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 information Real-time location & tracking: Find best match to measured SS in table. * Source:
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: cts/motetrack cts/motetrack RADAR: