HarvestHub: Enhancing Bidding Systems for Small-Scale Farmers
Year: 2025
Type: article
Abstract: The rapid advancement of digital technologies has transformed agricultural marketplaces, offering innovative solutions to improve market access and pricing mechanisms for small-scale farmers. This paper explores existing digital solutions in agricultural trade, with a particular focus on AI-driven bidding systems that enhance transparency, efficiency, and fairness in pricing. Traditional agricultural supply chains often involve multiple intermediaries, leading to reduced profitability for farmers. By leveraging machine learning algorithms for price prediction and blockchain for secure transactions, modern bidding platforms facilitate direct engagement between farmers and buyers, ensuring competitive pricing and reducing exploitation. This paper examines various digital tools, their impact on agricultural commerce, and the challenges associated with their adoption, such as technological accessibility, data reliability, and farmer participation. It also highlights future research directions to improve scalability, affordability, and usability of AI-powered bidding systems, aiming to create a more equitable and sustainable agricultural marketplace.
Author: Aadhi Lakshmi M R, Adithyan Suresh Kumar, Dan Mody Mathew, Evana Ann Benny, Resmipriya M G
Institution: Amal Jyothi College of Engineering
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W6930886587
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