# Harnessing AI for Sustainable Shipping and Green Ports: Challenges and Opportunities
## 1 Introduction
The main types of ballast water treatment technologies available in the market are as follows:  
* Electric pulse/pulse plasma systems;
* Filtration systems (physical);
* Chemical disinfection (oxidizing and non-oxidizing biocides), including ozone generators;
* Ultraviolet treatment;
* Deoxygenation treatment;
* Heat (thermal) treatment;
* Acoustic (cavitation) treatment;
* Magnetic field treatment [7; 29; 30]. The IMO Ballast Water Management systems must be approved by the Administration (Reg. D-3 Approval requirements for Ballast Water Management systems). Other methods of ballast water management may also be accepted as alternatives to the ballast water exchange standard and ballast water performance standard (Reg. B-3), provided that such methods confirm at least equal protection of environment, human health, property, or resources and are approved in principle by the IMO's Marine Environment Protection Committee (MEPC). Regulation D-4 is related to prototype ballast water treatment technologies. It allows ships participating in a program approved by the administration to test and evaluate emerging ballast water treatment technologies for up to five years prior to compliance [31]. * Sewage and garbage--sewage should be collected in a dedicated tank and neutralized before being disposed of in the sea. Garbage should only be disposed of when permitted by the MARPOL convention and the implemented garbage management plan (GMP). Regarding garbage disposal, there are eight special areas defined in the Convention: the Baltic Sea area, the Mediterranean Sea, the Black Sea, the Red Sea, the North Sea, the Antarctic, the Gulfs, and the Wider Caribbean. Inside a special area, a vessel must be at least 12 nautical miles from land and en route, and only food waste ground to less than 25 mm can be discharged. Outside the special areas and while en route, food waste can be disposed at greater than 12 nautical miles from the nearest land. Between a distance of 3 and 12 nautical miles, only food waste that has been ground to less than 25 mm can be discharged from a vessel. The discharge overboard of all other garbage is strictly prohibited [32; 33; 34; 35]. All described threats have a direct impact on the environment, causing greenhouse effect, ozone depletion, acid rains, and health risks for humans and animals. In recent years, there has been a growing awareness of the environmental impacts associated with maritime activities. This awareness has catalyzed a global push towards more sustainable practices within the industry. International regulatory bodies such as IMO have introduced stringent regulations aimed at reducing emissions and promoting cleaner technologies. For instance, the IMO's 2020 sulfur cap limits the sulfur content in marine fuels to 0.5%, down from the previous limit of 3.5%. Furthermore, the IMO's Initial GHG Strategy aims to reduce total annual GHG emissions from international shipping by at least 50% by 2050 compared to 2008 levels [36; 37; 38; 39]. Despite these regulatory efforts, the maritime industry faces numerous challenges in achieving sustainability. These challenges include the high costs associated with adopting new technologies, the need for significant infrastructure changes, and the complexity of coordinating international policies and regulations. Nevertheless, these challenges also present opportunities for innovation and improvement within the sector [40, 41, 42, 43]. Despite the growing recognition of AI's potential in enhancing maritime sustainability, significant gaps remain in both the scientific and practical literature. Previous studies often focus on isolated applications of AI, such as fuel optimization or autonomous navigation, without addressing the comprehensive integration of AI technologies across maritime operations. Existing research lacks a holistic approach that considers the cumulative impact of different AI applications on sustainability, and there are few longitudinal studies on the long-term benefits and drawbacks of AI adoption.