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Sensor Web

Browsing the physical world in real-time

By: Vincent Tao

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History

• Conceived: 1997, NASA/Jet Propulsion Laboratory

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History

• Conceived: 1997, NASA/Jet Propulsion Laboratory

• Idea: – sensor chips to monitor and control

environment– sensations transmitted via internet in real-time

CMSC 828S / Saket Navlakha / 4

History

• Conceived: 1997, NASA/Jet Propulsion Laboratory

• Idea: – sensor chips to monitor and control

environment– sensations transmitted via internet in real-time

• Why is this different?

CMSC 828S / Saket Navlakha / 5

History

• Conceived: 1997, NASA/Jet Propulsion Laboratory

• Idea: – sensor chips to monitor and control environment– sensations transmitted via internet in real-time

• Why is this different?– Cheaper sensors more possibility– Networked (not individual) sensors

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Example: Restaurant Waiting Time

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Problems: Interoperable

• Interoperable– In-site (on-site) sensors

• Measuring physical properties of an area

– Remote sensing• Via radiation reflected or emitted from object• GPS

– Web

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Problems: Interoperable

• Interoperable– In-site (on-site) sensors

• Measuring physical properties of an area

– Remote sensing• Via radiation reflected or emitted from object• GPS

– Web

• Implies data formatting standards (Open GIS)– Web Map Service, Geographic Markup Language,

SensorML, etc

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Problems: Intelligent

• Intelligent– Sense environment and respond– Communicate amongst each other– Data integration

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Problems: Flexible

• Flexible– Different types of sensors

• Deterministic• Triggered• On-demand

– Broken sensors– Fault tolerant to noise, redundant– Weather conditions– Easy deployment

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Problems: Scalability & Size

• Scalability– Large number of interacting sensors– Large number of simultaneous requests– Efficiently locate sensors– Adapt to sensor join/leaves

• Size: does one size fit all?

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Problems: Scalability & Size

• Scalability

• Size: does one size fit all?– smaller panels (less energy harvesting)– smaller antennae (less radio range)– smaller batteries (less power)– larger sensors (harder to manage, intrusive)

What about tiered architecture?

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SenseWeb

• Microsoft Research project

• Goals:– Ease of data publication– Application-to-application compatibility– Primitives to query live sensors

Create SensorNet

• Display: MSN Virtual Earth

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SenseWeb: Architecture

• Data Publishing Toolkit (DPT)– Publishes sensor metadata (location/type) to GeoDB– Publishes sensor data in response to queries

• Uses sensor ontology standards• GeoDB

– Indexes metadata; uses hierarchical triangular mesh (HTM)

– Queries submitted by keyword, location, etc.

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SenseWeb: Architecture

• Data Publishing Toolkit• GeoDB• Aggregator

– Data integration: mashes sensor data with client side GUI (e.g. MSN Virtual Earth overlay)

– User query GeoDB relevant sensors DPT real-time data aggregate/summarize

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SenseWeb: Architecture

• Advantages– Data owner only talks to DPT– End users only browse web page and query

data GeoDB and Aggregator transparency

• Disadvantages?

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Conclusion

• Ubiquity & Invisibility• Overview of problems• Four layers

– Sensor: sensor design, materials, etc– Communication: protocols, standards, etc– Location: routing, addressing, etc– Information: data integration, distribution, etc

• Which can be different? Which need standardization?

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Conclusion

• Next: algorithms & techniques to solve problems (e.g. HTM, P2P communication, statistical data modeling, more applications)