Hybrid Agricultural Development Support Communication Model (DSC) by Integrating Traditional Practices with ICT-Based and AI-Driven Innovations: A Review Study
DOI:
https://doi.org/10.71016/tp/ndpmz782Keywords:
Agricultural Development Support Communication, ICT in Agriculture, Artificial Intelligence, Hybrid Communication Model, Traditional Farming Knowledge, Precision AgricultureAbstract
Aim of the Study: This study aims to develop a communication strategy that integrates traditional methods, ICT-based technologies, and AI tools. An integrated communication strategy will increase the inclusive and efficient dissemination of agricultural knowledge.
Methodology: For analyzing contemporary communication techniques and their integration with old methods, a review of peer-reviewed articles was conducted using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, which promote a transparent and systematic approach to identifying, screening and selecting relevant studies. The PRISMA guidelines were carefully followed to reduce bias, which guaranteed that the findings were consistent and reliable.
Findings: Findings suggest that integration of modern technologies and old communication methods can be used to develop a hybrid communication model for the development of the agricultural sector. These strategies can assist farmers in gradually adopting AI models. To enhance the engagement of farmers by providing timely and tailored information, ICT-based tools such as mobile applications, SMS and interactive voice response (IVR) systems were found to be relevant.
Conclusion: In conclusion, better adoption of modern means of communication and information dissemination can be facilitated by an integrated approach where farmers' feedback is a part of creating solutions. This study also emphasizes the importance of DSC frameworks' implementation for legislators and extension programs. Agricultural support systems can become more sustainable, efficient, and inclusive by matching real-life knowledge with AI's analytical attributes.
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Copyright (c) 2025 Ayisha Hashim, Dr. Shazia Hashmat, Laiba Riasat (Author)

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