Development of an automated grass cutting machine for university field using internet of things/ Mary Jane G. Dieto, Kimberly R. Ibanez, Maria Fe D. Pole, and Maria Flor D. Pole.--

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Dieto, Mary Jane G [author]

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Material type: Text

TextPublication details: Manila: Technological University of the Philippines, 2024.Description: xiii, 140pages: 29cmContent type:

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BTH QA 76.9 D54 2024

Dissertation note: College of Industrial Technology.-- Bachelor of engineering technology major in computer engineering technology: Technological University of the Philippines, 2024. Summary: This study develops an IoT-based automated grass-cutting machine to improve efficiency and safety in maintaining the TUP-Manila field. Traditional methods require manual labor, which is time-consuming and poses safety risks. The problems related to noise pollution and gasoline-powered mower environmental damage along with intensive manual procedures continue to persist as significant problems. Existing solutions, such as solar and automated grass cutters, have limitations in range, features, and reliance on manual operation. The study aims to develop a grass-cutting machine for TUP-Manila field with the following objectives: (1) design a system that cuts and collects grass while incorporating safety features such as a front blade cover and IoT-based camera monitoring; (2) develop a mobile-controlled system using agile methodology; (3) test speed, cutting precision, grass collection, and battery life under operating conditions; and (4) evaluate the system based on ISO/IEC 25010:2023 standards. The development process followed an agile methodology, consisting of planning, design, development, testing, deployment, and review phases. The development followed an agile methodology with phases of planning, design, development, testing, deployment, and review. The testing showed the prototype's speed had minor discrepancies (76 m/min with 5.13% and 84 m/min with 1.18% deviation). Cutting precision showed a 13.33% difference in grass height, while the collector bin gathered 0.45 kg (75.86%) and 0.65 kg (79.07%) of grass from 76 m and 84 m, respectively. Evaluation of the system based on quality criteria yielded a grand weighted mean of 4.36 on a 5-point Likert scale in evaluations.

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Holdings
Item type	Current library	Shelving location	Call number	Copy number	Status	Date due	Barcode
Bachelor's Thesis CIT	TUP Manila Library	Thesis Section-2nd floor	BTH QA 76.9 D54 2024 (Browse shelf(Opens below))	c.1	Not for loan		BTH0006281

Bachelor's thesis

College of Industrial Technology.-- Bachelor of engineering technology major in computer engineering technology: Technological University of the Philippines, 2024.

Includes bibliographic references and index.

This study develops an IoT-based automated grass-cutting machine to improve efficiency
and safety in maintaining the TUP-Manila field. Traditional methods require manual labor,
which is time-consuming and poses safety risks. The problems related to noise pollution
and gasoline-powered mower environmental damage along with intensive manual
procedures continue to persist as significant problems. Existing solutions, such as solar and
automated grass cutters, have limitations in range, features, and reliance on manual
operation. The study aims to develop a grass-cutting machine for TUP-Manila field with
the following objectives: (1) design a system that cuts and collects grass while
incorporating safety features such as a front blade cover and IoT-based camera monitoring;
(2) develop a mobile-controlled system using agile methodology; (3) test speed, cutting
precision, grass collection, and battery life under operating conditions; and (4) evaluate the
system based on ISO/IEC 25010:2023 standards. The development process followed an
agile methodology, consisting of planning, design, development, testing, deployment, and
review phases. The development followed an agile methodology with phases of planning,
design, development, testing, deployment, and review. The testing showed the prototype's
speed had minor discrepancies (76 m/min with 5.13% and 84 m/min with 1.18% deviation).
Cutting precision showed a 13.33% difference in grass height, while the collector bin
gathered 0.45 kg (75.86%) and 0.65 kg (79.07%) of grass from 76 m and 84 m,
respectively. Evaluation of the system based on quality criteria yielded a grand weighted
mean of 4.36 on a 5-point Likert scale in evaluations.

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