Wireless Sensor Networks COE 499 Introduction to Sensor Networks

1. Wireless Sensor Networks COE 499Introduction to Sensor Networks Tarek Sheltami KFUPM CCSE COE http://faculty.kfupm.edu.sa/coe/tarek/coe499.htm

2. Outline • Introduction • Application Areas • Systems Involved • Communications • Challenges in SNETs • Unique constraints • Power Issues

3. Involved Technologies Network Technology Sensor Network Computational Power Sensor Technology

4. Application Areas • Military • Infrastructure security • Environment & Habitat Monitoring • Healthcare • Industrial Sensing • Traffic Control • Seismic Studies • Life Sciences

5. The Systems involved • Sensor Node Internals • Operating System • Physical Size

6. Sensor Node Internals CPU INFRARED ACOUSTIC SEISMIC IMAGE MAGNETIC… POWER SUPPLY ELECTRO-MAGNETIC INTERFACE SENSOR COMMUNICATION NODE • Some Current Node Platforms: • Sensoria WINS • Smart Dust – Dust Inc. Berkeley • UC Berkeley mote – Crossbow (www.xbow.com)

7. Operating System - TinyOS • Custom built at UC, Berkeley for wireless sensor nodes • Component-based architecture: ensures minimum code size • Component library includes: • Network protocols • Sensor drivers • Data acquisition tools • Distributed services

8. Physical Size WINS NG 2.0 Berkley Motes AWAIRS I LWIM III AWACS

9. A Few Smart Sensor Implementations Finger Tip Sensors Smart Its Project Tiny Heart Capsule Endoscope JPL Sensor A Bee Tracker

10. Smart Sensor Example in Health Care • Can be taken just like a capsule • It moves through the intestinal track due to contraction and relaxation • Excreted naturally and is disposed off • Safe to the body • Future: Remote control Pills and Micro-surgery Duodenal Bleeding

11. Sensor Network in Health Care.. • In-Home Health Care Solution from Intel • In-home technology prototypes illustrate how tiny silicon-based sensing devices discreetly embedded in objects such as shoes, furniture and home appliances • It can make it possible for elders, Alzheimer's disease patients and others with disabling conditions to continue to live at home • Intel and university researchers determined that wireless sensor networks, combined with powerful computing and complex algorithms, can effectively send prompts through various household devices to assist the elderly and inform, as well as ease the workload of caregivers.

12. Biomimetics Living organisms use sensory abilities for all activities This is in spite of lot of noise in the environment The science of such sensory fusion is available in Biology Biomimetics – Mimic the available knowledge in Biology to design robust sensor fusion algorithms A few preliminary applications are shown below Electronic Tongue Electronic Nose

13. In-Home Health Care Solution from Intel • Intel Research Seattle uses postage-sized wireless radio frequency identification (RFID) tags affixed to household objects • To monitor and record the daily activities of an elder • The tags wirelessly communicate the data back to a central system that could help manage everyday activities so that the elders' independence is maintained while relieving some of the burden of around-the-clock care by caregivers

14. California Institute of Technology - MicroBat

15. Solar panel. Cabinet with radio sender, micro processor and digital and analog I/O. Water level sensor. Water wheel at farm gate.

16. Central Goulburn no. 2 channel.

17. Mulwala canal. Largest irrigation channel in the southern hemisphere.

18. Communication • Network Protocol • Network Discovery • Network Control & Routing

19. Network Protocol • For wireless sensor networks: IEEE 802.11 standards • Personal Area Networks (PAN): IEEE 802.15 standard • Radius of 5 to 10m • Ideal application in short-range sensors

20. Network Discovery • Knowledge of identity and location of its neighbor • Ad hoc protocols can be used • GPS system can be used as well

21. Network Control & Routing • Network adapts dynamically to • conserve resources like energy and available nodes • Make optimum use of bandwidth and processing power • Connectivity must emerge as needed from algorithms • Directed Diffusion routing • Data identity is separate from node identity • Promotes adaptive, in-network processing

22. Sensors • Passive elements: seismic, acoustic, infrared, strain, humidity, temperature, etc. • Passive Arrays: imagers (visible, IR), biochemical • Active sensors: radar, sonar • High energy, in contrast to passive elements • Technology trend: use of IC technology for increased robustness, lower cost, smaller size

23. Event Driven Model

24. On-Demand Model

25. TinyOS is an open-source operating system designed for wireless embedded sensor networks. It features a component-based architecture which enables rapid innovation and implementation while minimizing code size as required by the severe memory constraints inherent in sensor networks. TinyOS's component library includes network protocols, distributed services, sensor drivers, and data acquisition tools – all of which can be used as-is or be further refined for a custom application. TinyOS's event-driven execution model enables fine-grained power management yet allows the scheduling flexibility made necessary by the unpredictable nature of wireless communication and physical world interfaces. TinyOS has been ported to over a dozen platforms and numerous sensor boards. A wide community uses it in simulation to develop and test various algorithms and protocols. New releases see over 10,000 downloads. Over 500 research groups and companies are using TinyOS on the Berkeley/Crossbow Motes. Numerous groups are actively contributing code to the sourceforge site and working together to establish standard, interoperable network services built from a base of direct experience and honed through competitive analysis in an open environment.