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Blockchain Integrated Machine Learning for Training Autonomous Cars

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Hybrid Intelligent Systems (HIS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 420))

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Abstract

Autonomous cars have always been fascinating towards the coming generation of we techies and since then training them has also been an important concern. That’s when we can consider Machine Learning integrated with Blockchain to provide high security to build this model. Machine Learning and Blockchain are two very innovative domains of computing. There has been a constant improvement in neural networks in past years. Since Artificial Intelligence-based learning algorithms are taken into account and a drive towards the training of autonomous cars is seen. Here, we are going to train a single car with great precision and accuracy, and then this alone trained car will share the data with all the other cars in its network. Hence, all of them will be sharing a particular network and the data will be exchanged. Now, when it comes to the learning of cars, we will be creating a blockchain network that will connect every car for that particular company. In this way, while in a dynamic condition also, the cars will stay connected with each and every one and the data will be exchanged. So, the training will be done using Deep Neural Networks and since the data transfer and weights update requires high security, we will be using Blockchain. For example, if any car gets hit by an accident or due to any possible fatal breakdown or due to any changes in the route or signals (government laws), this data will be transmitted to each other car in this network. Hence every car will get its weight updated to avoid or tackle the situation. This in the end will decrease the computational time and increase the measure of safety and well-being.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India

    Dhruv Agrawal & Amit Kumar Tyagi

  2. Department of Management Studies, Vaish College of Engineering, Rohtak, India

    Rohit Bansal

  3. Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, Tamilnadu, India

    Terrance Frederick Fernandez

  4. Centre for Advanced Data Science, Vellore Institute of Technology, Chennai, Tamilnadu, India

    Amit Kumar Tyagi

Authors
  1. Dhruv Agrawal
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  2. Rohit Bansal
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  3. Terrance Frederick Fernandez
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  4. Amit Kumar Tyagi
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Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Campus Centre de Créteil, Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

  3. Department of Computer Science, Università degli Studi di Milano, Milan, Milano, Italy

    Vincenzo Piuri

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  5. University of Bari, Bari, Italy

    Gabriella Casalino

  6. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

  7. Ontario Tech University, Oshawa, ON, Canada

    Patrick Hung

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Agrawal, D., Bansal, R., Fernandez, T.F., Tyagi, A.K. (2022). Blockchain Integrated Machine Learning for Training Autonomous Cars. In: Abraham, A., et al. Hybrid Intelligent Systems. HIS 2021. Lecture Notes in Networks and Systems, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-030-96305-7_4

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