Intelligent Energy Management for Body Sensor Networks WTBU Emerging Markets & Innovation Leo Estevez, Ph.D.

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Presentation transcript:

Intelligent Energy Management for Body Sensor Networks WTBU Emerging Markets & Innovation Leo Estevez, Ph.D.

Making Wireless Natural & Synthetic Body Networks Self Preservation –Invisible (Battery) –Predictive (Memory) Energy Systems –Ambient –Kinetic –Potential Energy Management –Sensory –Memory

Ambient Energy Systems

Making Wireless Natural Ambient Energy Systems

Making Wireless Solar Ambient Energy Solar (1000W/m 2 ) –GaAs 247mW/cm 2 (IMEC) –PV-TV 3.8W/ft 2 Picture Courtesy of UTD

Making Wireless Thermal Ambient Energy Head –30 uW/cm2 Wrist –100uW Research/Pictures from IMEC

Making Wireless RF Ambient Energy GSM-900 2mW HF RFID 16mW 0.8in (20mm) Mini-Reader Module

Kinetic Energy Systems

Making Wireless Natural Kinetic Energy Systems

Making Wireless Translational Kinetic Energy Shoe –20mW Vibration –uWs Picture Courtesy of UTD Lab

Making Wireless Rotational Kinetic Energy Watch –uWs Shoe –3.2W Picture/Research from NYU

Potential Energy Systems

Making Wireless Natural Potential Energy Systems

Making Wireless Voltage Potential Energy Standby –MSP nA Active –MSP uW/MHz –ARM Cortex - 450uW/MHz

Making Wireless RF Potential Energy Selectivity Collision Avoidance

Sensory Energy Management

Making Wireless Natural Sensory Energy Management

Making Wireless Location Sensors A-GPS –Seconds Zigbee –Milliseconds Enabler IIA-GPS 31 x 46 x 3.1 mm

Making Wireless Activity Sensors Accelerometers –500uA Altimeters –5uA

Memory Energy Management

Making Wireless Natural Memory Energy Management Fast/Working Slow/Learning

Making Wireless Working Memory Energy Management FRAMEEPROMFlash Nonvolatile PrincipleFerroelectricityCharge Storage Read Cycle nsec200nsec90nsec Internal Program Voltage 5V/3.3V18V12V Write Cycle85-110nsec5msec1sec Fast/Working –Low Power/Capacity Slow/Learning –High Power/Capacity

Making Wireless Learning Memory Energy Management PowerRelative Location & State Descriptions On Time 5uAPressure Changed -> Accelerometer ON 90% 500uAX Steps From Y Entity -> Zigbee ON 9% 15mAAround Entity X -> Recognition Processor ON.9% 80mALearned Event Detected -> GSM ON.1% SEND PREDICTION ERROR

Making Wireless eZ430-RF2480 Demonstration Kit USB or Battery Powered ZigBee 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 $99 (US$)