SSRS - Ship Safety And Routeing System

Ship Routing Algorithm to Minimize Fuel consumption and CO2 emission

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Architecture   ·   Features   ·   Local Setup

Table Of Contents

• About the Project
• Architecture
• Impacts and Benefits
• Demonstration
• Technologies Used
• Contributing
• Authors

About The Project

Development of a versatile algorithm for optimal ship routing in the Indian Ocean, optimizing for fuel consumption, voyage time, safety, and other parameters, using real-time weather data and ship characteristics, with potential to expand optimization features

- Optimizing a ship's route and speed can reduce CO2 emissions by up to 48–60% and can save billions of dollars.
- Our algorithm utilizes the CMEMS(ocean dataset) for getting precise marine information and ocean conditions along with the accurate International Ports data after consulting with experienced marine officers.
- The application allows ship captains to adjust routes based on cost or fuel optimization for a customized path.
- Our solution's algorithm self-improves using past ship incidents, becoming smarter in suggesting the most efficient routes.

Architecture

Impacts and Benefits

Potential Impact on the Stakeholders:

1. Shipping Companies: Significant cost savings through optimized fuel-efficient routes and real-time data to avoid delays, improving overall efficiency and safety.

2. Ship Crew: Immediate assistance can be received from nearby ships through a radar system, improving emergency safety.

3. Logistics Companies: Supply chain optimization with real-time updates, ensuring better reliability in delivery schedules and reducing disruptions.

4. Port Authorities: Improved traffic management by providing visibility of incoming ships and reducing port congestion through efficient scheduling.

5. Maritime Insurers: Enhanced risk assessment using real-time and historical data, reducing incidents with SOS features and live ship tracking.

Benefits of the Solution:

1. Environmental: The solution promotes lower carbon emissions by steering ships through more fuel-efficient routes and avoiding ecologically sensitive areas, contributing to sustainable maritime operations.

2. Resource Management: Nearby port visibility allows efficient refueling and docking, minimizing unnecessary stops and optimizing operational time.

3. Safety and Risk Mitigation: Live SOS alerts and weather data enhance crew safety, helping ships avoid dangerous conditions and receive quick assistance.

4. Operational Efficiency: Real-time ocean data ensures optimal routing and minimizes delays, while customizable routes improve flexibility for different vessel types.

Explaination

demonstration.1.1.mp4

Demonstration

Live Map Page

Show Route Page

Maritime News Page

Ship Details Page

Past History Page

Commands Page

Technologies Used

• Frontend
  • React
  • CSS
• Backend
  • Flask
• Algorithm
  • Combination of dijkstra and cost matrix

Contributing

Local Setup || Project Structure

NOTE: Individual instructions can be found in respective directories.

• The project contains 4 broad directories.

*
├───client
├───data
├───processing
└───server

• client: The frontend for the application.
• data: The dataset for the applications.
• processing: Processing on the dataset
• server: The backend for the application.

Client

For local setup of frontend:

• cd client
• npm i
• npm run dev

Structure

src
├───assets
├───components
├───Pages
├───App.jsx
└───main.jsx

Individual Component & Pages Structure

component
├───component.jsx
└───component.css

pages
├───page.jsx
└───page.css

Download the data

Copernicus Marine Service

• Physical dataset

  • download

• Waves dataset

  • download

data
├───GLOBAL_ANALYSISFORECAST_PHY_001_024/(Physical dataset files)
└───GLOBAL_ANALYSISFORECAST_WAV_001_027/(Waves dataset files)

For ex,

├───GLOBAL_ANALYSISFORECAST_PHY_001_024/
    ├───glo12_rg_1d-m_20230620-20230620_3D-uovo_hcst_R20230628.nc
    ├───glo12_rg_1d-m_20230621-20230621_3D-uovo_hcst_R20230705.nc
    ├───glo12_rg_1d-m_20230622-20230622_3D-uovo_hcst_R20230705.nc
└───GLOBAL_ANALYSISFORECAST_WAV_001_027/
    ├───mfwamglocep_2023062000_R20230621_12H.nc
    ├───mfwamglocep_2023062012_R20230621_12H.nc
    ├───mfwamglocep_2023062100_R20230622_12H.nc

Server

For local setup of backend:

• cd server
• python app.py

server
└───app.py

Authors

• Hamza Sayyed
  • LinkedIn
• Om Shete
  • LinkedIn
• Mohib Abbas Sayed
• Parth Puranik
• Vedant Borkar
• Nikshita Karkera

License 📜

GNU License