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A DIGITAL QUALITY ASSESSMENT OF BAMBOOSHOOTS.AI FOR HARVEST AND PEST DETECTION

Journal: Proceedings on Engineering Sciences (Vol.6, No. 4)

Publication Date:

Authors : ;

Page : 1489-1496

Keywords : Bambooshoots.AI; Disease Prediction; Web Application; Usability; Software Quality;

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Abstract

This research offered an in-depth evaluation of "BambooShoots.AI," a platform aiding bamboo cultivators in harvest timing and pest detection. Using a quantitative method, it incorporated Lund A.M.'s USE Questionnaire (2001) and usage data analysis to gauge user satisfaction and effectiveness. The majority of participants were mid-aged cultivators, providing insights on system usefulness, ease of use, learning, and overall satisfaction. Demographics showed a primary user base of 35-44-year-olds with balanced gender representation and a high rate of Bachelor's degree holders, highlighting the platform's broad appeal. BambooShoots.AI was noted for its significant usability, scoring well in all evaluated aspects. The study suggested enhancing the interface for older users, continuous feedback integration for improvement, and specialized training programs. It emphasized the need for accessible and inclusive design, aligning with evolving user needs. BambooShoots.AI emerged as a potent, user-focused tool in agricultural technology, pointing to its potential for wider adoption and development in the farming community, and affirming its role as a critical asset in modern agriculture.

Last modified: 2024-12-09 16:27:32