A Smart System for Optimal Harvest Crop Time Prediction Using Historical Climate and Market Price Data

  • Mrunalini Bhandarkar Poornima University
  • Nand kishor Gupta Department of Electrical & Electronics Engineering, Poornima University Jaipur, India
  • Basudha Dewan Department of Electronics and Communication Engineering, Manipal University Jaipur, India
  • Payal Bansal Department of Electronics & Communication Engineering, Poornima institute of Engineering and Technology Jaipur, Rajasthan, India
DOI: https://doi.org/10.19139/soic-2310-5070-3431
Keywords: Best harvesting time, Price estimation, Feature analysis, Deep learning, Climate change

Abstract

The most important function for the farmer cultivating more crops is to correctly predict the time and price for crop harvests. However, the existing methods' functions cannot predict the crop harvest time and prices accurately due to the fewer features they use. Therefore, in this existing research work, an innovative method known as the Hyena Zfnet Encoder Framework (HZEF), acting as the forecasting system for accurately estimating crop harvest prices and crop harvest times, has been proposed. The proposed method started by considering crop information, past climatic information, crop harvest, and crop harvest prices. Filtered images were employed for removing image noise obtained from the learned image representation. For selecting features, techniques were applied.Consequently, through the matching of the harvesting data and the climate change data, the harvesting season was projected, and the historical data on the prices was applied in deriving the probable prices. The voice assistant functionality proceeded to analyze the harvesting times and the prices associated with each tested agricultural produce. Finally, the new model attained the R-square value of 99.7%, the Root Mean Square Error value at 0.007%, and the computation time of 0.0003s compared to the conventional models. Keywords: Best harvesting time, Price estimation, Voice assistant, Feature analysis, Deep learning, Climate change
Published
2026-03-04
How to Cite
Mrunalini Bhandarkar, Nand kishor Gupta, Basudha Dewan, & Payal Bansal. (2026). A Smart System for Optimal Harvest Crop Time Prediction Using Historical Climate and Market Price Data. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-3431
Issue
Online First
Section
Research Articles
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