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Reducing Power Consumption of Weather Stations for Landslide Monitoring

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Information Technology in Geo-Engineering (ICITG 2019)

Abstract

Among different natural disasters, landslides are widespread in hilly areas. For landslide monitoring, one needs to collect data via weather stations about the prevailing weather and soil properties at remote locations that are prone to landslides. Due to the non availability of grid power, one may need to depend upon large sized solar panels and batteries if the weather station’s power requirements are high. The primary objective in this paper is to apply software and hardware methods to reduce the power requirements of a weather station for landslide monitoring. In an experiment, three different microcontroller implementations were used as part of a weather station for evaluating weather and soil properties: AT-mega2560 (Mega), ATmega328p (Uno), and ATmega328p (low power). The Mega and Uno microcontrollers exist as part of the popular Arduino open source electronic prototyping platform. In the low power microcontroller, we simplified the power circuit and closed pins on the microcontroller that were not being used at different times. All three microcontrollers were connected to an identical set of sensors in identical weather stations and run at the same voltage setting of 5 V at the same time. Results revealed that Mega, while awake, consumed 140 mA current. In sleep mode, it consumed 40 mA current. Similarly, the Uno, while awake, consumed 50 mA current. In sleep mode, it consumed 40 mA current. However, the low power microcontroller consumed only 10 mA when awake and less than 0.25 mA when sleeping. We highlight the implications of this research for developing low cost and low power landslide monitoring solutions in the world.

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Correspondence to Varun Dutt .

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Pathania, A. et al. (2020). Reducing Power Consumption of Weather Stations for Landslide Monitoring. In: Correia, A., Tinoco, J., Cortez, P., Lamas, L. (eds) Information Technology in Geo-Engineering. ICITG 2019. Springer Series in Geomechanics and Geoengineering. Springer, Cham. https://doi.org/10.1007/978-3-030-32029-4_13

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  • DOI: https://doi.org/10.1007/978-3-030-32029-4_13

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  • Print ISBN: 978-3-030-32028-7

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