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Sensing and Actuation: End-to-end systems design for safety critical applications. Dr. Elena Gaura, Reader in Pervasive Computing Director of Cogent Computing Applied Research Centre, Coventry University, [email protected] Dr. James Brusey, Senior Lecturer, [email protected]

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Gaura brusey

Sensing and Actuation:End-to-end systems design for safety critical applications

Dr. Elena Gaura, Reader in Pervasive Computing

Director of Cogent Computing Applied Research Centre, Coventry University,

[email protected]

Dr. James Brusey, Senior Lecturer, [email protected]

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Bremen, February 2009.

Cogent Staff and PhD studentswww.cogentcomputing.org

Tessa Daniel

[email protected]

Expertise:

Applicative Query Mechanisms; Information Extraction in Wireless Sensor Networks.

John Kemp

[email protected]

Expertise:

Advanced Sensing; Sensing Visualisation Systems.

Tony Mo

[email protected]

Expertise:

Wireless sensing for gas turbine engines

Michael Richards

[email protected]

Expertise:

3D CFD Modelling

Dr Elena Gaura

[email protected]

Expertise:

Advanced Sensing; Advanced Measurement Systems; Ambient Intelligence; Design and Deployment of Wireless Sensor Networks; Distributed Embedded Sensing; Intelligent Sensors; Mapping Services for Wireless Sensor Networks; MEMS Sensors

Dr James Brusey

[email protected]

Expertise:

Industrial Robotics and Automation; Machine Learning; RFID; Sensing Visualisation Systems.

Mike Allen

[email protected]

Expertise:

Design and Deployment of Wireless Sensor Networks; Distributed Embedded Sensing.

Costa Mtagbe

Expertise:

Environmental monitoring

Ramona Rednic

[email protected]

Expertise:

Body sensor networks,

Posture

Dan Goldsmith

[email protected]

Expertise:

Middleware design and test-beds for WSNs

Dr. Fotis Liarokapis

[email protected]

Expertise:

Mixed reality systems; mobile computing, virtual reality for entertainment and education

Dr. James Shuttleworth

[email protected]

Expertise:

3D Graphics; data fusion and feature extraction, information visualization

Gaura, Brusey


Gaura brusey

Talk Scope

  • development cycle for a multi-modal wearable instrument

  • system design decisions

  • embedding actuation and its consequences

  • hurdles encountered….

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Pointers

  • Timeliness: BSNs and WSNs are becoming commercial in their simpler forms; also coming out of research labs in elaborate versions;

  • Task Difficulty: Designing such systems needs teams of applications specialists, electronics engineers (most often) and definitely Computer Scientists;

  • Usefulness: proven, but, apart from being very useful, BSNs are a lot of fun to develop!

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Talk Structure

  • Part 1: Introduction and overview of the application

  • Part 2 : The deployment environment - a physiological perspective

  • Part 3 : System design

  • Part 4 : Enabling actuation - on-body processing

  • Part 5 : Implementation - software and hardware support

  • Part 6: Results analysis and evaluation

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Part 1: Introduction and overview of the application

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

WSNs: research motivation

  • Start point:

  • -Smart Dust (1998) – Pister

  • ($35,000) vision of “millions of tiny wireless sensors (motes) which would fit on the head of a pin”

  • -sharing “intelligent” systems features (self –x) pushed to XLscale – millions of synchronized, networked, collaborative components

  • Today:

  • -Dust Networks - $30 mil venture (2006);

  • -TinyOS – the choice for 10000 developers

  • -make the news and popular press

  • - fashion accessory & easy lobbying

  • - big spenders have committed already (BP, Honeywell, IBM, HP)‏

  • -technologies matured (digital, wireless, sensors)‏

  • -first working prototypes;

  • -getting towards “out of the lab”

  • -social scientists are getting ready!

Attention!

Your spatio-temporal activities are recoded and analyzed by the 20000 sensors wide campus net

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

WSNs –reality

Market forecast:

2014- $50bil. , $7bil in 2010 (2004)‏

2014- $5-7 bil. sales (conservative)‏

2011-$1.6 bil. smart metering/ demand response

Industrial Markets-old and new; mostly wired replacements; generally continuous monitoring systems with “data-made-easy” features and internet connected

Prompted by regulations and drive towards process efficiency or else…

the “cement motes” from Xsilogy come with 30 min warranty!

Infineon tyre sensor

Connecting 466 foil strain gages to a wing box

Invensys asked a Nabisco executive what was the most important thing he wanted to know. The reply came without a moment's delay: "I'd like to know the moisture content at the centre of the cookie when it reaches the middle of the oven."

Research: mainly newly enabled applications; “macroscopes”/ “microscopes” ; adventurous money savings ideas

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

WSNs - pushing the frontiersThe motivational square

…forget about throwing them from the back of that plane!...

Practical, application oriented research and deployments

Visions

Making the most out of a bad situation

Research space

Research space

Commercial endeavours

Research/Adoption roadblocks

Internet able Microclimate, soil moisture, disease monitoring

Largest part of community

Theoretical research for large scale networks

Industrial needs

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Why is it all so hard?

…the WSN design space(Ray Komer, ETH, 2004)‏

deployment

mobility

cost, size, resources and energy

heterogeneity

communications modality

infrastructure

network topology

coverage

connectivity

network size

lifetime

other QoS requirements

Highly theoretical works

Vs

practical deployments

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

WSN challenges

  • Application specific (deployment, size, weight, etc)‏

  • System specific – the network is the SENSOR

    • Distributed processing- system infrastructure

    • Information extraction

    • Scalability

    • Robustness

  • Node specific – hardware integration/fabrication/packaging

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

WSN – challenges cont’d

  • Physical environment is dynamic and unpredictable (Hw&Sw)‏

  • Small wireless nodes have stringent energy, storage, communication constraints (Hw mainly)‏

  • In-network processing of data close to sensor source provides (Sw, systems design)‏

    • Scalability for densely deployed sensors

    • Low-latency for in situ triggering and adaptation

  • Embedded nodes collaborate to report interesting spatio-temporal events (Sytems design)‏

Embeddable Portable Adaptive

Low cost Robust Self healing

Self configuring Globally query-able

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Application related challenges

  • User requirements definition – novel technology hence this is hard

  • Capability/expectations mitigation

  • Lack of comparison measure at end-to-end systems level

  • !!!Consequence!!!

  • Don’t underestimate the role of cyclic requirements/development/demonstration methodology

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Data acquisition phase

  • Sensors availability – MEMS technologies are just maturing - many physical sensors available

  • Digital or analogue output - Digitization required

  • Sensors compatibility with other systems components

  • SENSORS CALIBRATION, DRIFT AND FAULTS- Mostly uncalibrated, but…very cheap

  • Integration sometimes a problem

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Processing and comms challenges

  • Nodes size, weight, energy resources and processing capabilities – contrary constrains which need mitigating

  • Unreliability of wireless communications

  • Lack of debugging tools and wireless technology immaturity

  • Off-the-shelf comms encapsulation; unlexible protocols

  • Processing with little on much data

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Processors and Motes Hardware

Mote

Sensor device interface

Processor

Memory

Communications

Form factor

Renee

Mezzanine card

Atmel 8 bit 4 MHz

49 kB

916MHz, software modulation

484 mm2

rectangle

Mica 2

Mezzanine card (4 sensors)‏

Analog

Atmel 8 bit 8 MHz

644 kB

916/433MHz

hardware modulation

19.2 kbps

1800 mm2

rectangle

Mica2Dot

Single sensor

Analog

Atmel 8 bit 4 MHz

644 kB

916/433MHz

hardware modulation

19.2kbps

255 mm2

disc

MicaZ

Mezzanine card (4 sensors)‏

Analog

Atmel 8 bit 8 MHz

644 kB

2.4GHz

ZigBee

1800 mm2

rectangle

Intel mote

Digital interface

ARM 32-bit 12 MHz

586kB

2.4GHz

Bluetooth

900

mm2

rectangle

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Information extraction challenges

  • Timeliness of acquired data

  • Time synchronization

  • Data storage

  • Information extraction at source

  • Co-opertive behaviour

  • Global vs local treatment of the challenge

  • Mitigating energy vs quality/detail vs timeliness vs system cost, size, etc

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Information delivery challenges

  • Raw data is too much saying too little

  • Huge range of user requirements motivated by – conservativeness of some engineering fields (ref- Energy sector, aerospace, defence)‏

  • Ease of interpretation by human in the loop – hard to accommodate with limited resources

  • Range of useful options continuously growing presently

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Actuation enablers

  • Are still in its infancy

  • Much to be gained from any breakthroughs here

  • Enabling actuation has serious consequences in the overall system design

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

User satisfaction

  • Usually unknown/unpredictable till the development ends

  • Trail and error as the favourite methods presently

  • Huge range of reported work which failed to satisfy for all possible resons

  • Unreliability of the put-together systems is damaging to the filed

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

The Grand WSN challenge

Facilitating the migration of pervasive sensing from future potential to present success

  • Design space

  • Care for the un-expert user – “beyond data collection systems”

  • Robustness, fault tolerance

  • Long life – across system layers and system components- in network processing &distribution

  • Maintenance free systems – scalability, remote programming &generic components/ infrastructure

“The network is the sensor”

VLS networks as

Scientific instruments

Permanent monitoring fixtures

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Software - design features

  • designing for information visualization

  • designing for robustness and long life - Fault Detection and management

  • designing for practical applications

  • designing for robust services support

  • designing for information extraction- Complex Querying

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Designing for practical applications

  • The problems:

  • Robustness of deployment

  • Technologies Integration

  • Fitness for purpose

  • Non-experts will use it!!!

BSN

End-to-end system design approach

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Matching application requirements with available technology in a safety critical application

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Project history

  • Commissioned late 2005

  • Externally funded

  • Client: NP Aerospace Plc - protective clothing manufacturer for Defence - mostly for bomb disposal missions, de-mining, etc

  • PhD student project

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Project aim: Increased safety of missions through remote monitoring

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

The problem: the suit Environment

  • Increased heat production and reduced ability to remove heat results in storage

  • Thermoregulatory system becomes unable to correctly regulate core temperature

  • This may result in physical and psychological impairment

  • Increased risk of making an avoidable error and jeopardising the mission

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Possible solutions

Manufacturer solution: add a cooling system to the suit

Inadequate:

Inefficient use due to human factors

Distraction

Alternative:

in-suit instrumentation and continuous monitoring

automated cooling actuation based on state

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Architecture

  • Sense-model-decide-act architecture

  • Two control loops

    • Rapid feedback to autonomously adjust cooling

    • Support for modifications to mission plans and investigation into the construction of the suit.

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Instrument Requirements

  • provide detailed physiological measurement - better insight into what is happening

  • support on-line and real-time thermal sensation estimates

  • report of useful information (rather than data) to a remote station and the operative

  • enable rapid assessment of hazardous situations

  • allow the provision of thermal remedial measures through control and actuation

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Part 2 : The deployment environment - a physiological perspective

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

UHS and Suit Trials

  • UHS- the thermoregulatory system is unable to defend against increases in core body temperature

  • UHS - associated with significant physical and psychological impairment

  • Trials activity regime -four 16:30 min:sec cycles

    • treadmill walking

    • unloading and loading weights from a kit bag

    • crawling and searching

    • arm cranking

    • standing rest

    • seated physical rest

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Experimental data

  • Measurands- wired instrumentation

    • Heart rate

    • rectal temperature

    • skin temperatures (arm, chest, thigh and calf )‏

  • Assessment

    • Subjective thermal sensation – twice per cycle, per segment and overall

    • Comfort – as above

  • Measurands - wireless

    • Skin temperature - 12 sites (symetrical + neck +abdomen)‏

    • Acceleration - 3D - 9 sites

    • Pulse oximetry, heart rate, CO2, galvanic

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Experimental data

Figure 5. Core temperature responses (n=4; error bars are omitted for clarity) FS-NC=full suit, no cooling; NS= no suit

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Experimental data

Figure 6. Skin and rectal temperature over time for a subject wearing the full suit with no cooling. Note how core temperature rises with thigh temperature after the two merge. This experiment needed to be terminated as the subject could not continue.

Figure 3. Typical heart rate response to EOD activity simulation (based on a single subject trial). FS-NC=full suit, no cooling; NO-S=no suit; W=walking; U=unloadin/loading weights; C=crawling and searching; A= arm exercise; R= seated rest. NB. Two of four subjects were not able to complete four activity cycles.

Figure 4. Mean skin temperature responses (averaged over 4 subjects; error bars are omitted for clarity). FS-NC=full suit, no cooling; NS=no suit

Figure 7.Self-assessed thermal sensation compared with chest skin temperature for subject 1.

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Part 3: System design

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Constraints and design choices- I

  • Suit related

    • Mix of wired and wireless

    • Multiple sensors to each node

    • Wires in suit

    • Size, power and weight a concern

  • Suit modularity accounted for – multi-node BSN

  • Three tiers of comms

    • Sensors to node

    • Node to node

    • Node to base station

Two separate systems for:- posture monitoring

Physiological ???

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Constraints and design choices- II

  • Application related

    • Intermittent comms - jammers, obstacles

    • Maintaining autonomous operation - key

  • Two modes of wireless comms

    • In-suit, on body - short range, near field

    • External to mission control - long range

    • Buffering - avoid overflow

    • Priority transmission

    • Information extraction in-suit

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Constraints and design choices-III

  • Safety critical

    • Cooling actuation

    • Operative alerts

    • Mission alerts

    • Hardware redundancy

  • Information extraction in-network - major design implications

  • Fault isolation and management

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Constraints and design choices-IV

  • Instrument scope-dual

    • In field

    • In the lab - for physiological research and manufacturer research

  • User led choice of operation

  • In field

    • max infromation output - thermal sensation, cooling status, trends, alerts x2

    • Data on demand - temperature and other selected

  • In the lab

    • Data output - continuous - all including accel

    • Information output - continuous

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Part 4: In-network modeling

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Processing

  • Basic filtering performed on sensor node

    • Allows rejection of invalid data and generation of alarms

  • Additional filtering using a Kalman filter on the processing nodes

    • Smooths data as well as providing estimates of error

  • Modelling of thermal sensation

  • Operative alerts

  • Mission control alerts

Include posture

CO2 thresholding

HR

Prediction models

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

ISWC, Pittsburgh, 01/10/2008

Temperature and Thermal Comfort


Gaura brusey

Temperature, Filters and Fusion – Kalman Filtering

  • Why filter?

    • Basic measurements may be too noisy

    • Can’t estimate gradient meaningfully otherwise

  • Why fuse measurements?

    • Two measurements are more reliable than one

    • Allow for / detect faulty sensors

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Thermal sensation Modelling

  • Takes skin temperature (and optionally core temperature) readings as input

  • Provides an estimation of thermal sensation, both per body segment and globally, as output

  • The main part of the model is a logistic function based on two main parameters:

    • the difference between the local skin temperature and its “set” point (the point at which the local sensation is neutral)

    • the difference between the overall skin temperature and the overall set point

  • Thermal sensation is given in the range −4 to 4, with −4 being very cold and 4 being very hot

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Zhang’s model

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Zhang’s model evaluation

Figure 9.Overall thermal sensation over time during the activity regime with the full suit and with no cooling.

Figure 8. Overall thermal sensation over time during the activity regime with no suit.

Figure 10.Overall thermal sensation over time for a habituated subject with the full protective suit and no cooling.

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

ISWC, Pittsburgh, 01/10/2008

HR and CO2


Gaura brusey

ISWC, Pittsburgh, 01/10/2008

Posture


Gaura brusey

ISWC, Pittsburgh, 01/10/2008

Posture


Gaura brusey

Follow-up

  • New model needed

  • Activity needs monitoring – posture

  • Other physiological parameters have to be tried out –HR, galvanic response, heat flux

  • Model needs to predict not estimate/assess

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Part 5: Prototype implelentation

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Platform and sensors

Picture of CO2 and HR

JOHN’ New DIAGRAM HERE

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Networking

New pic from John and Ramona here

  • Wireless links between actuation / processing nodes

  • Wireless link between actuation node and remote monitoring point

  • Data/information buffered in case of link failure - may be uploaded at future point

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Temperature Component Data Flow

Figure 13. Data and information system flow

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

ISWC, Pittsburgh, 01/10/2008

Posture Component Data Flow


Gaura brusey

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Remote Monitoring

New pic from Ramona paper

New pic from John paper

  • Main information display panel includes:

    • a 3D figure showing the interpolated temperature distribution across the subject’s skin

    • the current average skin temperature, and

    • the current thermal sensation level

  • Other panels show the location and status of the sensors and the history of the incoming data

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Actuation

  • Reinforcement Learning algorithms (such as SARSA) can be used to develop a “policy” for controlling the cooling fan based on the “state” of the user

  • Action is to turn fan on or off and regulate volume

  • Utility is based on maintaining good comfort levels over time

  • Takes account of battery depletion, likely mission duration, posture, as well as current thermal comfort

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Operative alerts

  • Framework in place

  • Data and information processing flows readily available (piggy back on mission control)‏

  • Avoid false alarms - link to robustness and fault management

  • Sound considered at this stage but tactile sounds good too

  • Research into HCI issues badly needed

Elena to change

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Evaluation and results

Figure 19. Predicted thermal sensation including dynamic component of model

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

(a)‏

(b)‏

(c)‏

(d)‏

(e)‏

(f)‏

Figure 10. Skin temperature over time for (a) arm, (b) neck, (c) abdomen, (d) chest, (e) thigh, and (f) calf sites. The two leg sensors (thigh and calf positions) were placed on the right leg only. For several skin sites, temperature values were also obtained using a wired-in data logger (denoted "Logger"). The vertical lines in each graph show the start and end of activities. Each activity is represented by a number.

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Enriching the system for larger informational gain - posture monitoring

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Aim and postures

  • Dual aim

    • Direct activity information to mission control for

      • Supervision of mission - health hazards/colapse/restrains

      • Technical assessment - problems - controller expertise

      • Inferrence of abstract info by controllers

    • Parameter for thermal state prediction

  • 8 postures required: stand, walk, crawl, sitting, lying down (up, down, side x2)‏

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Results and evaluation for posture monitoring

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

Review of tutorial and summary

  • exposition of design techniques and design choices

  • focus on an example

  • BSN- neither large nor widely distributed but there are a number of fundamental requirements

    • the size of the nodes, wearability of the instrumentation, robustness, reliability and fault-tolerance, etc

  • they dictate the majority of the design and implementation choices.

  • Pursuing application driven design processes will enable the development of industrially strong systems which will increase confidence in the technology and contribute to its adoption in near future.

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


Gaura brusey

WSN – theoretical wonders

  • Scoping of large scale applications

  • Complex problems solved for individual functional components/services

  • Theoretical proofs and simulation only

  • Lack of integrative work

Visions led

SENSE and SEND

1. Dust size- mm cube

2. Unplanned deployment

3. Distributed

4. Millions of

5. Re-configurable nets

6. Self-healing

7. Scalable

8. Autonomous

9. Information systems

10.Collaborative decisions

1. Stack of quarters & miniaturization vs mote life trade-off

2. Planned, carefully measured; ID based

3. Gateway based – centrally controlled; backboned

4. Hundreds at most (ExScal)‏

5. Hard coded

6. Prone to failure (more than 50% usually)‏

7. Only through complete re-design

8. Tightly controlled

9. Data acquisition – relay to base

10. Central post processing

Gaura, Brusey

ISWC, Pittsburgh, 01/10/2008


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