MARC details
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| fixed length control field |
04236nam a22003377a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250715172614.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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250714b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
TUPM |
| Language of cataloging |
English |
| Transcribing agency |
TUPM |
| Modifying agency |
TUPM |
| Description conventions |
rda |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
BTH TK 870 |
| Item number |
C33 2025 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Cabrillas, Robin John T. |
| Relator term |
author |
| 245 ## - TITLE STATEMENT |
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| Title |
Mushkin: |
| Remainder of title |
Enhancing mushroom yield production via long short-term memory (lstm) with monitoring using yolo v8 for image processing in an iot-based urban agriculture/ |
| Statement of responsibility, etc. |
Robin John T. Cabrillas, Karl C. Cabulagan, Adrian C. Dela Cruz, Ayessa Denise S. Opanda, John Harold S. Ricafrente, and Maica V. Tameta.-- |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Manila: |
| Name of publisher, distributor, etc. |
Technological University of the Philippines, |
| Date of publication, distribution, etc. |
2025. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xvi, 217pages: |
| Dimensions |
29cm. |
| 336 ## - CONTENT TYPE |
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| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
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| Source |
rdacarrier |
| 500 ## - GENERAL NOTE |
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| General note |
Bachelor's thesis |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
College of Engineering.-- |
| Degree type |
Bachelor of science in electronics engineering: |
| Name of granting institution |
Technological University of the Philippines, |
| Year degree granted |
2025. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Includes bibliographic references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Millions of people in the Philippines continue to struggle with food insecurity. Growing<br/>mushrooms has become a popular way to increase food production in constrained areas<br/>through urban agriculture. This paper presents MushKin, an Internet of Things (IoT)-based<br/><br/>system that combines YOLO v8 with Long Short-Term Memory (LSTM) models for real-<br/>time monitoring and yield optimization in mushroom farming.<br/><br/>Environmental sensors are used by the system to track variables like light intensity,<br/>substrate wetness, CO2 levels, temperature, and humidity. While LSTM algorithms<br/>estimated ideal growing conditions, the ESP32 microcontroller gathers data to enable<br/>autonomous climate management. YOLO v8 also makes it easier to identify issues and<br/>recognize growth stages, which improves cultivation efficiency. To provide accessibility<br/>and user-friendliness, a web-based platform enables farmers to remotely monitor and<br/>control the system.<br/>MushKin was tested and evaluated at Bigay Buhay Multipurpose Cooperative (BBMC)<br/>to compare it with conventional farming practices. Results show that MushKin<br/>significantly increases sustainability, decreases labor-intensive monitoring, and improves<br/>yield prediction accuracy for five different mushroom species: oyster, milky, reishi,<br/>chestnut, and shiitake. The MushKin method has been shown to enhance productivity,<br/>according to statistical research, including T-tests.<br/>The precision and productivity of the Mushkin system were shown to be significantly<br/>higher than those of conventional mushroom cultivating techniques. Reliable real-time<br/>detection and measurement were made possible by the model's 0.707 precision, 0.637<br/>recall, and 0.673 [email protected], all of which were obtained using YOLOv8. When compared<br/><br/>to hand measurements, size estimations of cap area, length, and diameter for five different<br/>species of mushrooms consistently had percentage errors below 7%, demonstrating the<br/>consistency and quality of the approach.<br/>Additionally, significant increases were found when comparing the yields of Mushkin<br/>and conventional farming methods. Cap size, stem length, and total harvested weight all<br/>showed statistically significant changes, favoring tradition supported by Mushkin.<br/>Extended harvesting times were also made possible by Mushkin-enabled systems, which<br/>raised the overall yield. T-tests confirmed these results, confirming the system's ability to<br/>improve quality and productivity.<br/>This study demonstrates how AI-powered IoT solutions can be used in urban agriculture<br/>to support sustainable food production. MushKin offers an efficient and effective method<br/>of mushroom farming by combining automation, predictive analytics, and smart<br/>monitoring, opening the door for more extensive precision agriculture applications. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Ai-powered |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Long short-term (lstm) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Internet of things (iot) |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Cabulagan, Karl C. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Dela Cruz, Adrian C. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Opanda, Ayessa Denise S. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Ricafrente, John Harold S. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Ricafrente, John Harold S. |
| Relator term |
author |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Bachelor's Thesis COE |
| Suppress in OPAC |
No |