000			02343nam a22003257a 4500
003			OSt
005			20250710143110.0
008			250710b |||||||| |||| 00| 0 eng d
040			_aTUPM _bEnglish _cTUPM _dTUPM _erda
050			_aBTH QA 76 _bC78 2025
100			_aCruz, Wency Gabriel O. _eauthor
245			_aCrash kita: _bimplementing convolutional neural network for vehicular accident detection and assistance on tirona highway, bacoor city, cavite/ _cWency Gabriel O. Cruz, Joshua Louise B. Margallo, Maverick Rayne A. Ramos, Carl C. Senaris, and Sandryl A. Torres.--
260			_aManila: _bTechnological University of the Philippines, _c2025.
300			_ax, 140pages: _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege of Science.-- _bBachelor of science in computer science: _cTechnological University of the Philippines, _d2025.
504			_aIncludes bibliographic references and index.
520			_aIn the Philippines, traffic accidents are still a major issue, particularly along the Tirona Highway in Bacoor City, Cavite. The goal of this study, "CRASH KITA: Implementing Convolutional Neural Network for Vehicular Accident Detection and Assistance," is to develop a model that uses computer vision and IP cameras to automatically detect accidents. The researchers used two pre-trained YOLOv11 models to recognize different types of accidents. One focused on car-to-car collisions and reached around 84% mean average precision and 75% accuracy, while the other model included motorcycles with lower accuracy at 70%. The system includes a website made with PHP, Tailwind, and Bootstrap, where barangay authorities can view, confirm, manage accidents, and create reports. Testing showed that the system works well, but with limitations depending on the camera angle. Overall, “CRASH KITA” shows that using machine learning can help improve road safety monitoring by speeding up accident detection and response.
650			_aComputer vision
650			_aRoad safety
650			_a IP cameras
700			_aMargallo, Joshua Louise B. _eauthor
700			_aSenaris, Carl C. _eauthor
700			_aRamos, Maverick Rayne A. _eauthor
700			_aTorres, Sandryl A. _eauthor
942			_2lcc _cBTH COS _n0
999			_c30262 _d30262