000 02488nam a22002417a 4500
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005 20251111093653.0
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041 _aengtag
050 _aT9 G83 2025
082 _a.
100 1 _a Guatno, Cris Paul V.; Obillo, Dean Emmanuel A.; Taguinod, Jovan E.
245 _aHarnessing AI for agriculture utilizing color-condition camera sensors and thermal imaging drones for crop color-condition detection and predictive yield analysis with inventory management system
264 1 _a.
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300 _bCapstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
336 _2text
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337 _2 unmediated
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338 _2volume
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505 _aABSTRACT: Technological Gaps and Challenges for Agriculture in the Philippines Such advancements may be relevant to other countries as well but we should also consider that there is a greater potential of technology adoption with these purposes than ever before, especially those small-scale farmers from local areas who have less accessibility on technological trendsetting. In this study, the researchers attempt to solve these problems using Artificial Intelligence (AI) in order to improve crop monitoring and predictive yield amidst the climate change. Color-condition using Convolutional Neural Networks (CNN) with 76.97% accuracy and predictive analysis by Artificial Neural Network (ANN). This optimizes the timing of planting and harvest, depending on the combination of this algorithm. This study aims to capture the crops maturity through color-condition detection and gather data for yield analysis by capturing the thermal temperature of the soil. The AI can identify crop health and maturity issues, such as nutrient deficiencies. It will also enhance crop yield predictions by inputting information such as soil types, temperature, fertilizers used, and weather conditions. Additionally, this study implements a partial website system to serve as an interface for the images captured by the camera attached to the drone. This website also showcases the goals of the proposed study. Furthermore, it includes a crop stock and inventory management feature to reduce paper usage and promote an eco-friendly environment. Through this innovation, local farmers can adapt to new technologie
526 _aF
655 _aacademic writing
942 _2lcc
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999 _c37057
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