Post-Harvest Technologies and Automation: Al-Driven Innovations in Food Processing and Supply Chains DOI Open Access
Biswa Ranjan Das,

Azmirul Hoque,

Subhra Saikat Roy

et al.

International Journal of Scientific Research in Science and Technology, Journal Year: 2025, Volume and Issue: 12(1), P. 183 - 205

Published: Jan. 26, 2025

The rapid advancements in artificial intelligence (AI) and automation are transforming post-harvest technologies, offering innovative solutions to improve food quality, safety, supply chain efficiency. This paper reviews the role of AI-driven innovations processing logistics, with a focus on automation, predictive analytics, quality control. AI such as machine learning, computer vision, IoT integration, optimizing processes like sorting, grading, packaging, microbial detection, reducing waste extending shelf life. Moreover, AI-powered robotics smart warehouses streamlining transportation inventory management, enhancing operational integration demand forecasting optimization is further improving traceability, minimizing disruptions, environmental impact. Despite promising potential, challenges data system cost barriers, regulatory concerns remain. future technologies presents opportunities for continued innovation, deep IoT, global scalability, pathways sustainable systems. concludes by discussing impact sector its potential drive more efficient, resilient, chains worldwide.

Language: Английский

Post-Harvest Technologies and Automation: Al-Driven Innovations in Food Processing and Supply Chains DOI Open Access
Biswa Ranjan Das,

Azmirul Hoque,

Subhra Saikat Roy

et al.

International Journal of Scientific Research in Science and Technology, Journal Year: 2025, Volume and Issue: 12(1), P. 183 - 205

Published: Jan. 26, 2025

The rapid advancements in artificial intelligence (AI) and automation are transforming post-harvest technologies, offering innovative solutions to improve food quality, safety, supply chain efficiency. This paper reviews the role of AI-driven innovations processing logistics, with a focus on automation, predictive analytics, quality control. AI such as machine learning, computer vision, IoT integration, optimizing processes like sorting, grading, packaging, microbial detection, reducing waste extending shelf life. Moreover, AI-powered robotics smart warehouses streamlining transportation inventory management, enhancing operational integration demand forecasting optimization is further improving traceability, minimizing disruptions, environmental impact. Despite promising potential, challenges data system cost barriers, regulatory concerns remain. future technologies presents opportunities for continued innovation, deep IoT, global scalability, pathways sustainable systems. concludes by discussing impact sector its potential drive more efficient, resilient, chains worldwide.

Language: Английский

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