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An Energy Efficient Localization Strategy for Outdoor Objects Based on Intelligent Light-Intensity Sampling

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Ubiquitous Intelligence and Computing (UIC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6406))

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Abstract

A simple and low cost strategy for implementing pervasive objects that identify and track their own geographical location is proposed. The strategy, which is not reliant on any GIS infrastructure such as GPS, is realized using an electronic artifact with a built in clock, a light sensor, or low-cost digital camera, persistent storage such as flash and sufficient computational circuitry to make elementary trigonometric computations. The object monitors the lighting conditions and thereby detects and tracks the sunrise and sunset times. By the means of a simple celestial model an estimate of the geographical position of the object can be made. An intelligent light sampling method is proposed allowing the object to sleep most of the time and hence save battery power. The strategy is energy efficient and the speed of convergence can be adjusted as a function of the energy consumed. Objects employing the method can therefore operate for long times without recharging their batteries. The strategy has applications in mobile sensor networks where nodes need to log geographical information, sensing equipment such as floating buoyancies, or pervasive technologies in need of geo-spatial information such as digital cameras, mobile devices, etc.

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Sandnes, F.E. (2010). An Energy Efficient Localization Strategy for Outdoor Objects Based on Intelligent Light-Intensity Sampling. In: Yu, Z., Liscano, R., Chen, G., Zhang, D., Zhou, X. (eds) Ubiquitous Intelligence and Computing. UIC 2010. Lecture Notes in Computer Science, vol 6406. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16355-5_17

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  • DOI: https://doi.org/10.1007/978-3-642-16355-5_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16354-8

  • Online ISBN: 978-3-642-16355-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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