Smart University Laboratory

A tétel rövid nézete
dc.contributor.advisorAlmusawi, Husam Abdulkareem
dc.contributor.authorAwad, Noureldin Elsadig Hassan
dc.contributor.departmentDE--Műszaki Kar
dc.date.accessioned2025-12-16T16:35:45Z
dc.date.available2025-12-16T16:35:45Z
dc.date.created2025-11-23
dc.description.abstractThis thesis describes the design, programming, implementation of a complex Smart Electrical University Laboratory System, a single digital environment which is configured to transform the management of laboratory by overcoming the slowness of the conventional paper-based processes. The hybrid architecture of the system is its key innovation: The Smart Inventory System and Face Recognition Attendance System are implemented as a secure web-based application that runs locally over the Wi-Fi network of the lab and allows comfortable and device-independent access to all smartphones, tablets, or computers located inside the lab and the data privacy of the system is ensured by the lack of contacts with the world as well as by the absence of service usage on cloud systems. Conversely, both the Voice Assistant and Lab Schedule Manager are native host applications , and use its increased processing power to perform real-time, resource-intensive tasks, audio processing, and the ability to serve a PyQt5-based GUI-rendering to the display, functions that could not be performed on the original Raspberry Pi 3 because of the extreme limitations in memory and processing power. Facial Recognition system FaceNet, which is developed with a small CNN model (FaceNet) through DeepFace, offers high-precision, low-latency recognition in controlled lab conditions, and the system has high-quality error recovery algorithms. The smart integration is another strength factor that improves resiliency of the system: the voice assistant offers contextual technical support, where speech requests are dynamically integrated in the inventory system interface, and the attendance data is automatically aligned with the inventory activities to monitor the equipment usage. The Lab Schedule Manager is an independent Pi 4 application that offers a powerful real-time scheduling interface that allows access to the lab table and laboratory sessions with no conflicts using a dedicated desktop application. This design with a centralized data storage and user interface through a secure and open web interface and delegated real-time and high-load tasks to host applications in the Pi 4 provides a scalable, reliable, and economical ecosystem. The development plan was focused on realism and stability: the complete system was initially created, debugged and tested on a Windows PC to fix the complicated Python library incompatibility issues and to guarantee the functionality. This was then put into final code that was fully tested and optimized and run on Raspberry Pi 4, thereby proving its feasibility on current embedded hardware. The three-pronged method of development of windows, deployment on Pi 4 and accessing the system to a secure web interface makes sure that the system is not only technically sound but accessible to all users, secure and practical.
dc.description.courseMechatronical Engineeringen
dc.description.degreeBSc/BA
dc.format.extent64
dc.identifier.urihttps://hdl.handle.net/2437/400913
dc.language.isoen
dc.rights.infoHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectsmart lab
dc.subjectImprovement of University Laboratory
dc.subjectSmart University Laboratory
dc.subjectinventory system for university
dc.subject.dspaceEngineering Sciences
dc.titleSmart University Laboratory
Fájlok
Eredeti köteg (ORIGINAL bundle)
Megjelenítve 1 - 1 (Összesen 1)
Nincs kép
Név:
Smart University Laboratory.pdf
Méret:
1.08 MB
Formátum:
Adobe Portable Document Format
Leírás:
Megjelenítés
Engedélyek köteg
Megjelenítve 1 - 1 (Összesen 1)
Nincs kép
Név:
license.txt
Méret:
1.69 KB
Formátum:
Item-specific license agreed upon to submission
Leírás:
Letöltés
Gyűjtemények
Theses (Department of Electrical Engineering and Mechatronics)