toward scalable activity recognition for sensor networks

MITSHUBISHI ELECTRIC RESEARCH LABORATORIESCambridge, Massachusetts

Toward Scalable Activity Recognition for Sensor Networks

Christopher R. WrenMERL Research

Emmanuel Munguia TapiaMIT House_n

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Changes for the better

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Office

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Office

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Office

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A sensor network for building context.

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Second Implementation

Emmanuel’s MERL internship Summer 2005

Wireless Motion DetectorWires for Power

155 installed and operational

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Why Smarter Buildings?

• Safety & Security– Unusual Activity Detection– Economical Context Sensing– Tuned Escape Routes

• Eldercare – Activity Monitoring– Awareness

• Energy Efficient Buildings– Lighting– HVAC– Integrated building systems

• Socially–Aware Buildings– Presence– Availability– Awareness

• Entertainment• Elevator Demand Prediction• Retail

– Predict densities– monitor reaction to displays

• Industrial Process– Ergonomics– Safety– Efficiency

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How do you build a sensor network?

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Photo courtesy of Kathy Ryall

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LoCA27 nodes1 receiver

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today155 nodes7 receivers

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How do you use a sensor network?

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SARSEN: Scalable Activity Recognition for Sensor Networks

•Locality of processing–Abstract information early–Reduce communication–Small data means small CPU

•Locality of Context–Build form small components–Small areas are more portable–Independent of context–A hallway is a hallway

•Build understanding–Tracking is not possible–Find consistent explanations–Abstractions reduce space

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Behavior Hierarchy

Action

Activity

Movement

Motion no context, no temporal information

limited local context, no temporal information

more context,significant temporal structure

activities in global context

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Behavior Hierarchy

Action

Activity

Movement

Motion

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Hardware

• 155 sensors, public spaces of a 2000m2 office building floor.• 7 weeks of data and counting• 3x106 observed motion events• ~90-150 people• Collaborative environment• Many kinds of spaces:

– laboratories – cubicles – offices – meeting rooms

• frequent visitors

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Behavior Hierarchy

Action

Activity

Movement

Motiontopology

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Automatically Recovered Topology

TR2005-003: “Similarity-based Analysis for Large Networks of Ultra-Low Resolution Sensors.” To Appear Pattern Recognition Special Issue on Similarity-Based Pattern Recognition

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Behavior Hierarchy

Action

Activity

Movement

Motion

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Movement

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Turn Movement

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Walk Movement

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Still Movement

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Behavior Hierarchy

Action

Activity

Movement

Motion

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Activities

• Temporal Structure: Markov Chains• Trained from hand-written examples

– Visit: stop, stand around, start– Meet: exit, exit, exit.

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Meet Activity

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Visit Activity

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Behavior Hierarchy

Action

Activity

Movement

Motion

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Next Generation

>3 years on AA!802.15.4 radio

Easy to manufacture

Jonathan WesthuesDarren Leigh

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Summary

•Buildings as experts in themselves!

•Cheap to install and operate•Potentially cheap…

…also in terms of privacy

•Aware buildings can be safer, more efficient, richer.

•Hierarchical Behavior Elements…not Tracks

SARSEN

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Thank You!

Christopher R. Wrenwren@merl.com

Emmanuel Munguia Tapiaemunguia@mit.edu

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Why Motion Detectors?

They’re cheaper, require less bandwidth, less computation, less memory, but also….

Cameras provide a greater potential for abuse when you vary the intentionality of the person in control of the technology.

Dimensional Metaethics, Carson ReynoldsAnalytic framework for ethical comparison

TR2006-005: Worse is Better for Ambient Sensing, Pervasive 2006 Workshop on Privacy, Trust and

Identity Issues for Ambient Intelligence

toward scalable activity recognition for sensor networks

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