IMPLEMENTATION OF DIGITAL LABORATORY PASSPORTS FOR EQUIPMENT AND INSTRUMENT RECORDING

This article presents the development of an information system for digital passports of laboratory equipment, intended to automate the accounting, identification and recording of the operational history of physical resources in laboratories of higher education institutions. The relevance of the study is determined by the need to move from paper-based journals and spreadsheets to more reliable digital solutions that ensure transparency, accessibility and structured storage of equipment data.

The aim of the study is to develop and test a prototype system that provides rapid identification of laboratory equipment using QR codes and access to up-to-date information through a web interface. The system was developed using the Python programming language, the Flask microframework, the embedded SQLite database and the qrcode library for QR code generation. The digital passport of equipment includes a unique identifier, name, inventory number, location, user information, as well as the date and time of the beginning and completion of equipment use.

As part of the study, a minimum viable version of the system was implemented and tested in the laboratory of the Department of Automation and Information Technologies at Shakarim University. The testing results confirmed the correct operation of the main modules, including QR code generation, registration of the beginning and completion of equipment use, saving records in the database and displaying the operational history. The proposed solution reduces the number of manual operations, lowers the risk of data loss and increases the transparency of laboratory equipment accounting.

The practical significance of the work lies in the possibility of adapting the system for other laboratories and educational organisations. The article also discusses the limitations of the current version and prospects for further development, including functionality expansion, repair accounting, report export and integration with the university’s information systems.

1. Kocharyan T.M. Osnovnye problemy, voznikayushchie pri provedenii inventarizatsii imushchestva i obyazatel'stv i ikh reshenie / T.M. Kocharyan, R.V. Morgunova // Innovatsii i investitsii. – 2020. – № 2. – S. 201-205. https://cyberleninka.ru/article/n/osnovnye-problemy-voznikayuschie-priprovedenii-inventarizatsii-imuschestva-i-obyazatelstv-i-ih-reshenie/viewer. (In Russian).

2. Implementing QR codes in academia to improve sample tracking, data accessibility, and traceability in multicampus interdisciplinary collaborations / C. Hernandez et al // PLOS ONE. – 2023. – Vol. 18, № 4. https://doi.org/10.1371/journal.pone.0282783.

3. Tobacco Leaf NIR Management and Classification Based on JSON Conversion and Constrained K-Means for SQLite Database / J. Huo et al // 2024 IEEE 15th International Conference on Software Engineering and Service Science (ICSESS). – 2024. – Р. 158-162. https://doi.org/10.1109/ICSESS62520.2024.10719383.

4. Wu Y. SQLite Embedded Database in Data Chain Devices / Y. Wu, H. Luo, Y. Liu // Proceedings of the Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023). – Shenyang, China, 2023. – Vol. 12787. – Paper 127870Y. https://doi.org/10.1117/12.3004802.

5. Wan Y. Embedded Database SQLite Application Based on ARM Platform / Y. Wan // Proceedings of the Fourth International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2024). – Yinchuan, China, 2024. – Vol. 13259. – Paper 132592U. https://doi.org/10.1117/12.3039708.

6. Realizatsiya bazy dannykh s ispol'zovaniem freimvorka Python Flask: sistema upravleniya bazoi dannykh kolledzha / N. Chauhan et al // International Journal of Engineering and Computer Science. – 2019. – T. 8. – S. 24894-24899. https://doi.org/10.18535/ijecs/v8i12.4390. (In Russian).

7. Design and Development of an Application for Database Maintenance in Inventory Management System Using Tkinter and SQLite Platform / K. Yuvaraj et al // IOP Conference Series: Materials Science and Engineering. – Vol. 995. – 012012. https://doi.org/10.1088/1757-899X/995/1/012012.

8. Implementation of Database Using Python Flask Framework: College Database Management System / N. Chauhan et al // International Journal of Engineering and Computer Science. – 2019. – Vol. 8. – Р. 24894-24899. https://doi.org/10.18535/ijecs/v8i12.4390.

9. Suraya Sholeh M. Designing and Implementing a Database for Thesis Data Management by Using the Python Flask Framework / M. Suraya Sholeh // International Journal of Engineering, Science and Information Technology. – 2021. – Vol. 2. – Р. 9-14. https://doi.org/10.52088/ijesty.v2i1.197.

10. A Comprehensive Analysis and Evaluation of SQLite Deleted Record Recovery Techniques: A Survey / S. Lee et al // Forensic Science International: Digital Investigation. – 2025. – Vol. 55. – 302031. https://doi.org/10.1016/j.fsidi.2025.302031.

11. Ramos-Miller M. Towards Inventory Control Excellence: An Innovative Approach Based on a Web-Based Platform / M. Ramos-Miller, A. Pacheco // F1000Research. – 2023. – Vol. 12. – 1471. https://doi.org/10.12688/f1000research.140745.2.

12. Tunnel-Based Intra Network Controller Using NGROK Framework for Smart Cities / P. Kumaresan et al // Proceedings of the International Conference on Electronics, Communication and Aerospace Technology (ICECA). – 2021. – Р. 39-43. https://doi.org/10.1109/ICECA52323.2021.9676036.