A Visual Aquaculture System Using a Cloud-Based Autonomous Drones

This paper presents a low-cost and cloud-based autonomous drone system to survey and monitor aquaculture sites. We incorporated artificial intelligence (AI) services using computer vision and combined various deep learning recognition models to achieve scalability and added functionality, in order t...

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Bibliographic Details
Published in:Drones (Basel) 2021-12, Vol.5 (4), p.109
Main Authors: Ubina, Naomi A., Cheng, Shyi-Chyi, Chen, Hung-Yuan, Chang, Chin-Chun, Lan, Hsun-Yu
Format: Article
Language:English
Subjects:
Aquaculture
Artificial intelligence
autonomous drone
Big Data
Cameras
Cloud computing
Commercial fishing
Computer vision
Decision making
Deep learning
Drones
Efficiency
Face recognition
Farmers
Farms
Feeding
Fish
Fish production
Fisheries
Fishing
Food
Machine learning
Methods
Navigation
object detection and activity recognition
Object recognition
Power
remote sensing
Sensors
Surveillance
Surveillance systems
System effectiveness
visual aquaculture surveillance
Wireless networks
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Summary:This paper presents a low-cost and cloud-based autonomous drone system to survey and monitor aquaculture sites. We incorporated artificial intelligence (AI) services using computer vision and combined various deep learning recognition models to achieve scalability and added functionality, in order to perform aquaculture surveillance tasks. The recognition model is embedded in the aquaculture cloud, to analyze images and videos captured by the autonomous drone. The recognition models detect people, cages, and ship vessels at the aquaculture site. The inclusion of AI functions for face recognition, fish counting, fish length estimation and fish feeding intensity provides intelligent decision making. For the fish feeding intensity assessment, the large amount of data in the aquaculture cloud can be an input for analysis using the AI feeding system to optimize farmer production and income. The autonomous drone and aquaculture cloud services are cost-effective and an alternative to expensive surveillance systems and multiple fixed-camera installations. The aquaculture cloud enables the drone to execute its surveillance task more efficiently with an increased navigation time. The mobile drone navigation app is capable of sending surveillance alerts and reports to users. Our multifeatured surveillance system, with the integration of deep-learning models, yielded high-accuracy results.
ISSN:2504-446X
2504-446X
DOI:10.3390/drones5040109