Performance Evaluation of an evolving data compression algorithm embedded into an OBD-II edge deviceShow others and affiliations
2020 (English)In: Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2020, p. 696-701Conference paper, Published paper (Refereed)
Abstract [en]
The new industrial revolution, known as industry 4.0, aims to create value throughout the product life cycle into all industries sectors. In the automotive industry perspective, data can be obtained throughout the life cycle of vehicles if they are appropriately instrumented with an On-Board Diagnostic scanner (OBD-II). Communications interfaces (3G/4G/LoraWan/Wi-Fi) assume essentials rules in order to relay all collected data to services in the cloud. Challenges emerge when using the Low Power, Wide-Area Network (LPWAN) protocols, as the case of LoRaWAN. This article aims to evaluate the feasibility of embedding a data compression algorithm driven by a light-weight evolving real-time approach in order to reduce the amount of data to be transmitted periodically. The proposal was embedded in a low-cost, low-power system on a chip microcontroller based on Edge OBD-II Freematics ONE+™. Results have shown the feasibility of the proposal and indicated compression rates of up to 98% without impact the primary operation of the edge device. © 2020 IEEE.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2020. p. 696-701
Keywords [en]
Connected Vehicles, Data Compress, Edge OBD-II, Evolving real-time algorithm, Industry 4.0, Automotive industry, Data compression, Life cycle, Low power electronics, System-on-chip, Wide area networks, Communications interface, Compression rates, Data compression algorithms, Industrial revolutions, Low-power systems, Microcontroller-based, On board diagnostics, Product life cycles, Internet of things
Identifiers
URN: urn:nbn:se:miun:diva-41508DOI: 10.1109/MetroInd4.0IoT48571.2020.9138270ISI: 000573618400134Scopus ID: 2-s2.0-85088872340ISBN: 9781728148922 (print)OAI: oai:DiVA.org:miun-41508DiVA, id: diva2:1536300
Conference
2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020
2021-03-102021-03-102021-04-28Bibliographically approved