Extending SMS Service Coverage in Rural Areas by using LoRa Communication Technology

Gimenez, Francisco; Zerbini, Carlos; Riva, Guillermo

doi:10.1109/tla.2020.9085273

Cited by 12 publications

(4 citation statements)

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“…From known rules, it is possible to actively generate learning about the experiences with the availability of large volumes of data to support the other decision-support processes. To synchronize each step and process, an infrastructure [ 67 , 68 , 69 ] computer network for remote communication between various devices, data collectors, cameras, and sensors is implemented.…”

Section: Methodsmentioning

confidence: 99%

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning

Silva

Mendes

Blas

et al. 2022

Sensors

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Due to the increasing urban development, it has become important for municipalities to permanently understand land use and ecological processes, and make cities smart and sustainable by implementing technological tools for land monitoring. An important problem is the absence of technologies that certify the quality of information for the creation of strategies. In this context, expressive volumes of data are used, requiring great effort to understand their structures, and then access information with the desired quality. This study are designed to provide an initial response to the need for mapping zones in the city of Itajaí (SC), Brazil. The solution proposes to aid object recognition employing object-based classifiers OneR, NaiveBayes, J48, IBk, and Hoeffding Tree algorithms used together with GeoDMA, and a first approach in the use of Region-based Convolutional Neural Network (R-CNN) and the YOLO algorithm. All this is to characterize vegetation zones, exposed soil zones, asphalt, and buildings within an urban and rural area. Through the implemented model for active identification of geospatial objects with similarity levels, it was possible to apply the data crossover after detecting the best classifier with accuracy (85%) and the kappa agreement coefficient (76%). The case study presents the dynamics of urban and rural expansion, where expressive volumes of data are obtained and submitted to different methods of cataloging and preparation to subsidize rapid control actions. Finally, the research describes a practical and systematic approach, evaluating the extraction of information to the recommendation of knowledge with greater scientific relevance. Allowing the methods presented to apply the calibration of values for each object, to achieve results with greater accuracy, which is proposed to help improve conservation and management decisions related to the zones within the city, leaving as a legacy the construction of a minimum technological infrastructure to support the decision.

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Section: Methodsmentioning

confidence: 99%

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning

Silva

Mendes

Blas

et al. 2022

Sensors

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“…Helmet-UAV off-body links for SaR [13], [14] Terrestrial links for mountain SaR [8] Localization and tracking [15] Emergency communications [9] Remote health monitoring [16] Extend the SMS coverage to unconnected areas [10] Human activity recognition [17] Industrial monitoring [11] UAV communications for swarm configurations [18] Wireless underground sensor networks [12] Recovery of incapacitated UAVs [19], [20] Smart cities…”

Section: This Workmentioning

confidence: 99%

Numerical and Experimental Characterization of LoRa-based Helmet-to-UAV links on Flat Lands

Bianco,

Mejia-Aguilar,

Marrocco

2022

Preprint

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The use of the LoRa communication protocol in a new generation of transceivers is attractive for search and rescue (SaR) procedures because they can operate in harsh environments covering vast areas while maintaining a low power consumption. The possibility of wearing helmets equipped with LoRa-radios and installing LoRa transceivers in unmanned aerial vehicles (UAVs) will accelerate the localization of the targets, probably unconscious. In this paper, the achievable communication ranges of such links are theoretically and experimentally evaluated by considering the possible positions of the helmet wearer (standing or lying) on a flat field, representing a simple SaR scenario. Simulations and experimental tests demonstrated that, for the standing position, the ground-bounce multi-path produces strong fluctuations of the received power versus the Tx-Rx distances. Such fluctuations can be kept confined within 100 m from the target by lowering the UAV altitude. Instead, for a more critical lying position, the received power profile is monotonic and nearly insensitive to the posture. For all the considered cases, the signal emitted by the body-worn transceiver can be exploited to localize the helmet wearer based on its strength, and it is theoretically detectable by the UAV radio up to 5 km on flat terrain.

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“…La cobertura de telefonía celular es deficiente en varias regiones rurales de Latinoamérica. En Gimenez et al [3] encontramos una propuesta para extender la cobertura de mensajes SMS en zonas rurales utilizando comunicaciones LoRa (Long Range9).…”

Section: Comunicacionesunclassified

Guest Editorial Special Issue on Embedded Systems

Micco

Vargas

Fierens

2020

IEEE Latin Am. Trans.

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Extending SMS Service Coverage in Rural Areas by using LoRa Communication Technology

Cited by 12 publications

References 0 publications

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning

Numerical and Experimental Characterization of LoRa-based Helmet-to-UAV links on Flat Lands

Guest Editorial Special Issue on Embedded Systems

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