MoteTrack: Robust, Decentralized Approach to RF-based Location Tracking

Konrad Lorinz and Matt Welsh

Harvard University, Division of Engineering and Applied Sciences

Presented by: Sarat Chandra Subramaniam

Why Track? Awareness of context (localization) adds

tremendous value.

In sensor networks, physical location of event is very important.

Focus Application 1: Disaster Response

Focus Application 2: Emergency Medical Care

Tracking using radio: RADAR* Key idea: Signal Strength matching. Inputs:

Radio Map. Building Layout.

Offline cailbration: Tabulate <location, SS> information

Real-time location & tracking: Find best match to measured SS in table.

* Source: http://www.research.microsoft.com/~padmanab/talks/cambridge-radar-jan00.pdf

Why we can’t port this to Motes

Low device capability and memory size.

Dealing with failed nodes.

But why motes?

Inexpensive and low power Location detection can be incorporated to

sensor networks. Motes can be readily incorporated into

equipment and uniform.

The motes used

Beacon Mote Mobile Mote

Solution to outlined problems

Distribution of ‘reference signatures’ among beacon motes.

Decentralized location estimation protocol. Adaptive signature distance metric.

Putting it together Phase I: Initial set-up (performed once)

Placement of beacon motes at various locations. Construction of Signal Strength Map (reference

signature database). Distribution of these maps among beacon motes.

Phase II: Location Estimation (normal operation) Estimation of location of mobile motes.

Phase I: Initial Set-up

Phase II: Location Tracking

Accuracy

Closing Remarks Adds location tracking capabilities (alone)

to motes and can be re-programmed on the fly.

Requires mobile motes to be connected to a computer.

Many extensions can be thought about, wait till we get a mote with more memory on board.

References MoteTrack Project:

http://www.eecs.harvard.edu/~konrad/projects/motetrack

RADAR:

http://research.microsoft.com/~padmanab/