ViGuard : animal and human detection using machine learning / Giselle W. Cipriano, Trisha Nicole C. Dominguez, Hannah Isabel A. Magbanua, Vernadette D. Piedad.

By:

Cipriano, Giselle W

Contributor(s):

Material type: Text

TextManila : Technological University of the Philippines, 2022Description: xiii, 125 pages : illustrations ; 28 cm. + 1 CD-ROM (4 3/ in.)Subject(s):

LOC classification:

BTH T 58.5 C57 2022

Dissertation note: College of Science -- Bachelor of Science in Information Technology, Technological University of the Philippines, 2022. Abstract: This study developed the "ViGuard: Animal and Human Detection using Machine Learning." The system helps strengthen outdoor private residential property security. It also enhances home surveillance experience in detecting intruders. This study also provides awareness for the users in safeguarding their area and valuables. The system was developed with the use of Raspberry Pi, PIR Motion Sensors, USB Web Camera, and Servo Motor. It was tested to be satisfactorily working in terms of the presence of power supply, user alert reliability, motion detection with satisfactory accurate analysis, and also in terms of monitoring of response time in sending the email output and capturing the image of the detected intruder. The system was evaluated using a survey instrument with criteria based on the TUP Evaluation Instrument for Prototype Developed. Based on the evaluation results, the project was rated "Highly Acceptable" in terms of functionality, aesthetics, workability, durability, economy, safety, and saleability, which proves that the system is very functional and reliable.--Author's Abstract.

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Holdings
Item type	Current library	Shelving location	Call number	Status	Date due	Barcode
Bachelor's Thesis COS	TUP Manila Library	Thesis Section-2nd floor	BTH T 58.5 C57 2022 (Browse shelf(Opens below))	Not for loan		BTH0003434

Thesis (Undergraduate)

College of Science -- Bachelor of Science in Information Technology, Technological University of the Philippines, 2022.

Includes bibliographical references.

This study developed the "ViGuard: Animal and Human Detection using Machine Learning." The system helps strengthen outdoor private residential property security. It also enhances home surveillance experience in detecting intruders. This study also provides awareness for the users in safeguarding their area and valuables. The system was developed with the use of Raspberry Pi, PIR Motion Sensors, USB Web Camera, and Servo Motor. It was tested to be satisfactorily working in terms of the presence of power supply, user alert reliability, motion detection with satisfactory accurate analysis, and also in terms of monitoring of response time in sending the email output and capturing the image of the detected intruder. The system was evaluated using a survey instrument with criteria based on the TUP Evaluation Instrument for Prototype Developed. Based on the evaluation results, the project was rated "Highly Acceptable" in terms of functionality, aesthetics, workability, durability, economy, safety, and saleability, which proves that the system is very functional and reliable.--Author's Abstract.

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