1. CMSC 828S / Saket Navlakha / 1 Sensor Web Browsing the physical world in real-time By: Vincent Tao

2. CMSC 828S / Saket Navlakha / 2 History Conceived: 1997, NASA/Jet Propulsion Laboratory

3. 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

4. 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?

5. 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

6. CMSC 828S / Saket Navlakha / 6 Example: Restaurant Waiting Time

7. 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

8. 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

9. CMSC 828S / Saket Navlakha / 9

10. CMSC 828S / Saket Navlakha / 10 Problems: Intelligent Intelligent –Sense environment and respond –Communicate amongst each other –Data integration

11. 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

12. 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?

13. 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?

14. 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

15. CMSC 828S / Saket Navlakha / 15

16. 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.

17. 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

18. 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?

19. 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?

20. CMSC 828S / Saket Navlakha / 20 Conclusion Next: algorithms & techniques to solve problems (e.g. HTM, P2P communication, statistical data modeling, more applications)