Education, Science, Technology, Innovation and Life
Open Access
Sign In
  1. Home
  2. Journals
  3. Advances in Computer, Signals and Systems
  4. Vol 10, Issue 2, 2026

Design and Research of Autonomous Cruise Fish Disease Identification System Based on UAV Platform

Download as PDF

DOI: 10.23977/acss.2026.100205 | Downloads: 0 | Views: 78

Author(s)

Bing Chen 1, Ronghui Lin 1, Shimao Dong 1, Lihua Zeng 2,3, Siyue Feng 1, Siruo Liu 1, Zichun Dai 1,3

Affiliation(s)

1 College of Urban Transportation and Logistics, Shenzhen Technology University, Shenzhen, Guangdong Province, China
2 College of Health Science and Environment Engineering, Shenzhen Technology University, Shenzhen, Guangdong Province, China
3 School of Pharmaceutical Sciences, Shenzhen University, Shenzhen, Guangdong Province, China

Corresponding Author

Zichun Dai

ABSTRACT

To address the problems of low efficiency, delayed monitoring and limited coverage of manual fish disease inspection in traditional aquaculture, and adapt to the industrial application trend of low-altitude economy in agricultural fields, this paper designs an autonomous cruise fish disease identification system based on unmanned aerial vehicle (UAV) platform. Taking the PIX quadrotor UAV as the flight carrier and Raspberry Pi 5 as the core hardware, the system integrates autonomous cruise path planning technology and deep learning fish disease recognition algorithm, and constructs a three-layer technical framework consisting of management subsystem, cruise subsystem and identification subsystem. It realizes autonomous fixed-point cruise, real-time image acquisition, intelligent disease identification and comprehensive data management in aquaculture areas. This paper comparatively analyzes the adaptability of various path planning algorithms under complex water environments in fishery, completes software and hardware collaborative integration of algorithms, flight controller and Raspberry Pi. Combined with the fish disease identification model, real-time display and data export of recognition results are realized on the visual front-end interface. Experimental results show that the autonomous cruise positioning error of the system is ≤0.5 m, and the fish disease recognition accuracy reaches 92.3%. It can effectively replace manual daily maintenance and monitoring of fishery farms, and greatly improve the efficiency of fish disease prevention and control. The system provides a feasible technical scheme for the application of low-altitude economy in intelligent aquaculture, promotes the in-depth integration of aquaculture industry and low-altitude economy, and possesses favorable practical application value and industrial promotion prospect.

KEYWORDS

Autonomous cruise; Fish disease identification; Unmanned aerial vehicle; Low-altitude economy; Path planning; Embedded deployment; Aquaculture

CITE THIS PAPER

Bing Chen, Ronghui Lin, Shimao Dong, Lihua Zeng, Siyue Feng, Siruo Liu, Zichun Dai. Design and Research of Autonomous Cruise Fish Disease Identification System Based on UAV Platform. Advances in Computer, Signals and Systems (2026). Vol. 10, No. 2, 42-48. DOI: http://dx.doi.org/10.23977/acss.2026.100205.

REFERENCES

[1] Hsain A, Zaki Y, Abaakil O, Bekkar H A, Chtouki Y. Tiny Machine Learning for Real-Time Aquaculture Monitoring: A Case Study in Morocco[C]//2024 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT). Dubai, United Arab Emirates: IEEE, 2024: 1-5.
[2] Costa C C, Belo A D A M. Ensuring Fish Safety Through Sustainable Aquaculture Practices[J]. Hygiene, 2025, 5(4): 51.
[3] Yang Y. A review of the application of unmanned aerial vehicles in air pollution monitoring[J]. Advances in Engineering Innovation, 2025, 16(7): 140-147.
[4] Jhansi G, Sujatha K. HRFSVM: identification of fish disease using hybrid Random Forest and Support Vector Machine[J]. Environmental Monitoring and Assessment, 2023, 195: 918.
[5] Gong Z Q. Research Status and Progress of Multi-platform Earth Observation Technology in Aquaculture[J]. Journal of Fisheries Research, 2025, 47(06): 722-731.
[6] Zhou J Z. Discussion on Developing Low-Altitude Economy According to Local Conditions[J]. Civil Aviation Management, 2025(04): 30-33.
[7] Chen L, Miao Z Q, Wang X K, et al. Review of Autonomous Aircraft Technology and Its Application in Low-altitude Economy[J]. Robot, 2025, 47(03): 470-496. DOI:10.13973/j.cnki.robot.250073.
[8] Luo S H, Zhao H X. Low-altitude Economy Empowers Aquaculture——Brief Analysis of Technology Integration and Industrial Upgrading Path[J]. Contemporary Fisheries, 2025, 50(08): 70-71.
[9] Wu S H, Zhou Y, Ao Q, et al. AUV and Its Control System for Fishery Breeding Monitoring[J]. Journal of Shanghai Ocean University, 2023, 32(05): 953-966.
[10] Zhang B J, Liu L P, Cao J F, et al. Research on Industrial Standard System Planning of Low-altitude Economy[J]. Information and Communication Technology and Policy, 2024, 50(11): 41-47.

Subscription
E-Mail Alert
Most popular papers
Call for Special Issue
Publication Ethics & OA Statement
Plagiarism Policy
Contact Us
Downloads: 48411
Visits: 1107024

Sponsors, Associates, and Links

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.