Author(s)

YuHan Chen¹, XinYuan Gao², BoYu Shan¹, XianXing Luo³, ShangXuan Li⁴, Yi Zhang^1*

Affiliation(s)

¹College of Electrical Engineering, North China University of Science and Technology, Tangshan 063210, Hebei, China.

²College of Materials Engineering, North China University of Science and Technology, Tangshan 063210, Hebei, China.

³College of Artificial Intelligence, North China University of Science and Technology, Tangshan 063210, Hebei, China.

⁴College of Traditional Chinese Medicine, North China University of Science and Technology, Tangshan 063210, Hebei, China.

Corresponding Author

Yi Zhang

ABSTRACT

To address the pain points of traditional medical waste transportation, such as high reliance on manual labor, irrational routes, prominent dumping risks, and difficulties in traceability, this paper designs an intelligent transportation system integrating multiple technologies. The core innovation lies in constructing an integrated intelligent architecture of "perception-localization-scheduling-traceability-risk prevention." This system breaks the traditional human-dominated model of medical waste transportation and achieves intelligent control of the entire transportation process through deep integration of software and hardware. The system primarily uses ESP32C3 as the main controller, innovatively integrating UWB high-precision positioning, K230 visual recognition, and anti-dumping mechanical structures to form a triple innovation system: First, the linkage between UWB and K230 visual recognition enables precise positioning and classification identification of waste bins; Second, the integration of improved genetic algorithms with A* algorithms achieves dynamic route scheduling and obstacle avoidance; Third, a cloud-based traceability system is constructed based on the MQTT protocol, complemented by anti-dumping structures to mitigate risks. After debugging, the system's positioning accuracy reaches the centimeter level. The classification recognition accuracy of the medical waste trash bins is relatively high. The single transportation efficiency has been improved, and the transportation process can be traced, meeting the digital supervision requirements of the "Medical Waste Management Regulations". This provides a reliable solution for the intelligent upgrade of medical waste transportation.

KEYWORDS

Medical waste transportation; UWB positioning; Cloud-based collaboration; Path planning; End-to-end traceability

CITE THIS PAPER

YuHan Chen, ShangXuan Li, BoYu Shan, XianXing Luo, XinYuan Gao, Yi Zhang. Intelligent transportation system of medical waste based on UWB positioning and cloud collaboration. Journal of Computer Science and Electrical Engineering. 2026, 8(1): 57-63. DOI: https://doi.org/10.61784/jcsee3118.

REFERENCES

[1] Azzouz A, Bouhmidi R, Munir E M, et al. Dual-band terahertz MIMO antenna using DGS for UWB applications. Results in Optics, 2026, 23: 100968.

[2] Zeng Yang, Yin Gang, Zhang Yong, et al. Attention-Based TCN for LOS/NLOS Identification Using UWB Ranging and Angle Data. Electronics, 2026, 15(2): 448.

[3] M S G E, M A A K, Mohammed A, et al. Intelligent transportation system using wireless optical communication: a comparative study. Optical and Quantum Electronics, 2023, 56(2).

[4] Fares A, Reem A, Mohammed Z, et al. YOLO and Blockchain Technology Applied to Intelligent Transportation License Plate Character Recognition for Security. Computers, Materials & Continua, 2023, 77(3): 3697-3722.

[5] Yong Jie, Ziyi Ke, Ziqiang Chen, et al. Rapid density estimation of tiny pests from sticky traps using Qpest RCNN in conjunction with UWB-UAV-based IoT framework. Neural Computing and Applications, 2023, 36(17): 9779-9803.

[6] Tighilt Y, Bensid C, Sayad D, et al. Low-Profile UWB-MIMO Antenna System with Enhanced Isolation Using Parasitic Elements and Metamaterial Integration. Electronics, 2023, 12(23): 4852.

[7] Kim K, Lee S, Yoo T, et al. Vehicular Localization Framework with UWB and DAG-Based Distributed Ledger for Ensuring Positioning Accuracy and Security. Electronics, 2023, 12(23): 4756.

[8] Caner P, Mehmet T, Hassan K, et al. The Use of Virtual Reality Technology in Intelligent Transportation Systems Education. Sustainability, 2022, 15(1): 300.

[9] Vivekananda N G, Jarwar A M, Jaber M M, et al. Effective two-tier tokenization for intelligent transportation supply chain systems using hybrid optimized query expansion. Multimedia Tools and Applications, 2022, 84(29): 1-29.

[10] Liu Xin, Zhang Yang, Ruan Zhi, et al. Intelligent Vehicle-road Integrated Traffic Safety System Based on Beidou. The Educational Review, USA, 2022, 6(11).