Intelligent Energy Management for Body Sensor Networks

WTBU Emerging Markets & Innovation

Leo Estevez, Ph.D.

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Natural & Synthetic Body Networks

• Self Preservation– Invisible (Battery)– Predictive (Memory)

• Energy Systems– Ambient– Kinetic– Potential

• Energy Management– Sensory– Memory

Ambient Energy Systems

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Natural Ambient Energy Systems

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Solar Ambient Energy

• Solar (1000W/m2)– GaAs

• 247mW/cm2 (IMEC)

– PV-TV• 3.8W/ft2

Picture Courtesy of UTD

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Thermal Ambient Energy• Head

– 30 uW/cm2

• Wrist– 100uW

Research/Pictures from IMEC

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RF Ambient Energy• GSM-900 (2W)

• @1m 2mW

• HF RFID (200mW)• @1cm 16mW

0.8in (20mm)

0.8in (20mm)

Mini-Reader Module

Kinetic Energy Systems

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Natural Kinetic Energy Systems

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Translational Kinetic Energy

• Shoe– 20mW

• Vibration– uWs

Picture Courtesy of UTD Lab

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Rotational Kinetic Energy

• Watch– uWs

• Shoe– 3.2W

Picture/Research from NYU

Potential Energy Systems

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Natural Potential Energy Systems

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Voltage Potential Energy• Standby

– MSP430 - 800 nA

• Active– MSP 430 - 65uW/MHz– ARM Cortex - 450uW/MHz

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RF Potential Energy

• Selectivity• Collision Avoidance

Sensory Energy Management

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Natural Sensory Energy Management

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Location Sensors

• A-GPS– Seconds

• Zigbee– Milliseconds

Enabler IIA-GPS31 x 46 x 3.1 mm

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Activity Sensors

• Accelerometers– 500uA

• Altimeters– 5uA

-1.5

-1

-0.5

0

0.5

1

1.5

2

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73

Memory Energy Management

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Natural Memory Energy Management

Fast/Working Slow/Learning

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Working Memory Energy Management

FRAM EEPROM Flash

Nonvolatile Principle Ferroelectricity Charge Storage Charge Storage

Read Cycle 85 -110nsec 200nsec 90nsec

Internal Program Voltage

5V/3.3V 18V 12V

Write Cycle 85-110nsec 5msec 1sec

• Fast/Working– Low Power/Capacity

• Slow/Learning – High Power/Capacity

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Learning Memory Energy Management

Power Relative Location & State Descriptions

OnTime

5uA Pressure Changed ->Accelerometer ON

90%

500uA X Steps From Y Entity ->

Zigbee ON

9%

15mA Around Entity X ->

Recognition Processor ON

.9%

80mA Learned Event Detected ->

GSM ON

.1%

SEND PREDICTION ERROR

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eZ430-RF2480 Demonstration Kit

USB or Battery PoweredZigBee Processor

MSP430F2274(backside)

Evaluate Z-Accel today with comprehensive USB-based wireless development tool

The eZ430-RF2480 Demo Kit: Allows fast evaluation of Z-Accel Interfaces an MSP430F2274 to the CC2480 Demonstrates the Simple API command interface Available now for only $99 (US$)