Embedded computing is a sector in strong growth, driven by the increasing offer in the internet of things. Since position information is typically one of the intrinsic features of a sensory platform, the present work considers and analyzes the embedded lossless compression of localization data. A structural data scheme is proposed based on the number of occurrences of the independent coordinate components, named as µJSON. It is shown that, when considering a low-level language implementation on an embedded processor acquiring GNSS data, the proposed schema implies lower compression rates than its counterparts. An embedded test-bench platform is assembled, and several real case scenarios are considered for effectiveness and validation purposes.
Cite
[1] S. D. Correia, R. Perez, J. Matos-Carvalho and V. R. Q. Leithardt, "µJSON, a Lightweight Compression Scheme for Embedded GNSS Data Transmission on IoT Nodes," 2022 5th Conference on Cloud and Internet of Things (CIoT), 2022, pp. 232-238, doi: 10.1109/CIoT53061.2022.9766635.
[2] R. Perez, V. R. Q. Leithardt and S. D. Correia, "Lossless Compression Scheme for Efficient GNSS Data Transmission on IoT Devices," 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET), 2021, pp. 1-6, doi: 10.1109/ICECET52533.2021.9698642.