Abstract
This article provides the results of the multimedia data transmission parameters research by LoRa using, in particular the results of images and voice transmission using the fragment of the model network in the Internet of Things Laboratory SPbSUT. During the series of experiments there was noticed the LoRa radio modules performance variation of different parameters (Bandwidth, Spreading Factor and Coding Rate), which have affected on the time and quality of image transmission. For image compression were used JPEG and JPEG 2000 methods, which have allowed to achieve an acceptable compression and image reconstruction while transmitting in the low-speed network. In the course of the experiment, the images were transferred from a camera mounted on a quadrocopter at distance of several kilometers. We considered such parameters as the time of data transfer, packet loss, estimation of the images quality obtained on the basis of subjective and objective methods. For voice compression, the A-law method was used, which allowed to compress the frame size by 4 times. Experiments of real-time speech transmission were conducted in different languages and evaluated by the experts. During the results analyzing there were defined the lower subjective score for Arabic, and the higher scores for English and Vietnamese. In conclusion, this article provides the results of the quantitative and qualitative dimensions evaluation and presents directions for the further research.
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The publication was financially supported by the Ministry of Education and Science of the Russian Federation (the Agreement number 02.a03.21.0008) and RFBR according to the research project No. 16-37-00215 mol_a “Biodriver”.
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Kirichek, R., Pham, VD., Kolechkin, A., Al-Bahri, M., Paramonov, A. (2017). Transfer of Multimedia Data via LoRa. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. ruSMART NsCC NEW2AN 2017 2017 2017. Lecture Notes in Computer Science(), vol 10531. Springer, Cham. https://doi.org/10.1007/978-3-319-67380-6_67
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