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Challenges & Opportunities in Monitoring of Buildings with Wireless Sensor Networks Murat Demirbas University at Buffalo, SUNY Computer Science & Engineering.

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Presentation on theme: "Challenges & Opportunities in Monitoring of Buildings with Wireless Sensor Networks Murat Demirbas University at Buffalo, SUNY Computer Science & Engineering."— Presentation transcript:

1 Challenges & Opportunities in Monitoring of Buildings with Wireless Sensor Networks Murat Demirbas University at Buffalo, SUNY Computer Science & Engineering Dept.

2 2 New Class of Computing year log (people per computer) streaming information to/from physical world Number Crunching Data Storage productivity interactive Mainframe Minicomputer WorkstationPCLaptop PDA

3 3 Ubiquitous computing vision Instead of us interacting with the computers in the virtual world, the computers should interact with us in our physical world Technology is now available via MEMS, CMOS, CMOS radios PC processors are only 2% of all processors: the rest go to  Automotive; Communications; Consumer electronics; Industrial equipment Real-world deployments for networked embedded systems have already started:  Environmental monitoring  Precision agriculture  Asset management  Military surveillance

4 4 Wireless sensor networks (WSNs) A sensor node (mote)  8K RAM, 4Mhz processor  magnetism, heat, sound, light, vibration, infrared  wireless (radio broadcast) communication up to 100 feet  costs ~$10 (right now costs ~$100)

5 5 Real-world deployments of robust WSN Line In The Sand In OSU, we developed a surveillance service for DARPA-NEST  Detect, track, and classify trespassers as car, soldier, civilian  LiteS: 100 nodes in 2003, ExScal: 1000 nodes in Dec 2004 Thick Entry Line A S S E T 1 km 250 m

6 6 Real-world deployments of robust WSN Redwood monitoring

7 7 Benefits of using WSN Ease of deployment  Wireless communication means no need for a communication infrastructure setup  Drop and play Low-cost of deployment  Nodes are built using off-the-shelf cheap components Fine grain monitoring  Feasible to deploy nodes densely for fine grain monitoring

8 8 TinyOS in a nutshell Most popular operating system for WSN  developed by UC Berkeley Features a component-based architecture  software is written in modular pieces called components  TinyOS provides a component library that includes network protocols, services, and sensor drivers Easy to link components together by “wiring” their interfaces to form larger components  similar to using Lego blocks

9 9 Benefits of using TinyOS Separation of concerns  TinyOS provides a proper networking stack for wireless communication & abstracts away the complexity of message transfer, e.g., MAC layer Concurrency control  TinyOS provides a scheduler that achieves efficient concurrency control  An interrupt-driven execution model is needed to achieve a quick response time for the events and capture the data Modularity  TinyOS’s component model facilitates reuse and reconfigurability; several middleware services are available as well-documented components  Over 500 research groups and companies are using TinyOS

10 10 Middleware services Middleware is the software that supports building of complex distributed applications:  Time synchronization  Localization  Routing  Querying  Reprogramming  Power management

11 11 Challenges in sensor networks Energy constraint Unreliable communication Unreliable sensors Large scale networks Limited computation power Distributed execution :Nodes are battery powered, each transmission is precious :Radio broadcast, limited bandwidth, bursty traffic :False positives :Algorithms should scale well :Centralized algorithms inapplicable :Difficult to debug & get it right

12 12 Monitoring of next generation buildings Structural monitoring In-door environmental monitoring Extreme-events response

13 13 Structural monitoring Accelerometer and strain gauges  for monitoring the natural vibration frequencies of a structure under naturally induced or forced vibrations  2micro-g sensitivity & 2g range  1micro-strain sensitivity & 2milli range Networking challenges for reliable transmission of the large amount of bursty traffic  Wavelet compression, event thresholding  Combination of dimensionality reduction and scalar quantization: Transform coding

14 14 Open research problems Model-based monitoring –This may lead to huge bandwidth and energy savings –But, we need good models of the behaviors (e.g., a classification of the behavior to 10 categories?) Prioritization of data –Huge bandwidth savings are possible by deciding which data is more important –Need help from domain experts Lifetime of deployment –Alternative means to power the nodes Lightweight localization –It may be possible to achieve light-weight (in terms of computational power and communication cost) localization by exploiting domain specific information Data mules –Alternative ways of carrying messages by exploiting the mobility inherent in the system –E.g., can we use elevators to carry data between floors

15 15 In-door environment monitoring Applications: –Control of heating, AC, light intensity –Monitoring the in-door air quality Querying and wireless reprogramming can put the building in different modes: Night / Holiday / Busy mode Standard sensors are available for the job Open research problems Scalability –Hundreds of nodes should be deployed –Hierarchical management techniques can be useful Integration with 802.11 WAPs and Internet

16 16 Extreme event response Alarm should be issued quickly upon detection of fire, explosion, structural strength degradation, or chemical attack Using the information gathered, WSN can provide real-time evacuation directions for occupants The system can also be useful for enabling rescuers locate survivors under collapsed structures in the aftermath of a collapse Open research problems Timeliness & dependability guarantees are needed –Formal methods can be helpful The number of false- positives should be kept at an acceptable level for deployment Intuitive interfaces

17 17 Concluding remarks Interdisciplinary collaboration between CSE and CE is needed  CSE effort should be guided by the context provided by CE that answer the questions what to sense?, where to sense?, when to sense?  Depending on the answers to the questions such as What level of accuracy is acceptable?, Which events are of interest and which are ignorable?, and What are the right places for deployment?, CSE researchers can fine-tune the performance and lifetime of the wireless monitoring systems Security and privacy issues should also be addressed before real deployments


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