., Motorola Sensor Products
  • Wireless connectivity
  • Most accurate and reliable
  • Most expensive implementation 65 -80 per wheel
  • Full system solution solution includes
    microcontroller, radio frequency IC, development
    software

20
VDC and ABS
  • Hall effect sensors are replacing variable
    reluctance (VR) wheel-speed sensors
  • VR sensing mature and less costly
  • Hall effect more costly but more benefits
  • Sensors integrate signal conditioning
  • Provide stable output independent of speed, down
    to DC
  • Same sensor types are being applied to numerous
    other automotive applications to measure speed,
    position, and angle

21
Advance Chassis ControlMotorola Automotive
Volvo
Volvo S60 R and V70 R Driver selects Comfort,
Sport, or Advance Sport Setting
40 MHz uC continuously samples road-speed
information, position information for each wheel,
and horizontal and lateral acceleration, updating
damper setting every 2 mSec.
Developed by Ohlins Racings and Monroe
22
Vehicle and Driver Safety Systems
  • Imaging
  • Real time for periphery monitoring
  • Rear, side view systems
  • Lane departure warning
  • Automotive blackbox
  • Video
  • Audio
  • Vehicle dynamics
  • Collision detection and reporting

23
Vehicle and Driver Safety Systems
  • Imaging Sensors
  • Driver quality monitoring
  • Front and rear view

24
Vehicle and Driver Safety Systems
  • Imaging Sensors
  • Machine vision
  • Real time
  • Lane departure safety warning

25
Vehicle and Driver Security Systems
  • Remote vehicle monitoring
  • OnStar
  • Vehicle status reporting
  • Remote control of vehicle systems
  • LoJack
  • Location determination and reporting

26
Key Technical ChallengesWSN Networking
  • Efficient networking methods
  • Enable rapid, ad hoc networking of any number of
    devices
  • Support mobile or fixed location devices
  • Methods for network programmability
  • Collaborative Signal and information processing
    within the network
  • Detect, classify, track events and patterns of
    events occurring in geographic area

27
Key Technical ChallengesWSN Database Management
  • Design of distributed microdatabases of
    information about events of interest
  • Over spatio-temporal interval
  • Stored in devices and queried by multiple users
  • Methods for security and information assurance
    within the network
  • Intrusion detection
  • Intrusion tolerance
  • Survivable operation in event of failure and
    compromise

28
Key Technical ChallengesWSN Operational Lifetime
  • Effective hardware design for reliability and
    availability
  • Effective power management efficiency for maximum
    endurance and network operational lifetime

29
Re-creating the Internet
  • Sun Microsystems
  • The network is the computer
  • Intel and MIT
  • Extend the internet downward into a
    fine-grained, ubiquitous network of sensors and
    actuators
  • Two-Pronged Approach to Retrofit the Internet

30
Extending the Internet Above and Below
  • PlanetLab
  • Extend the Internet upward with an overlay
    network
  • Re-create the Internet in the form of a
    distributed, planet-wide parallel processor
  • Fine-grained Internet
  • Extend the Internet downward
  • Nodes consist of miniature hardware (Motes)
  • Distributed throughout the natural and urban
    environment
  • Based on adaptations to RFID technology

31
PlanetLab
  • 160 computers
  • 65 sites
  • 16 countries
  • 70 research projects
  • Linux as the operating system
  • Microsoft OS dominance threatened???
  • Initial push for 1,000 nodes connected to all
    Internet regions and long-haul backbones.

32
A Dispersed Low-Cost Wireless Sensor and Actuator
Network
  • 300 companies have designed Motes (volumes gt 5K
    pieces
  • OS TinyOS
  • DB Tiny DB
  • Intel sponsors projects
  • Example Great Duck Island, off the coast of
    Maine
  • Network of visual and audio sensors monitors
    island bird population in real-time

33
Intels Wireless Vineyard
34
Background Sensor Networks
  • Array of Sensor Probes (10-1000)
  • Collect In-Situ Data about Environment
  • Wireless Links
  • Relay Data
  • Collaboration

35
Distributing Queries Over Low Power Sensor
Networks Sam Madden, Robert Szewczyk,
Michael Franklin, Wei Hong, Joe Hellerstein, and
David Culler
Focus Hierarchical Aggregation
Wireless Sensor Networks
Palm DevicesLinux
  • Aggregation natural in sensornets
  • The big picture typically interesting
  • Aggregation can smooth noise and loss
  • UDAs to do signal processing
  • Provides data reduction
  • Power/Network Reduction in-network aggregation
  • Hierarchical version of parallel aggregation
  • Tricky design space
  • Metrics power cost and answer quality
  • Variables topology-selection, value-routing
    scheme, other tricks
  • Dynamic environment requires adaptive schemes

Smart Dust MotesTinyOS
  • A spectrum of devices
  • Varying degrees of power and network constraints
  • This demo Mica and TinyOS
  • Focus on many/tiny
  • Toward MEMS Smart Dust
  • Off-the-shelf HW for now Berkeley Mica Mote
  • Wireless, single-ported, ad-hoc network
  • Spanning-tree communication through root

Performance in Tiny SensorNets
A Query Language for Sensors
Aggregation and NW Optimization
  • Power consumption
  • Communication gtgt Computation
  • METRIC radio wake time
  • Send gt Receive
  • METRIC messages generated
  • Bandwidth Constraints
  • Internal gtgt External
  • Volume gtgt surface area
  • Result Quality
  • Noisy sensors
  • Discrete sampling of continuous phenomena
  • Lossy communication channel
  • Continuous queries with streaming, periodic
    results
  • UDAs and UDFs
  • Currently compiled-in
  • Mote Virtual Machine (Mate) under development
  • Periodic nature allows for
  • Scheduling of communication and sleep
  • Simple semantics for combining multi-hop readings
  • Clearly other alternatives here
  • E.g. sequence/timeseries/temporal query languages
  • An expanded taxonomy of aggregates
  • State
  • Duplicate sensitivity
  • Montonicity
  • Exemplary vs. Summary
  • Effects on
  • Value Routing
  • Snooping and Suppression
  • Caching and Presumption
  • Hypothesis Testing
  • Collapsing of the NW and QP layers!

SELECT ltaggsgt, ltattrsgt WHERE
ltpredsgtGROUP BY ltexprgt HAVING ltpredsgtEPOCH
DURATION ltconstantgt
TinyDB Software On Motes
  • 4200 lines of C Code
  • Runs on Mica Motes with light and temperature
    sensors, magnetometers and accelerometers
  • 4Mhz Atmel Processor
  • 4KB RAM, 40kBit radio, 512K EEPROM, 128K Flash
  • Ad-hoc queries
  • Java UI
  • Split-pane display
  • Topology visualization
  • Applications
  • Environmental, military
  • NW Monitoring!

36
(No Transcript)
37
Modern Sensor Nodes
Wireless Integrated Network Sensors (WINS)
38
Node Hardware
1Kbps - 1Mbps, 3-100 Meters, Lossy Transmissions
128KB-1MB Limited Storage
Transceiver
Embedded Processor
Memory
8-bit, 10 MHz Slow Computations
Sensors
Battery
66 of Total Cost Requires Supervision
Limited Lifetime
39
Desired Operations
  • Immediate
  • Transmit ID ? Mote health report
  • Transmit current readings from one/all sensors
  • Send logged data for sensor X
  • Calibrate real-time clock
  • Reconfiguration
  • Start logging data from sensor X sampled every T
    seconds
  • Set logging threshold and filter coefficients
  • Set ScatterCast interval to T seconds
  • Set your wakeup interval to T seconds

40
Networking
  • Multi-Hop Routing
  • Limited Transmission Range
  • Routing Issues
  • Irregular Topologies Data Transport Aware
  • Power Aware Fault Tolerant

41
Scientific Value
  • Multiple Data Points Time and Position
  • Temporal Synchronization
  • Hierarchical Schemes
  • Position Estimation
  • Digital Ranging
  • Offline Triangulation

42
Sensor Network Initialization
43
Simulator Node Layers
Sensor Triggers
Application
Data Fusion Clock Synchronization
Routing
Clustering Algorithms, Reliable Routing
Link
Medium Access, Commercial Chipsets
Node
44
Example Election Clustering
  • Distributed Algorithm
  • Nodes Elect Leaders, Form Groups
  • Limited Knowledge

45
Example Fixed Leader Clustering
  • Predefined Cluster Leaders
  • Find Nearest Leader
  • Mutiny if Leader too Far Away

Sleep
Undecided
Leader
Member
46
Sunrise Synchronization
  • Use Sunrise as Synchronization Point
  • Earlier Risers are More Eastern
  • Smooth with Cluster Values, Neighbor Clusters
  • Gross Estimate of East-West Dimension

47
Wireless Sensor Nodes Constraints
  • Low Data Rates ltlt 10 kbps
  • Self-configuring, maintenance-free and robust
  • Aggressive networking protocol stack
  • Redundancy in deployment
  • Low cost lt 1
  • Small size lt 1 cm3
  • Low power/energy
  • Long lifetime of product requires
    energy-scavenging
  • Plausible scavenging level lt 100 ?W

48
PicoNetwork Specifications
  • Density of nodes 1 node every 1 to 20 m2.
  • Radio range 3 to 10 m
  • Average bit rate per node 100-500 bps
  • Peak bit rate per node 10 kbps
  • Very low mobility of nodes
  • Loose QoS requirements
  • Sensor data is redundant, so reliability is not
    required
  • Most data is delay insensitive

49
Protocol Stack
  • Issues at the network layer
  • Addressing
  • Addressing will be class based
  • ltlocation, node type, sub typegt
  • Symbolic addressing may be supported
  • Routing
  • Should route packets to the destination
  • Given
  • Destination location
  • Position of self
  • Position of the neighbors

50
Data Link Layer
  • Maintains position of self and neighbors
  • Main radio receiver
  • Runs at 10 kbps
  • Locally unique channel, globally reused
  • Wake-up radio receiver
  • Global broadcast channel
  • Used to wake-up neighboring nodes

51
Routing Protocol Characteristics
  • Ensure network survivability
  • Low energy (communication and computation)
  • Tolerant and robust to topology changes
  • Scalable with the number of nodes
  • Light weight

52
Network Survivability
Network survivability is application-dependent
coverage may also be an issue
53
Proactive vs. Reactive Routing
  • Proactive routing maintains routes to every other
    node in the network
  • Regular routing updates impose large overhead
  • Suitable for high traffic networks
  • Reactive routing maintains routes to only those
    nodes which are needed
  • Cost of finding routes is expensive since
    flooding is involved
  • Good for low/medium traffic networks

54
Traditional Reactive Protocols
Destination
Source
  • Finds the best route and then always uses that!
  • But that is NOT the best solution!
  • Energy depletion in certain nodes
  • Creation of hotspots in the network

55
Directed Diffusion
Setting up gradients
Source
Destination
  • Destination initiated
  • Multiple paths are kept alive


56
Energy Aware Routing
  • Destination initiated routing
  • Do a directional flooding to determine various
    routes (based on location)
  • Collect energy metrics along the way
  • Every route has a probability of being chosen
  • Probability ? 1/energy cost
  • The choice of path is made locally at every node
    for every packet

57
Setup Phase
Directional flooding
Sensor
Controller
58
Data Communication Phase
Each node makes a local decision
59
Whats The Advantage?
  • Spread traffic over different paths keep paths
    alive without redundancy
  • Mitigates the problem of hot-spots in the network
  • Has built in tolerance to nodes moving out of
    range or dying
  • Continuously check different paths

60
Network Lifetime
  • Nodes have fixed initial energy 150 mJ
  • Measure the network lifetime until the first node
    dies out
  • Diffusion 150 minutes
  • Energy Aware Routing 216 minutes

44 increase in network lifetime
61
Findings on Routing
  • Mitigation of hot-spots is crucial in energy
    constrained networks
  • Simulation results suggest that probabilistic
    routing increases time until the first node dies
    out
  • Analysis is required to show the theoretical
    optimum
  • Network performance is application dependent
    need to clearly identify metrics of interest

62
Mote Development
62
63
Smart Dust
  • COTS Dust commercial-off-the-shelf components
  • Daft Dust low power circuit techniques
  • Clever Dust low energy microcontroller
  • Sapient Dust novel microcontroller

64
COTS Dust
  • Create a network of sensors
  • Explore system design issues
  • Provide a platform to test Dust components
  • Use off the shelf components

65
COTS Dust - RF Motes
  • Atmel Microprocessor
  • RF Monolithics transceiver
  • 916MHz, 20m range, 4800 bps
  • 1 week fully active, 2 yr _at_1

66
COTS Dust - Optical Motes
  • Laser mote
  • 650nm laser pointer
  • 2 day life full duty
  • CCR mote
  • 4 corner cubes
  • 40 hemisphere

67
Smart Dust
  • Distributed sensor networks
  • Sensor nodes
  • Autonomous
  • 1mm3
  • Interfaces
  • Power
  • battery, solar, cap.
  • Communication
  • LOS Optical (CCR, Laser)
  • Challenges
  • 1 Joule
  • 1 kilometer

68
Smart Dust Goals
  • Autonomous sensor node (mote) in 1mm3
  • Multiple sensors temperature, light, vibration,
    etc.
  • Thousands of motes
  • Demonstrate useful/complex integration in 1mm3

0.25µm CMOS double poly, 5 metals
69
Motivation
  • CoolRisc 81 µcont. standby power 100nW
  • Þ 1J consumed in lt 28 hours
  • 1µW/mm2 light incident on 1mm2 solar cell
  • Goal Reduce static consumption and minimize
    energy/instruction

70
Research Goals
  • System integration and miniaturization
  • Low-energy microcontroller
  • lt 0.1pJ/instruction/bit
  • lt 10nW leakage
  • 1-100kHz operation
  • Novel microcontroller architecture
  • Reconfigurable datapath components
  • Data-driven operation
  • Element-level power cycling

71
System Energy Budget Items
  • Solar Cell
  • Full sun 0.1mW/mm2, 1J/day/mm2
  • Indoor 0.1-10µW/mm2, 1-100mJ/day/mm2
  • Photodiode Receiver 0.1nJ/bit (projected by
    Leibowitz)
  • Accelerometer 0.5nJ/measurement (literature)
  • ADC 1nJ/sample (goal for Markow)
  • Transmitter 13nJ/bit (measured on charge pump)
  • Controller lt 2.8pJ/instruction/bit (CoolRISC 81)

72
Smart Dust Components
73
Dust Components
  • Thick film battery 1mm3, 1 J storage
  • Power capacitor 0.25mm3, 1uJ storage
  • Solar cell 1x1x0.1mm3, 0.1mW generation
  • CMOS controller 1x1x0.1mm3
  • Sensor 0.5x0.5x0.1mm3
  • Passive CCR communications
  • 0.5x0.5x0.1mm3, 10kbps, 1uW, 1km
  • Active laser communications
  • 1x0.5x0.1mm3, 1Mbps, 10mW, 10km
  • Total volume lt 1.5 mm3
  • Total mass lt 5 mgm

74
High Quality CMOS Mirror
  • CMP aluminum surface
  • Single crystal silicon mirror body for flatness
  • Torsional hinges
  • Multi-layer staggered torsional electrostatic
    combdrive (MSTEC) actuation
  • Reduced actuation voltage
  • More complex actuation mechanism possible

75
Optical CommunicationCorner Cube Reflector (CCR)
Imager
Laser
Courtesy of Victor Hsu
76
Optical CommunicationCorner Cube Reflector (CCR)
Imager
Laser
  • Capacitive actuation
  • 118bps w/ 8V actuation
  • 670 pJ/bit
  • 150m demonstrated range

Courtesy of Victor Hsu
77
CCR Interogator
78
1 Mbps CMOS Imaging Receiver
79
Signal Conversion
80
Turbulent Channel
81
Optical Communication vs. RF
  • Pro
  • Low power
  • Small aperture
  • Spatial division multiplexing
  • High data rates
  • LPI/LPD
  • Baseband coding
  • Con
  • Line of sight
  • Atmospheric turbulence

Scintillation
Low probability of intercept / Low probability of
detection
82
Optical Communication Advantages
  • Large antenna gain
  • Small radiator
  • Spatial division multiple access (SDMA)
  • Received power µ1/d2
  • RF received power µ1/d2?7
  • Output efficiency
  • Optical
  • Laser slope efficiency
  • Poverhead 1uW-100mW
  • RF
  • GMSK slope efficiency 50
  • Poverhead 1-100mW

83
Dust Delivery
  • Floaters
  • Autorotators
  • solar cells
  • Rockets
  • thermopiles
  • MAVs

84
Airborne Dust
Maple seed solar cell MEMS/Hexsil/SOI
1-5 cm
Controlled auto-rotator MEMS/Hexsil/SOI
Rocket dust MEMS/Hexsil/SOI
85
Micro Air Vehicle (MAV) Delivery
  • 60 mph
  • 18 min
  • 1 mi comm

Built by MLB Co.
86
Project Status
300µm
Courtesy of Victor Hsu
360µm
  • 80 mm3
  • Circuits 0.25 µm CMOS
  • CCR Cronos MUMPS

87
Project StatusSecond Attempt
CCR
Photodiode
Charge Pump
  • Compact circuit design with photocell, reset
    circuit, and electronics.
  • Reduced size to 300µm x 360µm
  • Digital circuits placed under ground pad to
    reduce area.

Vdd
GND/ LFSR
Reset
88
Project StatusFirst and Second Attempts
  • Integrated electronics and CCR on 5mm 1.4V
    battery
  • Verified photocell and CCR operation but
    electronics were faulty due to charge
    accumulation during fabrication

89
Daft Dust System Architecture
Corner Cube Reflector
  • Autonomous platform to demonstrate basic concepts
  • Optical signal receiving
  • Data processing
  • Synchronous information transmission

90
Packaging
Daft Dust package by Lixia Zhou
91
Daft Dust Device
  • 63 mm3
  • Circuits 0.25 µm CMOS
  • digital circuits underneath ground pad
  • metal shields to prevent photogenerated carriers

92
Demonstrated Functionality
R
gain
Clock Signal
Laser Input
A
v
i
photo
Transimpedance Amplifier
20 bit Shift Register w/Training Sequence
LFSR Pseudorandom Generator
Charge Pump
- 2 mm2 solar cell power source
93
Clever Dust Processor Features
  • Laser reprogrammable
  • Transmit automatically in case receiver doesnt
    work
  • Asynchronous transceiver architecture
  • Probe chip to determine baud rate
  • May have programmable baud clock
  • Store and transmit (fake) sensor data
  • Basic processing capabilities
  • Princeton architecture

94
Novel Architecture Design Method
  • Minimize energy through architecture
  • Minimum energy Þ ASIC implementation
  • Dynamic reconfigurability
  • How much is necessary tradeoff with ASIC
    mapping
  • Energy driven operation modes
  • Typical application scenario to guide design

95
Sapient Dust Top-Level Diagram
Sensors
Timer Bank
Setup Memory
Power Supply
ADC
Receiver Front End
Reconfigurable Datapath Components
CCR Driver
Real Time Clock
SRAM
96
Power Cycling
  • 8 bit comparator
  • 2.9nW powered up
  • 6.4pW turned off
  • Idle gt 33ms, turn off

97
Comparison
  • Sapient energy estimations from Epic Powermill at
    1kHz

98
Findings
  • Custom circuits 9x better than standard cell
  • Low-energy microcontroller
  • Feature laser reprogrammable
  • Techniques execution sequencing and
    element-level clock gating
  • Novel microcontroller architecture
  • Reconfigurable datapath
  • Data-driven operation
  • Extreme power cycling
  • 28x better than CoolRisc

99
Power and Energy
  • Sources
  • Solar cells
  • Thermopiles
  • Storage
  • Batteries 1 J/mm3
  • Capacitors 1 mJ/mm3
  • Usage
  • Digital control nW
  • Analog circuitry nJ/sample
  • Communication nJ/bit

100
UWB Radar
  • Ultra Wideband RF Sensors
  • UWB radar emission are typically between 100MHz
    and 3 GHz
  • Fractional bandwidth is very large 0.2
  • Exceptional resolution
  • Ability to penetrate common materials
  • Walls
  • Light foliage
  • Detect intrusion by change in impulse response of
    the environment rather than on Doppler dependency
    as in traditional radar systems

101
UWB Sensors
  • Light weight, battery-powered imaging
    interferometric UWB radars are being utilized by
    police to improve situational awareness during
    hostage and forced entry situations
  • The future hold promising potential for UWB based
    sensors providing exceptional intrusion detection
    for protection of critical infrastructures from
    terrorist activities

102
WSN Summary
102
103
Sensor Networks Applications
  • Military applications
  • Environmental applications
  • Health applications
  • Home applications
  • Other commercial applications

104
Military Applications
  • Monitoring friendly forces, equipment and
    ammunition.
  • Battlefield surveillance
  • Reconnaissance of opposing forces and terrain
  • Targeting
  • Battle damage assessment
  • Nuclear, biological and chemical attack detection
    and reconnaissance.

105
Environmental Applications
  • Forest fire detection
  • Biocomplexity mapping of the environment
  • Flood detection
  • Precision agriculture

106
Health Applications
  • Telemonitoring of human physiological data
  • Tracking and monitoring doctors and patients
    inside a hospital
  • Drug administration in hospitals

107
Home Applications
  • Home automation
  • Smart environment
  • Home security

108
Other Commercial Applications
  • Environmental control in office buildings
  • Interactive museums
  • Detecting and monitoring car thefts
  • Managing inventory control
  • Vehicle tracking and detection

109
Factors influencing sensor network design
  • Fault tolerance
  • Scalability
  • Production costs
  • Hardware constraints
  • Sensor network topology
  • Environment
  • Transmission media
  • Power consumption

110
Conclusion
  • Rapid advances in WSN technology promises
    ubiquitous deployment in the years ahead
  • Significant issues in regard to Orwellian
    consequences of the technology

111
Delay Tolerant NetworksWSN References
Thanks, Kwang!
112
(No Transcript)
113
Thank you!
113
About PowerShow.com