Wireless Sensor Networks for Habitat Monitoring

Slides:



Advertisements
Similar presentations
C TinyOS Platforms Panel: MICAz1UC Berkeley / Feb 11, 2005 Basic Anatomy of a Crossbow Node.
Advertisements

GDI Sensor Net RIP GDI Data Analysis Robert Szewczyk December 20, 2002.
Telos Fourth Generation WSN Platform
Is There Light at the Ends of the Tunnel? Wireless Sensor Networks for Adaptive Lighting in Road Tunnels IPSN 2011 Sean.
1 S4: Small State and Small Stretch Routing for Large Wireless Sensor Networks Yun Mao 2, Feng Wang 1, Lili Qiu 1, Simon S. Lam 1, Jonathan M. Smith 2.
SELF-ORGANIZING MEDIA ACCESS MECHANISM OF A WIRELESS SENSOR NETWORK AHM QUAMRUZZAMAN.
Sensor Network Applications for Environmental Monitoring Carla Ellis SAMSI 11-Sept-07.
CSE 5392By Dr. Donggang Liu1 CSE 5392 Sensor Network Security Introduction to Sensor Networks.
Fresh from the boat: Great Duck Island habitat monitoring
Wireless Sensor Networks: An overview and experiences. Matthew Grove PEDAL Seminar Series, January 9th 2008.
Topology Control Presenter: Ajit Warrier With Dr. Sangjoon Park (ETRI, South Korea), Jeongki Min and Dr. Injong Rhee (advisor) North Carolina State University.
PERFORMANCE MEASUREMENTS OF WIRELESS SENSOR NETWORKS Gizem ERDOĞAN.
Wireless Sensor Networks for Habitat Monitoring
Wireless Ad-Hoc Sensor Networks for Monitoring Endangered Plant Species Edo Biagioni University of Hawaii at Manoa Also Kim Bridges, Brian Chee, Anders.
What is a Wireless Sensor Network (WSN)? An autonomous, ad hoc system consisting of a collective of networked sensor nodes designed to intercommunicate.
1 Enviromatics Environmental Sensor Networks Environmental Sensor Networks Вонр. проф. д-р Александар Маркоски Технички факултет – Битола 2008 год.
The Mote Revolution: Low Power Wireless Sensor Network Devices
1 Introduction to Wireless Sensor Networks. 2 Learning Objectives Understand the basics of Wireless Sensor Networks (WSNs) –Applications –Constraints.
Habitat monitoring on Great Duck Island Robert Szewczyk Joe Polastre Alan Mainwaring John Anderson David Culler University of California, Berkeley June.
Crossbow Open Mote Developments Crossbow Technology.
GDI 2003: status report Robert Szewczyk Joe Polastre Alan Mainwaring David Culler NEST Retreat, Jan 15, 2004.
Mica: A Wireless Platform for Deeply Embedded Networks Jason Hill and David Culler Presented by Arsalan Tavakoli.
Wireless Sensor Networks for Habitat Monitoring
Reconfigurable Sensor Networks Chris Elliott Honours in Digital Systems Charles Greif and Nandita Bhattacharjee.
Habitat monitoring on Great Duck Island Robert Szewczyk Joe Polastre Alan Mainwaring John Anderson David Culler ACM SenSys’04 November 5, 2004.
The Mote Revolution: Low Power Wireless Sensor Network Devices
4/30/031 Wireless Sensor Networks for Habitat Monitoring CS843 Gangalam Vinaya Bhaskar Rao.
1 In-Situ Habitat and Environmental Monitoring Alan Mainwaring, Joe Polastre and Rob Szewczyk Intel Research - Berkeley Lablet.
GDI Environmental monitoring app Data & lessons learned Robert Szewczyk Joe Polastre Alan Mainwaring David Culler January 15, 2002.
Wireless Sensor Networks for Habitat Monitoring Jennifer Yick Network Seminar October 10, 2003.
Intel ® Research mote Ralph Kling Intel Corporation Research Santa Clara, CA.
Wireless Sensor Networks
Spring 2000, 4/27/00 Power evaluation of SmartDust remote sensors CS 252 Project Presentation Robert Szewczyk Andras Ferencz.
MICA: A Wireless Platform for Deeply Embedded Networks
Wireless Sensor Networks for Habitat Monitoring Reviewed by Li Zhang Courtesy: Prof. Parashar, Rutgers University.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2007 (TPDS 2007)
Sensor Network Applications. Introduction –Habitat and environmental monitoring represent essential class of sensor network applications by placing numerous.
Institut for Technical Informatics 1 Thomas Trathnigg Towards Runtime Support for Energy Awareness in WSNs Towards Runtime Support for Energy Awareness.
Mobile Relay Configuration in Data-Intensive Wireless Sensor Networks.
Security Patterns in Wireless Sensor Networks By Y. Serge Joseph October 8 th, 2009 Part I.
Introduction to Wireless Sensor Networks
An Ultra Low Power System Architecture for Sensor Network Applications Mark Hempstead, Nikhil Tripathi, Patrick Mauro, Prof. Gu-Yeon Wei, Prof. David Brooks.
788.11J Presentation “ Fire Wx Net ” Presented by Engy Ashraf Yehia.
Wireless Sensor Networks for Habitat Monitoring Intel Research Lab EECS UC at Berkeley College of the Atlantic.
1 Extended Lifetime Sensor Networks Hong Huang, Eric Johnson Klipsch School of Electrical and Computer Engineering New Mexico State University December.
System Architecture Directions for Networked Sensors Jason Hill, Robert Szewczyk, Alec Woo, Seth Hollar, David Culler, Kris Pister Presented by Yang Zhao.
Wireless Sensor Networks with Motes Gurdip Singh and Sumeet Gujrati.
College of Engineering Grid-based Coordinated Routing in Wireless Sensor Networks Uttara Sawant Major Advisor : Dr. Robert Akl Department of Computer Science.
Energy and Latency Control in Low Duty Cycle MAC Protocols Yuan Li, Wei Ye, John Heidemann Information Sciences Institute, University of Southern California.
Network and Systems Laboratory nslab.ee.ntu.edu.tw Branislav Kusy, Christian Richter, Wen Hu, Mikhail Afanasyev, Raja Jurdak, Michael Brunig, David Abbott,
Power and Control in Networked Sensors E. Jason Riedy and Robert Szewczyk Presenter: Fayun Luo.
System Architecture Directions for Networked Sensors Jason Hill, Robert Szewczyk, Alec Woo, Seth Hollar, David Culler, Kris Pister Presenter: James.
Presented by : Rashmy Balasubramanian.  Aimed at saving endangered species of turtle in Ontario  The WSN gathers information regarding risks factors.
SATIRE: A Software Architecture for Smart AtTIRE R. Ganti, P. Jayachandran, T. F. Abdelzaher, J. A. Stankovic (Presented by Linda Deng)
Adaptive Sleep Scheduling for Energy-efficient Movement-predicted Wireless Communication David K. Y. Yau Purdue University Department of Computer Science.
Design Constraint Presentation Team 5: Sports Telemetry Device.
Sensor Network Applications
Link Layer Support for Unified Radio Power Management in Wireless Sensor Networks IPSN 2007 Kevin Klues, Guoliang Xing and Chenyang Lu Database Lab.
Introduction to Wireless Sensor Networks
Wireless Sensor Networks
Wireless Sensor Networks for Habitat Monitoring Alan Mainwaring, Joseph Polastre, Robert Szewczyk, and David Culler Intel Research Lab. / UCBerkely Seo,
- Pritam Kumat - TE(2) 1.  Introduction  Architecture  Routing Techniques  Node Components  Hardware Specification  Application 2.
Wireless Sensor Networks
Weather Station Weather station design for measuring
Data Collection and Dissemination
CS6501/ECE6501 IoT Sensors and Systems
Wireless Sensor Networks
An Ultra Low Power System Architecture for Sensor Network Applications
Review: Analysis of Wireless Sensor Networks for Habitat Monitoring Polastre, Szewczyk, Mainwaring, Culler Review by Nate Ota CS294 8/28/03.
Data Collection and Dissemination
Presentation transcript:

Wireless Sensor Networks for Habitat Monitoring Alan Mainwaring1 Joseph Polastre2 Robert Szewczyk2 David Culler1,2 John Anderson3 1: Intel Research Laboratory at Berkeley 2: University of California, Berkeley 3: College of the Atlantic

Introduction Application Driven System Design, Research, and Implementation Parameterizes Systems Research: Localization Calibration Routing and Low-Power Communications Data Consistency, Storage, and Replication How Can All of these Services and Systems Be Integrated into a Complete Application?

Great Duck Island Breeding area for Leach’s Storm Petrel (pelagic seabird) Ecological models may use multiple parameters such as: Burrow (nest) occupancy during incubation Differences in the micro-climates of active vs. inactive burrows Environmental conditions during 7 month breeding season Clearly, such a model would consider multiple parameters. We’re focusing on ones in-and-around the underground nests (burrows) where eggs are laid. p.s. If anyone asks why they are called ‘petrels’, here’s the story: The birds are planktonic feeders and spend hours during the day hovering above the ocean’s surface picking bits of planton out with their feet. Sailors being a superstitious bunch likened this to walking on water, something for which St. Peter was famous.

Application > 1000 ft

Sensor Network Solution

Outline Application Requirements Habitat Monitoring Architecture Sensor Node Power Management Sensor Patch Transit Network Wide Area Network and Disconnected Operation Sensor Data System Analysis Real World Challenges

Application Requirements Sensor Network Longevity: 7-9 months Space: Must fit inside Small Burrow Quantity: Approximately 50 per patch Environmental Conditions Varying Geographic Distances Inconspicuous Operation Reduce the “observer effect” Data As Much as Possible in the Power Budget Iterative Process

Application Requirements Predictable System Behavior Reliable Meaningful Sensor Readings Multiple Levels of Connectivity Management at a Distance Intermittent Connectivity Operating Off the Grid Hierarchy of Networks / Data Archiving

Habitat Monitoring Architecture Transit Network Basestation Gateway Sensor Patch Patch Network Base-Remote Link Data Service Internet Client Data Browsing and Processing Sensor Node Pictorial outline

Sensor Node: Mica Hardware Software Atmel AVR w/ 512kB Flash 916MHz 40kbps Radio Range: max 100 ft Affected by obstacles, RF propogation 2 AA Batteries Operating: 15mA Sleep: 50mA Software TinyOS / C Applications Power Management Digital Sensor Drivers Remote Management & Diagnositcs

Sensor Node: Power Management AA Batteries have ~2500 mAh capacity Mica consumes 50mA in sleep = 1.2 mAh/day Mica Expected Lifetime Node Activity Days Years Mica Always On 7 0.1 Mica Always Sleeping 2081 5.7 Expected Lifetime (days) Number of Operating Hours per Day

Sensor Node: Power Management Operation nAh Transmitting a packet 20.000 Receiving a packet 8.000 Radio Listening for 1ms 1.250 Operating Sensor for 1s (analog) 1.080 Operating Sensor for 1s (digital) 0.347 Reading a Sample from the ADC 0.011 Flash Read Data 1.111 Flash Program/Erase Data 83.333 Target Lifetime: 7-8 months Power Budget: 6.9mAh/day Questions: What can be done? How often? What is the resulting sample rate? Operation Operating Time per Day Duty Cycle Sample Rate Always Sleep 24 hours 0% 0 samples/day + mCPU on 52 minutes 3.61% + Radio On (Listen) 28 minutes 1.94% + Sample All Sensors 21 minutes 1.45% 630 samples/day + Transmit Samples 20 minutes 1.38% 600 samples/day

Sensor Node: Mica Weather Board Digital Sensor Interface to Mica Onboard ADC Designed for Low Power Operation Individual digital switch for each sensor Designed to Coexist with Other Sensor Boards Hardware “Enable” Protocol to obtain exclusive access to connector resources Meeting the guidelines for env monitoring system

Sensor Node: Mica Weather Board Accuracy Interchange Max Rate Startup Current Photo N/A 10% 2000 Hz 10 ms 1.235 mA I2C Temp 1 K 0.2 K 2 Hz 500 ms 0.150 mA Pressure 1.5 mbar 0.5% 10 Hz 0.010 mA Press Temp 0.8 K 0.24 K Humidity 2% 3% 500 Hz 0.775 mA Thermopile 3 K 5% 200 ms 0.170 mA Thermistor 5 K 0.126 mA Work through power budget Energy per sample vs current x sample Important to Biologists Affect Power Budget

Sensor Node: Packaging Parylene: Great but sucks for connectors or exposed sensors (non soldered connections) Acrylic Size matters Ventilation Parylene Sealant Acrylic Enclosures

Sensor Patch Network Nodes: Transmit Only Network Single Hop Repeaters Approximately 50 Half in burrows, Half outside RF unpredictable Burrows Obstacles Drop packets or retry? Transmit Only Network Single Hop Repeaters 2 hop initially Most Energy Challenged Adheres to Power Budget

Transit Network Two implementations Antennae Linux (CerfCube) Relay Mote Antennae No gain antenna (small) Omnidirectional Yagi (Directional) Implementation of transit network depends on: Distance Obstacles Power Budget Duty cycle of sensor nodes dictates transit network duty cycle Same power budget could apply here using sophisticated scheme using traffic for entire patch, or you can engineer around it… Provision node adequately

Transit Network Renewable Energy Sources CerfCube needs 60Wh/day Assuming an average peak of 1 direct sunlight hour per day: Panel must be 924 in2 or 30” x 30” for a 5” x 5” device! A mote only needs 2Wh per day, or a panel 6” x 6”

Base Station / Wide Area Network Disconnected Operation and Multiple Levels of State Laptop DirecWay Satellite WAN PostgreSQL 47% uptime Redundancy and Replication Increase number of points of failure Remote Access Physical Access Limited Keep state all areas of network Resiliency to Disconnection Network Failures Packet Loss Potential Solution: Keep Local Caches Synchronization Challenges and Accomplishments: CoLo analogy etc

Sensor Data Analysis Tell story about john anderson

Sensor Data Analysis Outside Burrow Inside Burrow

System Analysis Power Management Goals Calculated 7 months, expect 4 months Battery half-life at 1.2V Predictable Operation Observed per node constant throughput, % loss 739,846 samples as of 9/23, network is still running Battery Consumption at Node 57 Packet Throughput and Active Nodes

Real World Experiences System and Sensor Network Challenges Low Power Operation (low duty cycle) Affects hardware and software implementation Multihop Routing Allows bigger patches Route around physical obstacles Must have ~1% operating duty cycle In Situ Retasking/Reconfiguration Let biologists interactively change data collection patterns Not Implemented due to conservative energy implementation Lack of Physical Access Remote management Disconnected operation Fault tolerance Reliance on other people and their networks Physical Size of Device Affects microcontroller selection, radio, practical choice of power sources

Real World Experiences Failures Extended Loss of Wide Area Connectivity Unreliable Reboot Sequence in Windows Solderless Connections Fail (expansion/contraction cycles) Node Attrition (Petrels are not mote neutral) Environmental Conditions (50km/hr gale winds knock over equipment) Lack of post-mortem diagnositics

Conclusions First long term outdoor wireless sensor network application Application driven sensor network design Defines requirements and constraints on core system components (routing, retasking, fault tolerance, power management)

Backup Slides

Mote 18: Outside

Mote 26: Burrow 115a

Mote 53: Burrow 115b

Mote 47: Burrow 88a

Mote 40: Burrow 88b

Mote 39: Burrow 84