000			02972nam a22003257a 4500
003			OSt
005			20250710102252.0
007
008			250710b |||||||| |||| 00| 0 eng d
040			_aTUPM _cTUPM _dTUPM _erda
050			_aBTH QA 76.9 _bD54 2024
100			_aDieto, Mary Jane G. _eauthor
245			_aDevelopment of an automated grass cutting machine for university field using internet of things/ _cMary Jane G. Dieto, Kimberly R. Ibanez, Maria Fe D. Pole, and Maria Flor D. Pole.--
260			_aManila: _bTechnological University of the Philippines, _c2024.
300			_axiii, 140pages: _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege of Industrial Technology.-- _bBachelor of engineering technology major in computer engineering technology: _cTechnological University of the Philippines, _d2024.
504			_aIncludes bibliographic references and index.
520			_aThis 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.
650			_aSmart lawn mower
650			_aIoT-based automation
650			_aRemote-controlled mower
700			_aIbanez, Kimberly R. _eauthor
700			_aPole, Maria Fe D. _eauthor
700			_aPole, Maria Flor D. _eauthor
942			_2lcc _cBTH CIT _n0
999			_c30247 _d30247