Data Driven Scene Classification to Analyze ADAS
Priyadarshini R1, S Kayalvizhi2, A Geetha3, Premkumar T4
1Priyadarshini R, Department of Computer Science and Engineering, Easwari Engineering College, Chennai (Tamil Nadu), India.
2Prof. S. Kayalvizhi, Department of Computer Science and Engineering, Easwari Engineering College, Chennai (Tamil Nadu), India.
3A Geetha, Department of Computer Science and Engineering, Easwari Engineering College, Chennai (Tamil Nadu), India.
4Premkumar T, System Developer Functions, ADAS AEG, WABCO Technology Center India.
Manuscript received on 02 July 2019 | Revised Manuscript received on 12 August 2019 | Manuscript Published on 27 August 2019 | PP: 117-119 | Volume-8 Issue-2S4 July 2019 | Retrieval Number: B10200782S419/2019©BEIESP | DOI: 10.35940/ijrte.B1020.0782S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In every sphere of life Big Data will be transformative. Data Visualization and Analytics plays an important role in decision making in various sectors. In autonomous vehicles data from various sensors and RADAR are stored in data logger, which is huge in size. To evaluate the performance of specific sensor manually is tedious task. This paper proposes an idea to create an interactive GUI framework to analyze the vehicle data and sensor data using big data visualization method. The framework contains various plots and plots are made interactive to analyze data in depth for all the scenarios of ADAS. It can be used to analyze the behavior of the vehicle at each instance of time interactively and time synchronized image frames are also incorporated with framework to see behavior of the plots. The paper proposes a Framework to analyze the huge amount vehicle data and sensor data which can be used to analyze the behavior of ADAS application.
Keywords: Data Visualization, ADAS, Framework, CAN, Dash Python.
Scope of the Article: Classification