2013
DOI: 10.4028/www.scientific.net/amm.284-287.2385
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Green Transport System: A Technology Demonstration of Adaptive Road Lighting with Giant Magnetoresistive Sensor Network for Energy Efficiency and Reducing Light Pollution

Abstract: To enhance energy efficiency and reduce light pollution of overnight road lighting in suburban traffic, we propose a novel green transport system based on giant magnetoresistive (GMR) sensors. The basic principle is to detect the perturbation to the earth magnetic field by a ferrous vehicle with GMR sensors. This system can switch on the road lighting to full illumination gradually before the motor vehicle arrives and dim it out after the vehicle leaves without the driver noticing. Based on a sparse suburban r… Show more

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Cited by 2 publications
(1 citation statement)
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“…With the help of dense wireless spintronic sensor nodes, the lighting system automatically increases the appropriate light intensity before the vehicle approaches and dims it out after the vehicle leaves. Such an intelligent road lighting system can achieve over 90% energy saving [175], leading to a green transport system. Besides, the city traffic data will be useful for bus management systems to design the bus routes and optimize the operation of the bus fleets in order to provide most efficient bus service [176].…”
Section: Smart Transport -All-round Traffic Monitoring and Management...mentioning
confidence: 99%
“…With the help of dense wireless spintronic sensor nodes, the lighting system automatically increases the appropriate light intensity before the vehicle approaches and dims it out after the vehicle leaves. Such an intelligent road lighting system can achieve over 90% energy saving [175], leading to a green transport system. Besides, the city traffic data will be useful for bus management systems to design the bus routes and optimize the operation of the bus fleets in order to provide most efficient bus service [176].…”
Section: Smart Transport -All-round Traffic Monitoring and Management...mentioning
confidence: 99%