Enhancing Agricultural Communication: Converting Circulars into Video Content Using MERN and Python


Authors : Kajal Dubey; Prachi Bisht; Pratik Dey; Rishita Jayant; Samyak Jain

Volume/Issue : Volume 10 - 2025, Issue 4 - April


Google Scholar : https://tinyurl.com/y3b3f4xn

Scribd : https://tinyurl.com/d76ur2cb

DOI : https://doi.org/10.38124/ijisrt/25apr976

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Abstract : The agriculture sector relies extensively on timely and effective communication for the exchange of vital information between farmers. Traditional text-based circulars are time- consuming due to low literacy levels, linguistic barriers, and limited access. In this research, an argument is made for a web platform built on the MERN stack (MongoDB, Express.js, React.js, Node.js) to create an interactive user interface, with Python as an additional feature to automate video creation. The platform utilizes Natural Language Processing (NLP), Text-to-Speech (TTS), and video rendering technologies to create accessible and interactive video content. A pilot trial of 150 farmers from different regions showed enhanced comprehension and engagement, suggesting the platform's capability to bridge the communication gap in the agriculture sector.

References :

  1. R. Singh and P. Gupta, "ICT in Agriculture: Bridging the Gap," Journal of Rural Development, vol. 15, no. 3, pp. 123–136, 2023.
  2. FAO, "Digital Agriculture: Tools for the Future," FAO Publications, 2022.
  3. OpenAI, "Applications of AI in Rural Communication," AI Journal, vol. 10, no. 4, pp. 56–67, 2024.
  4. K. Patel and A. Mehta, "Artificial Intelligence for Agricultural Knowledge Dissemination," International Journal of Agricultural Research, vol. 18, no. 2, pp. 89–102, 2023.
  5. J. Brown et al., "AI-Powered Video- Based Learning for Small-Scale Farmers," Agricultural Informatics Journal, vol. 7, no. 1, pp. 45–58, 2023.
  6. M. Zhang, "Challenges and Opportunities in Digital Agricultural Communication," Rural Tech Review, vol. 11, no. 3, pp. 78–90, 2022.
  7. S. Verma and R. Kumar, "Multimodal AI Systems for Farmer Advisory Services," Journal of Smart Agriculture, vol. 5, no. 4, pp. 112–130, 2023.

The agriculture sector relies extensively on timely and effective communication for the exchange of vital information between farmers. Traditional text-based circulars are time- consuming due to low literacy levels, linguistic barriers, and limited access. In this research, an argument is made for a web platform built on the MERN stack (MongoDB, Express.js, React.js, Node.js) to create an interactive user interface, with Python as an additional feature to automate video creation. The platform utilizes Natural Language Processing (NLP), Text-to-Speech (TTS), and video rendering technologies to create accessible and interactive video content. A pilot trial of 150 farmers from different regions showed enhanced comprehension and engagement, suggesting the platform's capability to bridge the communication gap in the agriculture sector.

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