Abstract
The LoRa technology enables long distance links with reduced power consumption at low cost, the main limitation being the low bandwidth that it offers. With LoRa, remote locations, like rural areas, can benefit from connectivity based services that would otherwise be impossible. In this work, we describe a LoRa architecture that can include generic external data sources using an MQTT-based interface. We particularly focus on audio sources aiming to two basic services: a voice messaging system that allows users who cannot read or write to send voice notes, and an audio compression service to extract the main features from the audio input to use it for developing intelligent ML-based audio analytics.
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Acknowledgments
This work has been partially supported by the Spanish Ministry of Science and Innovation, under the Ramon y Cajal Program (Grant No. RYC2018-025580-I) and under grants RTI2018-096384-B-I00, RTC-2017-6389-5 and RTC2019-007159-5, by the Fundación Séneca del Centro de Coordinación de la Investigación de la Región de Murcia under Project 20813/PI/18, and by the “Conselleria de Educación, Investigación, Cultura y Deporte, Direcció General de Ciéncia i Investigació, Proyectos AICO/2020”, Spain, under Grant AICO/2020/302.
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Nakamura, K., Hernández, D., Cecilia, J.M. et al. LADEA: A Software Infrastructure for Audio Delivery and Analytics. Mobile Netw Appl 26, 2048–2054 (2021). https://doi.org/10.1007/s11036-021-01747-z
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DOI: https://doi.org/10.1007/s11036-021-01747-z