Autonomous Marine Robot Based on AI Recognition for Permanent Surveillance in Marine Protected Areas

Abstract

The world’s oceans are one of the most valuable sources of biodiversity and resources on the planet, although there are areas where the marine ecosystem is threatened by human activities. Marine protected areas (MPAs) are distinctive spaces protected by law due to their unique characteristics, such as being the habitat of endangered marine species. Even with this protection, there are still illegal activities such as poaching or anchoring that threaten the survival of different marine species. In this context, we propose an autonomous surface vehicle (ASV) model system for the surveillance of marine areas by detecting and recognizing vessels through artificial intelligence (AI)-based image recognition services, in search of those carrying out illegal activities. Cloud and edge AI computing technologies were used for computer vision. These technologies have proven to be accurate and reliable in detecting shapes and objects for which they have been trained. Azure edge and cloud vision services offer the best option in terms of accuracy for this task. Due to the lack of 4G and 5G coverage in offshore marine environments, it is necessary to use radio links with a coastal base station to ensure communications, which may result in a high response time due to the high latency involved. The analysis of on-board images may not be sufficiently accurate; therefore, we proposed a smart algorithm for autonomy optimization by selecting the proper AI technology according to the current scenario (SAAO) capable of selecting the best AI source for the current scenario in real time, according to the required recognition accuracy or low latency. The SAAO optimizes the execution, efficiency, risk reduction, and results of each stage of the surveillance mission, taking appropriate decisions by selecting either cloud or edge vision models without human intervention.

Building a Practical Multi-Sensor Platform for Monitoring Vessel Activity near Marine Protected Areas: Case Studies from Urban and Remote Locations

“…At the time of writing, most of these systems are best suited for use in small, targeted areas [63] and provide complementary information to more traditional monitoring techniques [64]. However, with ongoing progress in edge computing and computer vision models, these vehicles can be effective tools for collecting data on vessel activity in MPAs [65].…”

Exploring the integration of artificial intelligence (AI) and augmented reality (AR) in maritime medicine: A narrative literature review (Preprint)

“…AI can also be used for remote monitoring and surveillance in the maritime setting, allowing early detection of medical issues and prompt intervention [14]. Additionally, AI robots can be deployed in maritime environments that are hazardous to human health, reducing the risks of injury or exposure to toxic substances [15]. The use of AI can lower costs, improve healthcare outcomes, and increase efficiency.…”

“…The integration of AI into maritime medicine requires careful consideration, appropriate regulations, and ethical considerations. The potential impact and benefits of AI technology in maritime medicine are relevant, with promising prospects for enhancing health services and safety in the marine environment [9], [13], [15]. With the use of AI innovations, maritime medicine can improve the safety, healthcare outcomes, and well-being of seafarers.…”

Coastal radar as a tool for continuous and fine-scale monitoring of vessel activities of interest in the vicinity of marine protected areas

“…Satellite-based solutions, including synthetic aperture radar (SAR), radio frequency (RF) detection, and optical imagery, used by Global Fishing Watch, HawkEye360, and others [37,38], offer non-participatory methods but can be limited by temporal resolution, data processing requirements, and difficulty in detecting small vessels amongst waves and coastline features [39]. For small-scale activity in coastal areas, autonomous marine vehicles and drones have been used to monitor areas of interest [40,41]. The need for technologies that can enhance management of smallscale fisheries worldwide is addressed by numerous international goals [42].…”