Overview and applications

1
Overview and applications

• Vinod Kulathumani
• West Virginia University

2
Outline

• Vision for sensor actuator networks
• Networked embedded systems
• Enabling technology
• Application areas
• Sensing-only systems
• Monitoring related applications
• Application examples
• Challenges and design space
• Sensing actuation
• Examples
• Challenges and design space
• ExScal, an example surveillance application

3
Embedded systems

• Found in variety of devices
• Aircraft, radar systems, nuclear and chemical
  plants
• Vehicles, TVs, camcorders, elevators
• gt 90 of CPUs used for embedded devices

4
Networked embedded systems

• Currently
• Embedded processors - part of a larger system
• Application known apriori
• Little flexibility in programming
• What if?
• embedded processors were connected preferably
  wireless?
• there was greater flexibility in programming ?
• sensing and actuation capabilities were included
  ?

5
The Vision for WSANs

• Combine wireless networks with sensing /
  actuation
• ? Ubiquitous computing /
  pervasive computing
• Fine-grained monitoring and control of
  environment
• Network and interact with billions of embedded
  computers
• Reasons
• Wireless communication - no need for
  infrastructure setup
• Drop and play
• Nodes are built using off-the-shelf cheap
  components
• Feasible to deploy nodes densely

6
New Class of Computing
log (people per computer)?
streaming information to/from physical world
year
Slide courtesy Murat Demirbas
7
Opinions

• Tiny computers that constantly monitor
  ecosystems, buildings, and even human bodies
  could turn science on its head.
• - Nature, March
  2006
• The use of sensornets throughout society could
  well dwarf previous milestones in information
  revolution.
• - National Research Council report, 2001
• Reinventing computer science
• - David Tennenhouse, Intel,
  2000

8
Enabling technology

• Powerful microprocessors
• Small form factor
• Low energy consumption
• Micro-sensors (MEMS, Materials, Circuits)?
• acceleration, vibration, gyroscope, tilt, motion
• magnetic, heat, pressure, temp, light, moisture,
  humidity, barometric
• chemical (CO, CO2, radon), biological,
  micro-radar
• actuators (mirrors, motors, smart surfaces,
  micro-robots)?
• Communication
• short range, low bit-rate, CMOS radios

9
A typical sensor node

• Telosb (2007)
• 8 MHz MSP430 processor
• 10kB RAM
• 250 Kbps data rate
• Integrated temperature, humidity, light sensors
• Others

10
Application areas for WSANs

• Science
• Environmental and habitat monitoring
• Oceanography, seismology, water management,
• Engineering
• Precision agriculture
• Industrial automation
• Control systems,
• Daily life
• Detecting emergencies and alerting, disaster
  recovery
• Health care
• Traffic management and many more

11
Sensing only systems

• Popular as wireless sensor networks
• Useful for monitoring based applications
• Large scale networks of embedded sensors
• Connected to a remote base station
• Self-configuring
• Typically resource constrained (Why?)

12
Block diagram of a sensor node
Application
PROCESSING SUB-SYSTEM
COMMUNICATION SUB-SYSTEM
SENSING SUB-SYSTEM
Processor
POWER MGMT. SUB-SYSTEM
ACTUATION SUB-SYSTEM
SECURITY SUB-SYSTEM
Actuator (Buzzer)
Network Interface
Sensor (Light)

• Substitute any sensing / actuating modality

13
Application category Monitoring type

• Environmental monitoring

Object tracking
Infrastructure monitoring
Body sensor networks
Perimeter security
Camera sensor networks
14
Emerging applications

• Combination of sensors with mobile devices
• Social networking
• Participatory urban sensing
• Assisted living health monitoring
• Vehicular networks with variety of sensors

15
Specific examples

• Detect and track intruders in a secure area
• Detect chemical or biological attacks
• Detect building fires and set up evacuation
  routes
• Monitoring dangerous plants
• Monitoring social behavior of animals in farms
  and natural habitats
• Monitoring salinity of water
• Monitoring cracks in bridges
• Tracking dangerous goods
• Shooter Localization
• Epilepsy monitoring and suppression
• Camera networks for urban surveillance
• Monitoring traffic on a highway

16
Challenges in sensor networks

• Energy constraint
• Unreliable communication
• Unreliable sensors
• Ad hoc deployment
• Large scale networks
• Distributed execution
• Ease of use

• Nodes are battery powered
• Radio broadcast, limited bandwidth, bursty
  traffic
• False positives
• Pre-configuration inapplicable
• Algorithms should scale well
• Difficult to debug get it right
• All Scientists not programmers

17
Sensing actuation systems

• Not simply monitoring events, objects
• Combined with actuation
• Traditional control applications
• Decouple information availability
• Control assumes information is instantaneously
  available
• What if information is transmitted over a sensor
  network?
• Losses, delays in information
• New tools needed for programming, reasoning about
  such systems
• Building blocks for Cyber-physical systems -
  recent buzzword!

18
Sensing actuation systems

• Not simply monitoring events, objects
• Combined with actuation
• Traditional control applications
• Decouple information availability
• Control assumes information is instantaneously
  available
• What if information is transmitted over a sensor
  network?
• Losses, delays in information
• New tools needed for programming, reasoning about
  such systems
• Building blocks for Cyber-physical systems -
  recent buzzword!

Note Applying control theory for network systems
has existed before (example TCP
congestion) This is control systems designed on
top of networks
19
Example sensor actuator networks

• Robotic systems
• Self-configuring structures
• Robotic surgery
• Self-configuring table
• http//www.youtube.com/ssrlab0/p/u/24/5uR34U1qc-Q
  
• Autonomic vehicular platoons
• Use in UAV swarms
• Autonomous driving Google Car!
• Distributed vibration control
• Distributed illumination control, irrigation,
  process control
• Smart power grid

20
We saw all these challenges for sensor networks

• Energy constraint
• Unreliable communication
• Unreliable sensors
• Ad hoc deployment
• Large scale networks
• Distributed execution
• Ease of use

• Nodes are battery powered
• Wireless, limited bandwidth, bursty traffic
• False positives, negatives
• Pre-configuration inapplicable
• Algorithms should scale well
• Difficult to debug get it right
• All Scientists not programmers

21
Add to these ....

• Energy constraint
• Unreliable communication
• Unreliable sensors
• Ad hoc deployment
• Large scale networks
• Distributed execution
• Ease of use

• Nodes are battery powered
• Wireless, limited bandwidth, bursty traffic
• False positives, negatives
• Pre-configuration inapplicable
• Algorithms should scale well
• Difficult to debug get it right
• All Scientists not programmers

. A control application that sits on
top Requires information guarantees from network
below!
22
Relation to CPS

• Cyber-physical systems are physical, biological,
  and engineered systems whose operations are
  integrated, monitored, and/or controlled by a
  computational core.
• Components are networked at every scale.
  Computing is deeply embedded into every physical
  component, possibly even into materials.
• The computational core is an embedded system,
  usually demands real-time response, and is most
  often distributed.
• The behavior of a cyber-physical system is a
  fully-integrated hybridization of computational
  (logical), physical, and human action.
• - National Science Foundation

23
Characteristics of CPS

• Cyber capability in every physical component
• Interaction at large scales with wired or
  wireless networks
• Dynamically re-organizing
• Novel computational substrates (bio / nano)
• Tight integration of computation, communication
  and control
• High degree of automation
• Operation must be dependable and certified
• Sensor nets control distributed computing
  real-time systems

24
Example Automotive Telematics

• Intra-vehicular sensing and control
• Engine control, Break system, Airbag deployment
  system, windshield wiper, Door locks,
  Entertainment system
• V2V networks
• Cars are sensors and actuators
• Vehicular safety
• Autonomous navigation
• Future Transportation Systems
• Incorporate both single person and mass
  transportation vehicles, air and ground
  transportations.
• achieve efficiency, safety, stability using
  real-time control and optimization.

25
Example Health Care and Medicine

• Electronic Patient Records
• Records accessible anywhere, any time
• Home care monitoring and control
• Pulse oximeters, blood glucose monitors, infusion
  pumps, accelerometers,
• Operating Room of the Future
• Closed loop monitoring and control multiple
  treatment stations, plug and play devices
  robotic microsurgery
• System coordination challenge
• Progress in bioinformatics gene, protein
  expression, systems biology, disease dynamics,
  control mechanisms

26
Example Electric Power Grid

• Current picture
• Equipment protection devices trip locally,
  reactively
• Cascading failure
• Better future?
• Real-time cooperative control of protection
  devices
• Self-healing, aggregate islands of stable bulk
  power
• Green technologies
• Coordinate distributed and dynamically
  interacting participants

27
Assignment 1

• Choose a WSAN application paper and prepare a
  report and ppt
• Prepare a 2 page report
• 11 point font
• Latex typesetting preferred
• Conference style formatting
• Prepare list of references
• Text in your own words
• State system requirements and challenges
• List enabling technologies
• Discuss how wireless networking of embedded
  devices play a role
• Discuss scalability and robustness of solution
• Discuss improvements and extensions
• State one new application of your choice for WSNs

28
Assignment 1

• A System for Fine-Grained Remote Monitoring,
  Control and Pre-Paid Electrical Service in Rural
  Microgrids (CMU, IPSN 2014)
• Aquatic Debris Monitoring Using Smartphone-Based
  Robotic Sensors (MSU, IPSN 2014)
• Airplanes Aloft as a Sensor Network for Wind
  Forecasting (Microsoft Research, IPSN 2014)
• One Meter to Find Them All - Water Network Leak
  Localization Using a Single Flow Meter (Penn
  state, IPSN 2014)

29
Assignment 1

• Identifying Drug (Cocaine) Intake Events from
  Acute Physiological Response in the Presence of
  Free-living Physical Activity (Memphis, IPSN
  2014)
• Sensors with Lasers Building a WSN Power
  Grid(NUCE Pakistan, IPSN 2014)
• A Real-time Auto-Adjustable Smart Pillow System
  for Sleep Apnea Detection and Treatment(Hongkong
  University, IPSN 2013)
• POEM Power-efficient Occupancy-based Energy
  Management System(UC Merced, IPSN 2013)

30
Assignment 1

• Magneto-Inductive NEtworked Rescue System
  (MINERS) Taking sensor networks
  underground(Oxford, IPSN 2012)
• Sensing Through the Continent Towards Monitoring
  Migratory Birds using Cellular Sensor Networks
  (Nebraska, IPSN 2012)
• Non-invasive Respiration Rate Monitoring Using a
  Single COTS TX-RX Pair (Aalto university, IPSN
  2014)
• Using wearable inertial sensors for posture and
  position tracking in unconstrained environments
  through learned translation manifolds (Edinburgh,
  IPSN 2013)

31
Other previous applications

• SLEWS A Sensorbased Landslide Early Warning
  System
• Power grid monitoring
• Embedded systems for energy-efficient buildings
  (eDIANA)
• Water quality monitoring
• Sensor networks for UV radiation control
• Precision agriculture and Agricultural
  applications
• Indoor environmental monitoring systems
• Damage detection in civil structures
• Participatory urban sensing

32
Other previous applications

• Micro-strain sensor network for monitoring
  shuttle launch
• Smart room using camera networks
• Active visitor guidance system
• Analysis of a habitat monitoring application
• Smart-tag based data dissemination
• Meteorology and Hydrology in Yosemite
• Continuous medical monitoring
• ZebraNet
• Virtual fences

33
Other previous applications

• SenseWeb
• CarTel
• Assisted Living
• Wearable wireless body area networks (Health
  care)
• Adaptive house
• House_n project
• Responsive Environments
• Counter-sniper system
• Self-healing land mines

34
Other previous applications

• Take a look at Libelium Top 50 applications
• These are some of the potential application areas
  for sensor actuator networks mostly non-military
• http//www.libelium.com/top_50_iot_sensor_applicat
  ions_ranking/

35
Project ExScal Concept of operation
Put tripwires anywherein deserts, other areas
where physical terrain does not constrain troop
or vehicle movementto detect, classify track
intruders Computer Networks 2004,
ALineInTheSand webpage, ExScal webpage
36
Envisioned ExScal customer application
Convoy protection
Detect anomalous activity along roadside
Hide Site
IED
Border control
Canopy precludes aerial techniques
Gas pipeline
Rain forest mountains water environmental
challenges
37
Application design choice

• One large powerful sensor vs many distributed
  sensors
• Distribution favours
• Robustness
• Overall coverage
• Overall cost
• Focus is on distributed computing and networking

38
ExScal summary

• Application has tight constraints of event
  detection scenarios long life but still low
  latency, high accuracy over large perimeter area
• Demonstrated in December 2004 in Florida
• Deployment area 1,260m x 288m
• 1000 XSMs, the largest WSN
• 200 XSSs, the largest 802.11b ad hoc network

39
One of ExScal sensors - PIR

• PIR is a differential sensor detects target as
  it crosses the beams produced by the optic

40
PIR signal Frequency
Human at 10 m
Car at 25m
Energy content for these two targets is in low
frequency band
41
Pir target detector
0-0.3 Hz
Person at 12 m
SUV at 25 m
Bandpass 2- 4 Hz
Bandpass 0.4- 2 Hz
42
A distributed classification approach

• Assume a dense WSN
• Concept each target type has unique influence
  field
• Multiple sensors which detect target coordinate,
  
• potentially each with multiple sensing
  modalities
• Classification is via reliable estimation of
  influence field size
• Computer Networks 2004

43
Further reading

• The Computer for 21st Century
• Next century challenges mobile networking for
  Smart Dust
• Connecting the physical world with pervasive
  networks
• D. Tennenhouse, Proactive computing
• Energy and performance considerations for smart
  dust
• Interesting Links on Sensor Networks
• www.wsnblog.com

44
Further reading

• Some good advice for graduate students
• Edsger Dijkstra, The Three Golden Rules for
  Successful Scientific Research
• Edsger Dijkstra, To a New Member of the Tuesday
  Afternoon Club
• Jim Kurose, Ten Pieces of Advice I Wish My PhD
  Advisor Had Given Me 
• Andre DeHon, Advice for Students Starting into
  Research
• S. Keshav, How to Read a Paper
• Philip W. L. Fong, How to Read a CS Research
  Paper?
• William Strunk Jr., E. B. White, The Elements of
  Style. (Recommended book on writing)