@inproceedings{b3c98dc4472c4c33aa5bc15553168658,
title = "Energy-Aware Edge Intelligence for Dynamic Intelligent Transportation Systems",
abstract = "Intelligent Transportation System is propagating its roots among various researchers and smart city experts owing to the emergence of a wide range of applications or services, including connected cars. Next-generation tourism deliberately relies on its upcoming recommendation services that are fueled up with dynamic edge intelligence. This paper proposes an Energy-Aware Edge Intelligence (EAEI) framework for guiding tourists or automated vehicles in selecting air quality-aware tourism locations in an energy-efficient manner. EAEI collects the air quality parameter values through massive sensor networks; opts for an energy optimal prediction service to suggest air quality values; and, guides vehicles or tourists in cities. The proposed framework was evaluated at the IoT Cloud Research Lab and found to save over 90% of energy consumption in edge nodes. Besides, the article highlights the comprehensive need for the framework which inspires tens of thousands of solutions in the near future.",
keywords = "Automated vehicles, Edge intelligence, Intelligent Transportation System, IoT, Prediction, Services",
author = "Shajulin Benedict",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; 10th International Advanced Computing Conference, IACC 2020 ; Conference date: 05-12-2020 Through 06-12-2020",
year = "2021",
doi = "10.1007/978-981-16-0404-1_11",
language = "English",
isbn = "9789811604034",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "132--151",
editor = "Deepak Garg and Kit Wong and Jagannathan Sarangapani and Gupta, {Suneet Kumar}",
booktitle = "Advanced Computing - 10th International Conference, IACC 2020, Revised Selected Papers",
}
