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CMSC 828S / Saket Navlakha / 1
Sensor Web
Browsing the physical world in real-time
By: Vincent Tao
CMSC 828S / Saket Navlakha / 2
History
• Conceived: 1997, NASA/Jet Propulsion Laboratory
CMSC 828S / Saket Navlakha / 3
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
CMSC 828S / Saket Navlakha / 6
Example: Restaurant Waiting Time
CMSC 828S / Saket Navlakha / 7
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
CMSC 828S / Saket Navlakha / 8
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
CMSC 828S / Saket Navlakha / 9
CMSC 828S / Saket Navlakha / 10
Problems: Intelligent
• Intelligent– Sense environment and respond– Communicate amongst each other– Data integration
CMSC 828S / Saket Navlakha / 11
Problems: Flexible
• Flexible– Different types of sensors
• Deterministic• Triggered• On-demand
– Broken sensors– Fault tolerant to noise, redundant– Weather conditions– Easy deployment
CMSC 828S / Saket Navlakha / 12
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?
CMSC 828S / Saket Navlakha / 13
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?
CMSC 828S / Saket Navlakha / 14
SenseWeb
• Microsoft Research project
• Goals:– Ease of data publication– Application-to-application compatibility– Primitives to query live sensors
Create SensorNet
• Display: MSN Virtual Earth
CMSC 828S / Saket Navlakha / 15
CMSC 828S / Saket Navlakha / 16
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.
CMSC 828S / Saket Navlakha / 17
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
CMSC 828S / Saket Navlakha / 18
SenseWeb: Architecture
• Advantages– Data owner only talks to DPT– End users only browse web page and query
data GeoDB and Aggregator transparency
• Disadvantages?
CMSC 828S / Saket Navlakha / 19
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?
CMSC 828S / Saket Navlakha / 20
Conclusion
• Next: algorithms & techniques to solve problems (e.g. HTM, P2P communication, statistical data modeling, more applications)