Intelligent Environments1 Computer Science and Engineering University of Texas at Arlington.

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Presentation transcript:

Intelligent Environments1 Computer Science and Engineering University of Texas at Arlington

Intelligent Environments2 Sensors Quantities to be sensed Sensor types Sensor characteristics Sensor installation Sensor interfacing and control Smart floor

Intelligent Environments3 Quantities to be Sensed Strain and pressure Position, direction, distance and motion Light and radiation Temperature Sound

Intelligent Environments4 Quantities to be Sensed Solids, liquids and gases Moisture (humidity) Flow Liquid acidity/alkalinity Air and water quality Smoke

Intelligent Environments5 Sensor Types Strain and pressure Load Pressure Applications Floors, doors, windows Scales

Intelligent Environments6 Sensor Types Position, direction, distance and motion Accelerometer Motion Applications Security Locator, tracking

Intelligent Environments7 Sensor Types Light, radiation and temperature Low-profile ceiling camera Wireless camera Light Radiation Temperature Applications Security, location, tracking Health safety Energy efficiency

Intelligent Environments8 Sensor Types Sound Wireless microphone Applications Security Volume control Speech recognition

Intelligent Environments9 Sensor Types Solids, liquids and gases Humidity Rain Carbon dioxide pH Flow Applications Pool maintenance Sprinkler efficiency Security and health monitoring

Intelligent Environments10 Sensor Characteristics Operating temperature Thermal sensitivity Non-linearity and hysteresis Excitation voltage and impedance Current and power Noise Example: load sensor Example: motion sensor

Intelligent Environments11 Sensor Installation Placement Environment Interference Aesthetics Power 120VAC, wired DC, battery, solar Combined with data lines (CAT5)

Intelligent Environments12 Sensor Interfacing and Control Interfacing Wireless (50MHz, 900MHz, 2.4GHz, …) Serial (9/25 wire), CAT5 (8 wire), phone (4 wire) Coax, fiber optic Bus (networking) Control Identification Calibration Parameter settings “Smart” features

Intelligent Environments13 Application: Smart Floor Orr and Abowd, “The Smart Floor,” Georgia Tech Identify users based on their footsteps Not intended to be a standalone system Load sensors Vdc excitation voltage 2.2 mV output per volt of excitation Sampled 300 times per second

Intelligent Environments14 Application: Smart Floor Footstep described by 10 features Profile mean, deviation, length, area, maximum and minimum Nearest neighbor for classification Results seem independent of footwear 93% recognition rate

Intelligent Environments15 My SmartHome Floor plan Landscaping Materials Sensors Placement, power, interfacing Reconfigurable Networking Overall smart architecture

Intelligent Environments16 My SmartHome

Intelligent Environments17 My SmartHome Sensors Bedrooms Bathrooms Kitchen Family room Garage Doors and windows Floors, walls, roof Utility (HVAC, water heater, washer/dryer) Yard