The SEAMONSTER Sensor Web: Lessons and Opportunities after One Year

1

The SEAMONSTER Sensor Web: Lessons and Opportunities after

One Year

DR Fatland1, MJ Heavner2,

E Hood2, C Connor2

1 Vexcel/Microsoft, 2 University Alaska Southeast

2

Outline

• What is SEAMONSTER?

• What are the goals of SEAMONSTER?

• How to encourage/facilitate collaboration

• Lessons Learned

3

SEAMONSTERSouthEastAlaskaMOnitoringNetwork forScienceTechnologyEducation and Research

We seek inspiration from the Tlingit legend of Gunakadeit, a seamonster who brought fish and furs to an impoverished village. The modern parallel is harvesting and distributing geospatial information via a sensor web to a world struggling with climate change.

Tlingit carvingof Gunakadeit

A modernseamonstertentacle

4

SEAMONSTER

• Scientifically Motivated Sensor Web

Technology Development

• Testbed Sensor Web

> Technology Collaborations

• Path for Technology Infusion

> Scientific Collaborations

5

Sensor Web Concept

The sensor web also encompasses a system-of-systems aspect, by virtue of the important fact that it interacts with a wide variety of external entities, including external systems and users.

6

Scientific Motivation, 1

Long term monitoring of the Juneau Icefield to observe watershed and ocean ecological impacts of glacial recession

50 km

7

Scientific Motivation, 2Detection of transient glacial lake outburst floods and observation for watershed impacts

Lake pre-drainage Lake post-drainage

8

Lemon Creek Watershed

The University of Alaska Southeast has (relatively) easy access to these areas. The initial watershed of interest is the Lemon Creek watershed (fed by Lemon Glacier) which can be entirely accessed via hiking.Lemon Glacier was monitored as part of IGY (1957-58) and is again being studied during IPY (2007-8).

5 km

10

Lemon Creek Sensor Web Met Station, Web Cam, Comm Hub

Lake Level, GPS,Geophone

Met Station, WebCamWater Qual,USGS Gauge

Water Qual

Communication between the nodes enables the Sensor Web.Ex: pressure transducer ( ) detects lake drainage and passes the message reconfiguring other sensor behavior.

11

Project Challenges

• Resource management– Power constrained (batteries and solar)– Also: storage, bandwidth, processing

• Different sampling requirements– Long term monitoring– Transient, rapidly evolving events

NEED SEMI-AUTONOMY or AGENTS

12

Goals of SEAMONSTER

• Event -> End User Sensor Web– Technology Testbed– Science– Technology Infusion– Education

13

Goals of SEAMONSTER

• Event -> End User Sensor Web– Technology Testbed– Science– Technology Infusion– Education

• How to?Collaboration

14

Example Collaboration, TechNeed: Software agents to reconfigure data acquisition based on observations and sensor web state.Specifically: If the lake pressure transducer measures a drop in lake level:1. Retask the camera to focus on the lakes2. Alert systems down the watershed to collect (relax power management)

Our Solution: Conceptual, minimal

implementation

15

Example Collaboration, Tech

Software agents: MACRO Project, NASA/AIST fundedLockheed Martin and Vanderbilt University

16

Example Collaboration, Tech

Software agents: MACRO Project, NASA/AIST fundedLockheed Martin and Vanderbilt University

17

Example Collaboration, Tech

Software agents: MACRO Project, NASA/AIST fundedLockheed Martin and Vanderbilt University

18

Example Collaboration, Science

19

Example Collaboration, Science

20

Example Collaboration, Science

21

Facilitating Collaboration: Project Wiki

22

Conclusions•SEAMONSTER is a testbed sensor web

•Compelling Technology and Science Use Case

•Lessons from Year 1:Facilitating collaboration

http://seamonsterak.com/

23

24

Platforms

Vexcel provided GeoBrick, Linux

Deployment-ready tmote

There are three different platforms in use, with relative computation, storage, and sensing capabilities as well as power requirements and cost.

Linksys NSLU-2, a UAStestbed platform, Linux

Tmote, tinyOS

25

Transducers

A combination of weather and water quality measurements provided the main data streams for SEAMONSTER in year 1.

26

Example Collaboration, Education

27

AcronymsACE ADAPTIVE Communications

Environment

CCM CORBA Component Model

CIAO Component Integrated ACE ORB

CORBA Common Object Request Broker Architecture

CoSMIC Component Synthesis with Model Integrated Computing

D & C Deployment and Configuration

DAnCE Deployment and Configuration Engine

GME Generic Modeling Environment

GNC Guidance, Navigation and Control

MDD Model Driven Design

OCL Object Constraint Language

OGC Open Geospatial Consortium

OMG Object Management Group

ORB Object Request Broker

PIM Platform Independent Model

PSM Platform Specific Model

PICML Platform Independent Component Modeling Language

QoS Quality of Service

RACE Resource Allocation and Control Engine

ReDAC Real-Time Deployment & Configuration

SA-POP Spreading Activation Partial Order Planner

SAS Sensor Alert Service

SOS Sensor Observation Service

SWE Sensor Web Enablement

TAO The ACE ORB

WNS Web Notification Service