Smart Dust
1 / 37

Smart Dust - PowerPoint PPT Presentation

  • Updated On :

Smart Dust. Embedded Computing Seminar. Noam Sapiens. Outline. What is smart dust? Characteristics Applications Military Commercial Requirements and restrictions Analysis of smart dust communication General architecture and design What we have today Would like to have

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'Smart Dust' - zeroun

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Slide1 l.jpg

Smart Dust

Embedded Computing Seminar

Noam Sapiens

Slide2 l.jpg


  • What is smart dust?

    • Characteristics

  • Applications

    • Military

    • Commercial

  • Requirements and restrictions

  • Analysis of smart dust communication

    • General architecture and design

  • What we have today

  • Would like to have

  • References

Slide3 l.jpg

What is Smart Dust?

Large scale networks of wireless sensors for various applications

  • The three key capabilities of smart dust are:

    • Sensory capabilities

    • Processing capabilities

    • Communication capabilities

Slide4 l.jpg

Smart dust characteristics

  • A system is made of one or a few base stations (interrogators) and as many smart dust motes as possible or required

  • Ubiquitous – sensors of different types

  • Very task/application oriented design and performance

  • Wireless communication

  • Self-organizing, self-optimizing, self-configuring, self-sustaining.

  • Very small (should be under 1mm3)

  • Low power consumption

  • Easy to deploy

  • Based on current or very near future components

Slide5 l.jpg

Military and Space applications

  • Internal and external spacecraft monitoring

  • Meteorological and seismological monitoring in difficult terrain and environments

  • Land/space communication

  • Chemical/biological environment sensing

  • Meteorological sensing – for better aiming of guns and artillery

  • Autonomous vehicles external aid

Slide6 l.jpg

  • Surveillance

    • Sensors minefield e.g. smart clear tracks on borders

    • Urban engagement (cont. DARPA funding in 2005)

      • Motion detection and enemy numbers

      • Bunker/building mapping

    • Peace time/treaty monitoring

    • Intelligence in hostile areas/behind enemy lines

  • Transportation monitoring and traffic mapping

    • Missile hunting

  • Monitoring soldier vitals and injury

  • Pursuit aid

  • Slide7 l.jpg

    Unmanned pursuit

    Integration of several smart dust experiments

    • Aerial smart dust deployment in the area of interest – ground and air

    • Sensors:

      • Each mote has motion detectors and a small CMOS camera

      • Some motes has GPS

    • Computation:

      • Image processing for target distinction

    • Communication:

      • Ad-hoc networking

      • Relative localization

    Energy tradeoff

    Local coordinate system

    Northwestern university

    UC Berkeley and MLB Co.

    Slide8 l.jpg

    UC Berkley PEG (pursuit-evasion game) experiment

    • 200 sensors network

    • One aerial and three ground unmanned vehicles – pursuers

    • One ground unmanned – evader

    • Pursuers are interrogators of the sensor network deployed

    • Sensor networks roles:

      • Provide complete monitoring of the environment, overcoming the limited sensing range of on board sensors

      • Relay secure information to the pursuers to design and implement an optimal pursue strategy

      • Provide guidance to pursuers, when GPS or other navigation sensors may fail

    UC Berkeley

    Slide9 l.jpg

    Experiment block diagram

    Sensor Network





    Evader motionestimator

    Pursuit Strategy

    Tracking control

    Slide10 l.jpg

    Commercial applications

    • Games and sports

    • Traffic monitoring

    • Inventory control

    • Security

    • Identification and tagging

    • Predictive maintenance

      • Product quality control

      • Industrial facilities

      • Vehicles and systems

      • Appliances

    • Agriculture

    Slide11 l.jpg

    • Building management

      • Energy management

      • Temperature control

      • Lighting control

      • Fire systems

    • Smart office spaces

    • Computer interface

      • Virtual keyboard

      • 3D virtual sculpturing

    • Health, medicine and wellness

    • Handicap aid

    Slide13 l.jpg


    • Perform a specific task according to the application

    • Sense as defined by the task profile (different types of detectors – will not be discussed in this talk)

    • Perform basic computations – digitization, noise filtering, DSP, FFT, image processing, decision making, localization, etc…

    • Establish ad-hoc communication in a physical environment

      • Base station communication and peer to peer

      • Ranges between a few meters (between motes) and over a km (motes to base station)

      • Multi-hop routing (if required)

      • Self configuration and optimization

    Slide14 l.jpg


    • Mote volume will not exceed 1mm3

    • A single mote is probably restricted to few sensory capabilities

    • Energy restrictions

      • Battery ≈ 1J/mm3 (about 10W for a day)

      • Capacitors ≈ 1mJ/mm3

      • Solar cells ≈ 1J/day (sun) or ≈1mJ/day (room light)

      • Vibrations ≈ 0.4-30W (depends on amplitude and frequency)

      • Thermopile ≈ 0.4-2W @ 25-37C

    • Very low cost motes (enable large scale distribution)

    • No science fiction technologies

    Slide15 l.jpg

    Analysis of smart dust communication

    RF vs. Optical

    • RF – radio frequency

      • MHz – hundreds of GHz  1mm – 100s meters wavelength

      • Technologies:

        • Bluetooth

        • Cell phones (GSM, CDMA, etc.)

        • RFID

    • Optical

      • 100THz – 1PHz  0.3 - 1.6 wavelength

      • Lasers and LEDs

    Slide16 l.jpg


    • Pros

      • Well developed technologies

      • Multiplexing techniques: TDMA, FDMA, CDMA.

      • Does not require line of sight

      • Not much affected by the environment

    • Cons

      • Antenna size (has to be at least ¼ of the wavelength)

      • Complex circuitry (modulation/demodulation, bandpass filters, etc.)

      • Energy consumption (approx. 100nJ/bit)

    Slide17 l.jpg


    • Pros

      • Low energy consumption (<1nJ/bit)

      • High data rates

      • Small aperture, very directional (localization)

      • Spatial division multiplexing

    • Cons

      • Very directional

      • Line of sight

      • Atmospheric turbulence, weather and environmental conditions dependent

    Slide19 l.jpg

    MEMs controlled corner cube retro-reflector

    • Perfectly aligned corner cube reflects light at the exact same direction of incidence

    • MEMs control of one of the corner cube side’s alignment enables modulation

    • Energy consumption of about 1pJ/bit @ 1kb/sec

    • Range up to 1km

    UC Berkeley

    Slide20 l.jpg

    Smart dust active transmitter

    • Incorporates a laser, lens and a MEM steering mirror

    • 1mrad transmission

    • Data rate of approx. 5Mb/sec

    • Energy consumption depends on distance and detector size

    1mW at 1mrad laser is 40 times brighter than 100W light bulb

    Slide21 l.jpg

    SEM view

    Laser diode

    MEM mirror


    Optical view

    UC Berkeley

    Slide22 l.jpg

    Experimental results

    • Beam steering at kHz rates

    • Steering in approx 1str ≈ 60X 60

    5.2 km Berkeley Marina

    15.3 km Coit Tower

    300m Link test

    14W laser

    8mW laser

    Slide23 l.jpg

    The base station

    • Hand held

      • Binoculars

      • Palm

      • Cell phone

    • Laptop computer

    • Command center

    • Unmanned vehicle (land, sea, air)

    • Autonomous systems

    Slide24 l.jpg

    Base station architecture






    Beam Splitter



    Smart dust





    Optical interrogation – principles of operation

    For example:FOV=17mX17mCMOS is 256X256, 432pixelsRange = 2kmfLens=20cmSpatial resolution = 6.6cm2

    Space division multiplexing

    Slide25 l.jpg

    Airborne base station example

    UC Berkeley and MLB Co.

    Slide26 l.jpg

    Challenges for mobile networking for smart dust

    • Line of sight requirement

    • Link directionality

    • Parallel readout and cross talk

    • Trade-offs

    • Revisit rates

    Slide27 l.jpg

    Line of sight requirement

    • Optical communication requires photons from the transmitter reach the receiver – photons travel in straight lines

    • Line of sight is not the only way of making the photons arrive at a desired location:

      • Diffuse reflections – low energy, wide spread (the entire FOV) and low contrast with the environment (especially with interrogating beam)

      • Non fixed smart dust systems - line of sight could be achieved intermittently

      • Ad hoc multi-hop routing

    Cannot work with passive communication, very small SNR





    Slide28 l.jpg

    Link directionality


    • Motes are unaware of neighbors location

    • Base station can disseminate location information to motes

    Passive links

    • A corner cube retro-reflector angle of acceptance is 10-20

      • Placing multiple corner cubes

      • Placing the corner cube and the receiver on a MEM mount – signal maximization

      • Increase mote density – high probability for communication with at least some motes in the area of interest

    Slide29 l.jpg

    Active links

    • Mote receiver is omnidirectional within a hemisphere

      • Enables mote attention without aiming

      • No source identification

    • Making the receiver directional (by adding a lens) and connecting its directionality to the transmitter will enable communication automatically to the source

      • Requires aiming

      • Solved by increasing the density of motes

    • In a static system, identification could be saved in mote memory

    • Difference between receiver and transmitter angular spreads leads to non-reciprocal linking

    Slide30 l.jpg

    Parallel readout and crosstalk

    • The network architecture of smart dust enables space division multiplexing in the base station

    • There are as many channels as there are pixels in the CMOS camera of the base station

    • If the interrogating beam is divergent enough several motes could be ready simultaneously

    • A base station will not distinguish between motes in the same space equivalent pixel

    • TDMA could be incorporated in the architecture – modulation of the interrogating beam could establish a clock for synchronization

    • Demand access method (as in cellular and satellite networks) could be implemented as well – a mote sends an active short pulse to the base station will receive attention by the interrogation beam of the base station

    Slide31 l.jpg


    SNR – signal to noise ratio, governs the probability for bit error

    Pt – average transmitter power

    A – receiver area

    N0 – receiver inherent noise

    B – bit rate

    r – the distance between the transmitter and receiver

     - beam divergence

    Slide32 l.jpg

    Revisit rate

    • Revisit rate should be application specific

    • Use of AI – learning system

      • Frequent revisits to areas in which changes happen most rapidly

    • Could be based on human judgment or automatic

    • Could be based on the demand access method

    Slide33 l.jpg

    What we have today

    • Different markets

      • Airborne systems – monitoring, camera stability, unmanned…

      • Marine

      • Land vehicles

      • Environment

    • Mote price ~100$

    • Kit price (8-12 motes) ~ 2000$

    • Building management

    • Industrial monitoring

    • Security

    Slide34 l.jpg

    Would like to have capabilities (a partial list)

    • Miniaturization of available smart dust and extreme price reduction

    • Possibility of optical pre-processing and optical circuits

    • Incorporate the concept of smart dust societies – integration of different types of smart dust

      • Requires more robust network protocols

      • Requires better definition of mote task

      • Enables complex systems easy distribution

      • Enables smaller and cheaper motes

    Slide35 l.jpg

    • Multi wavelength VCSEL arrays will enable smart dust WDM capabilities

    • Beam quality control (divergence) – for easier scanning

    • Electro-optic instead of MEMs

      • Higher bit rate (will be required for very large networks)

      • Lower energy (about 20pJ/bit @ 10Mb/sec)

    • Active smart dust – interfaces, robotic capabilities and motion

    Rocket chip


    Slide36 l.jpg

    References capabilities

    • JM Kahn, RH Katz & KSJ Pister, “Emerging challenges: mobile networking for smart dust”, J. of Comm. and Net. 2 pp.188-196 (2000)

    • Y Song, “Optical Communication Systems for Smart Dust”, M.Sc. Thesis, Virginia polytechnic institute and state university, 2002

    • The following urls: