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undergraduate thesis
Udaljeni sustav praćenja broja ljudi u zatvorenom prostoru koristeći Raspberry Pi i obradu slike
2023. urn:nbn:hr:200:467206
Radić, Domin
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Visual Computing

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Radić, D. (2023). Udaljeni sustav praćenja broja ljudi u zatvorenom prostoru koristeći Raspberry Pi i obradu slike (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:467206

Radić, Domin. "Udaljeni sustav praćenja broja ljudi u zatvorenom prostoru koristeći Raspberry Pi i obradu slike." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:467206

Radić, Domin. "Udaljeni sustav praćenja broja ljudi u zatvorenom prostoru koristeći Raspberry Pi i obradu slike." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:467206

Radić, D. (2023). 'Udaljeni sustav praćenja broja ljudi u zatvorenom prostoru koristeći Raspberry Pi i obradu slike', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 09 February 2025, https://urn.nsk.hr/urn:nbn:hr:200:467206

Radić D. Udaljeni sustav praćenja broja ljudi u zatvorenom prostoru koristeći Raspberry Pi i obradu slike [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2023 [cited 2025 February 09] Available at: https://urn.nsk.hr/urn:nbn:hr:200:467206

D. Radić, "Udaljeni sustav praćenja broja ljudi u zatvorenom prostoru koristeći Raspberry Pi i obradu slike", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:200:467206

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TitleUdaljeni sustav praćenja broja ljudi u zatvorenom prostoru koristeći Raspberry Pi i obradu slike
Title (english)Remote system for counting the number of people in an indoor space using Rasprerry Pi and image processing
AuthorDomin Radić
MentorIrena Galić (mentor)
MentorMarin Benčević (sumentor)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Visual Computing)
Osijek
Defense date and country2023, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Data Processing
Abstract
Ovaj završni rad istražuje razvoj i implementaciju udaljenog sustava za praćenje broja ljudi u zatvorenim prostorima primjenom tehnologije umjetne inteligencije. Temelj rada je korištenje YOLO algoritma konvolucijske neuronske mreže za preciznu detekciju i praćenje ljudi u stvarnom vremenu. Rad se također bavi usporedbom različitih metoda detekcije, uključujući R-CNN pristupe, kako bi se istaknule prednosti YOLO algoritma. Osim toga, rad se fokusira na praktičnu primjenu sustava pomoću Raspberry Pi platforme, pristupačnog i energetski učinkovitog računalnog rješenja. Razvijen je Python kod za implementaciju sustava, omogućujući udaljeno praćenje ljudi putem Raspberry Pi uređaja. Kroz ovaj rad, demonstrirano je kako umjetna inteligencija, posebno YOLO algoritam, može biti učinkovito korištena za rješavanje stvarnih problema u praćenju ljudi u zatvorenim prostorima. Integracija s Raspberry Pi platformom čini ovaj sustav pristupačnim i praktičnim za različite primjene, pridonoseći sigurnosti i učinkovitosti u različitim okruženjima.
Abstract (english)
This final thesis explores the development and implementation of a remote system for monitoring the number of people in enclosed spaces using artificial intelligence technology. The foundation of the work is the utilization of the YOLO convolutional neural network algorithm for precise real- time detection and tracking of people. The thesis also compares different detection methods, including R-CNN approaches, to highlight the advantages of the YOLO algorithm. Furthermore, the thesis focuses on the practical application of the system using the Raspberry Pi platform, an affordable and energy-efficient computing solution. Python code has been developed for system implementation, enabling remote monitoring of people through Raspberry Pi devices. Through this work, it is demonstrated how artificial intelligence, particularly the YOLO algorithm, can be effectively used to address real-world problems in monitoring people in enclosed spaces. Integration with the Raspberry Pi platform makes this system accessible and practical for various applications, contributing to safety and efficiency in different environments.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:467206
Study programmeTitle: Undergraduate University Study Programme
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektrotehnike i informacijske tehnologije (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka elektrotehnike i informacijske tehnologije)
Type of resourceText
File originBorn digital
Access conditionsOpen access
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Created on2023-10-19 15:50:23