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Intelligence Enabled Research pp 1–5Cite as

Vehicle Pollution Detection from Images Using Deep Learning

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1109))

Abstract

Vehicle pollution is one of the biggest contributors among the Air pollution sources. The main objective of this study is, to identify the pollutant vehicle from on-road real time images. We propose a novel image-based transfer learning approach by identifying the emission from the vehicle. These images can be captured from other nearby or adjacent vehicles or from traffic control units. Once the pollutant vehicle is detected, this information can be used for notification, pollution control, and surveillance in future as well. Our deep learning-based method involves Inception-v3, and it can work under any weather and light conditions with varying environments.

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Author information

Authors and Affiliations

  1. Jadavpur University, Kolkata, 700032, India

    Srimanta Kundu & Ujjwal Maulik

Authors
  1. Srimanta Kundu
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  2. Ujjwal Maulik
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Corresponding author

Correspondence to Srimanta Kundu .

Editor information

Editors and Affiliations

  1. RCC Institute of Information Technology, Kolkata, India

    Siddhartha Bhattacharyya

  2. Indian Statistical Institute, Kolkata, India

    Sushmita Mitra

  3. Visva-Bharati University, Santiniketan, India

    Paramartha Dutta

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Kundu, S., Maulik, U. (2020). Vehicle Pollution Detection from Images Using Deep Learning. In: Bhattacharyya, S., Mitra, S., Dutta, P. (eds) Intelligence Enabled Research. Advances in Intelligent Systems and Computing, vol 1109. Springer, Singapore. https://doi.org/10.1007/978-981-15-2021-1_1

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