Transforming Agricultural Productivity with AI-Driven Forecasting: Innovations in Food Security and Supply Chain Optimization

Sambandh Bhusan Dhal, Debashish Kar · 2024 · Forecasting

Summary. AI-driven forecasting models, including machine learning and deep learning, transform agricultural productivity and food supply chains by enabling real-time crop monitoring and resource optimization. Integration of IoT, remote sensing, and blockchain technologies improves decision-making across European hydroponic systems and Southeast Asian aquaponics. AI also enhances food preservation through advanced processing techniques. However, data quality, model scalability, and prediction accuracy remain significant barriers, especially in data-poor regions. Success requires context-specific implementations and public-private collaboration.

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@article{dhal-2024-transforming-agricultural-productivity-ai-driven,
  title   = {Transforming Agricultural Productivity with AI-Driven Forecasting: Innovations in Food Security and Supply Chain Optimization},
  author  = {Sambandh Bhusan Dhal and Debashish Kar},
  journal = {Forecasting},
  year    = {2024},
  doi     = {10.3390/forecast6040046},
  url     = {https://doi.org/10.3390/forecast6040046}
}

TY  - JOUR
TI  - Transforming Agricultural Productivity with AI-Driven Forecasting: Innovations in Food Security and Supply Chain Optimization
AU  - Sambandh Bhusan Dhal
AU  - Debashish Kar
JO  - Forecasting
PY  - 2024
DO  - 10.3390/forecast6040046
UR  - https://doi.org/10.3390/forecast6040046
ER  - 

Details

DOI

10.3390/forecast6040046

Countries

Belgium, Netherlands, France, Germany, Thailand, Vietnam, Indonesia

Regions

Europe, Asia

Categories

agtech, food-systems, climate-and-environment

Added

2026-04-28