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Application for Mood Detection of Students Using TensorFlow and Electron JS

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Machine Learning and Big Data Analytics (ICMLBDA 2022)

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 401))

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Abstract

We all depended on online platforms to learn and explore things during the pandemic. All our college/school activities are performed virtually through online applications like Zoom, Google meets, and Microsoft teams. Even though we have many applications, we do not have any specific application for tracking the listener’s mood. Usually, these applications consume lots of data while switching on the video; the speaker has no idea whether the listener is listening or just left the place, turning off their camera. To overcome this problem, we developed an electron desktop application that runs parallelly along with other applications to track the listener’s mood and helps in limiting the consumption of data. To create this application, we used the TensorFlow model, electron js, Axios for posting into the database, node express for backend, face API.js, and webcam js to access the image. So basically, it runs on the user end and makes API calls to the backend.

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Author information

Authors and Affiliations

  1. Department of Information Technology, MVGR College of Engineering (A), Vizianagaram, Andhra Pradesh, India

    Marada Srinivasa Rao

  2. Department of Computer Science and Engineering, Vignan’s Institute of Information Technology (A), Visakhapatnam, Andhra Pradesh, India

    Pasala Sandhya

  3. Department of Computer Science and Engineering, Lendi Institute of Engineering and Technology (A), Vizianagaram, Andhra Pradesh, India

    Bosubabu Sambana

  4. Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India

    Bosubabu Sambana & Priyanka Mishra

  5. Department of Computer Science and Engineering, Indian Institute of Information Technology Kota, Jaipur, Rajasthan, India

    Bosubabu Sambana

Authors
  1. Marada Srinivasa Rao
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  2. Pasala Sandhya
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  3. Bosubabu Sambana
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  4. Priyanka Mishra
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science & Engineering, Indian Institute of Technology Patna, Patna, Bihar, India

    Rajiv Misra

  2. Cardiff University, Cardiff, UK

    Rana Omer

  3. Dept. of EE Engineering, University of London, London, UK

    Muttukrishnan Rajarajan

  4. Dept. of ECE, National University of Singapore, Singapore, Singapore

    Bharadwaj Veeravalli

  5. Dept. of Computer Science, Central University of Rajasthan, Tehsil Kishangarh, Rajasthan, India

    Nishtha Kesswani

  6. Dept. of CSE, Indian Institute of Information Technology, Kota, Jawahar Lal Nehru Marg, Rajasthan, India

    Priyanka Mishra

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Srinivasa Rao, M., Sandhya, P., Sambana, B., Mishra, P. (2023). Application for Mood Detection of Students Using TensorFlow and Electron JS. In: Misra, R., Omer, R., Rajarajan, M., Veeravalli, B., Kesswani, N., Mishra, P. (eds) Machine Learning and Big Data Analytics. ICMLBDA 2022. Springer Proceedings in Mathematics & Statistics, vol 401. Springer, Cham. https://doi.org/10.1007/978-3-031-15175-0_19

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