Maritimedata.ai is a digital broker that provides data and analytics solutions for the maritime ecosystem. We work as an intermediary between clients in the maritime industry and solution providers to help them find the best data-driven solutions to their business challenges.

The objective of the newsletter is to provide you with up-to-date information on the most recent advancements in space and provide you with market insights derived from data driven analysis.

TL;DR

📣 What’s new!? 🚀

• BlackSky Introduces AI-Powered Maritime Custody Service for Real-Time Vessel Tracking and Surveillance 🛰️

• Marine Benchmark launches Benchmark Carbon for accurately monitoring Carbon Intensity Indicator (CII) and Attained Emission Rating (AER) for all vessels in the world fleet 🌱🚢

💡 Insight 📊

• Harnessing Historical AIS data for Machine Learning 🚢 🤖📖

• What the new EU sanctions package means for maritime compliance 🇪🇺

BlackSky Introduces AI-Powered Maritime Custody Service for Real-Time Vessel Tracking and Surveillance 

Abstract: BlackSky, a leading provider of real-time geospatial intelligence, has developed the Maritime Custody Service (MCS) to address the crucial need for advanced vessel tracking and surveillance in maritime domains. The MCS utilizes a multi-source system, combining commercial radio frequency (RF) data, electro-optical (EO) imagery, and synthetic aperture radar (SAR) imagery to monitor vessel movements in real-time. By leveraging data streams from the BlackSky Global satellite constellation and Spire Global Inc.'s satellite constellation, along with the Spectra AI platform, the MCS enables users to identify vessels of interest, monitor their positions, and observe their activities using commercial, unclassified sources. This article provides an overview of the MCS's design, algorithms, early prototype results, and expected improvements. 

Introduction: With the increase in maritime traffic and the associated risks of geopolitical conflicts and criminal activities at sea, there is a growing demand for real-time maritime surveillance systems. These systems play a critical role in identifying and responding to illegal activities such as smuggling, sanctions evasion, illegal fishing, marine terrorism, and disaster-related incidents. However, existing surveillance solutions have limitations in terms of capabilities, flexibility, and accuracy, hindering their ability to provide real-time intelligence for various applications. To overcome these challenges, BlackSky has developed the Maritime Custody Service (MCS), a cutting-edge AI-powered system for on-demand monitoring of vessels in the world's oceans and waterways. 

Maritime Custody Service (MCS) Overview: The MCS combines high-frequency satellite imaging, including electro-optical (EO) and synthetic aperture radar (SAR) sensors, with accurate target acquisition, vessel trajectory prediction, and vessel identification and classification. The system utilizes data from BlackSky's satellite constellation, Spire's satellite and terrestrial receivers for RF emissions, and the Spectra AI platform for image processing and analysis. By integrating these diverse data sources, the MCS can monitor vessels in real-time as they navigate open oceans, rivers, canals, and while docked at ports. It has the capability to detect vessels of interest, track their positions, and classify them by type. 

Concept of Operations: The MCS operates in a continuous cycle to maintain custody of monitored vessels. It begins with RF-based vessel tracking and trajectory prediction using emissions data collected by Spire's Lemur satellites and terrestrial AIS sensor network. The system then identifies imaging opportunities by intersecting the probabilistic vessel trajectory forecast with the ground tracks of BlackSky's satellites. Once the imaging opportunities are determined, BlackSky's satellite constellation captures images of the targeted vessels. The collected images are processed using the Spectra AI platform, which detects and classifies vessels. If a vessel is identified in the images, its position and trajectory are updated, ensuring accurate vessel tracking. 

1. Target Geolocation via RF: Using RF emissions collected by Spire’s Lemur satellites and terrestrial AIS sensor network, the MCS identifies a vessel’s current position, speed, and direction of travel, otherwise referred to as a vessel’s heading. 

2. Predict Vessel Trajectory: The MCS then predicts the vessel’s future trajectory by analyzing position and velocity information derived from the captured RF emissions. 

   Currently, the MCS uses a simple dead-reckoning approach, in which vessel trajectories are computed assuming constant vessel speed and direction. Accordingly, the vessel trajectories consist of a simple series of straight lines. However, BlackSky has developed more advanced heteroscedastic regression models in order to anticipate the future position of ships. See the Results & Expected Improvements section for additional detail. 

3. Identify Imaging Opportunities: BlackSky identifies imaging opportunities by intersecting the probabilistic vessel trajectory forecast with the upcoming ground tracks of BlackSky’s satellites. Opportunities with the highest probability of interception are then integrated into a mission plan and uploaded to the satellites for execution. 

4. Collect Images: The BlackSky satellite constellation then collects imagery at the coordinates with the highest probability of interception. To maximize the probability of a successful capture, BlackSky can collect multiple images along the vessel’s forecasted trajectory (to compensate for variations in the vessel’s speed) or across the vessel’s forecasted trajectory (to compensate for changes in the vessel’s heading). 

    

5. Detect Vessels: Once images are collected and downlinked, BlackSky’s Spectra AI platform analyzes the collected images. BlackSky’s proprietary vessel detection model is then run to locate and classify the different types of vessels present in the images. 

The vessel detections are then cross-referenced against any available AIS information describing the target vessel to determine whether it was successfully captured in the image. 

6. Update Target Geolocation: If the target vessel is identified in the collected images, Spectra AI can then update the vessel’s position and direction of travel and refresh its MCS trajectory forecast based on this new information. This helps ensure that an accurate starting location is used when vessel trajectory forecasts are initialized.

Once all six steps above have been executed, the cycle is repeated.  

By executing this loop during a vessel’s entire journey, the MCS can be used to maintain custody of a vessel as it travels nearly anywhere on Earth. Furthermore, if a vessel’s AIS report purports to be at a particular pair of coordinates, but the vessel is not present in the collected image, it is more likely the vessel is spoofing its AIS transmission.  

Results & Expected Improvements:

The MCS prototype has shown promising results, capturing targeted vessels both while docked at ports and while deployed at sea. The initial prototype achieved a vessel capture rate of approximately 25% of the collected images. However, there is room for improvement by refining the system's algorithms. Three key improvements are highlighted: transitioning from dead reckoning to probabilistic route prediction models for better vessel position forecasting, reducing image collection latency to ensure timely capture of vessels, and implementing multi-frame, larger area image collections to increase the probability of capturing vessels within the collected scenes. 

Conclusion: BlackSky's Maritime Custody Service (MCS) represents a significant advancement in real-time vessel tracking and surveillance capabilities. By leveraging AI and multi-source data integration, the MCS provides users with a powerful tool for monitoring maritime activities and detecting illicit behavior. With ongoing algorithm improvements, including enhanced vessel position forecasting and reduced image collection latency, the MCS is expected to become an even more effective solution for commercial, military, economic, and environmental applications, contributing to the security and safety of maritime domains worldwide. 

🔎 Who do we think should be interested in MCS?

Trade Finance 🛢️

• Compliance, Sanctions and AML officers: Help ensure compliance with regulations like AML and sanctions screening.

  MCS helps monitor vessel movements and detect suspicious activities beyond the means of vessel tracking data such as AIS.

• Trade Finance Operations Manager: Oversees trade finance activities and utilizes MCS for monitoring vessel movements and verifying trade documents.

Marine Insurers 🚢

• Hull Underwriters: MCS supports underwriters to understand the activity of vessels/owners in the event there are gaps in their AIS coverage to support thorough risk assessments and policy issuance.

• Claims Managers Investigates insurance claims using enhanced vessel tracking and historical data provided by MCS.

Commodity Traders 🌾 🛢️ 🪨

• Risk Managers: Manages trading risks by monitoring shipments, identifying potential delays, and proactively mitigating risks using enhanced data from MCS.

• Compliance Officers: Ensures trade compliance by monitoring vessel movements, identifying potential violations, and enforcing compliance measures with the support of MCS.

✉️ We're inviting readers of our newsletter to participate in our beta user access program for testing the Maritime Custody Service (MCS).

Sign up through the form below: Limited spots available. Join us today and contribute to the advancement of real-time vessel tracking and surveillance and help combat illicit shipping and sanctions evasion practices.

🗓️ Deadline for submissions: July 15th 2023

Introducing Benchmark Carbon: Join the Beta Access Test for Advanced Maritime Carbon monitoring

A new product offering from www.marinebenchmark.com

Introduction: Marine Benchmark combines first-class shipping data, cutting-edge technology and a lifetime of experience in shipping to create innovative, user-friendly analysis tools for the marine industry.

The Marine Benchmark fuel calculation model has been a reliable model and under development over more than 20 years. Marine Benchmark and its founders have been very early movers in calculating fuel and environmental KPIs.

The original version was developed as early as year 2000 in a European Union project, “Airborne emissions from shipping in EU waters”. The project was subsequently, over a number of years, responsible for calculating the EU related shipping emissions and reported to the EU commission.

Benchmark Carbon offers a comprehensive solution for accurately monitoring Carbon Intensity Indicator (CII) and Attained Emission Rating (AER) for all vessels in the world fleet. It provides historical data, current year-to-date information, and a 10-year future prognosis for CII. Here's how Benchmark Carbon solves the mentioned problems and user cases:

1. Monitoring CII and AER Rating: Benchmark Carbon monitors and calculates accurate historic and current attained CII and CCI ratings for all vessels in the world fleet. This allows users to assess the carbon efficiency of individual ships or entire fleets.

2. Current Year CII and Year-to-Date Trend: Users can access the current year's CII for any ship, providing real-time information on carbon emissions. Additionally, Benchmark Carbon offers a year-to-date trend analysis, enabling users to track the carbon performance of a vessel over time.

3. UN Register Access and Fleet Comparison: The platform provides full access to the UN register (S&P IHS), allowing users to filter and compare different parts of the world fleet. This feature helps ship owners, shippers, and operators analyze fleets and make informed decisions based on carbon efficiency.

4. CII Future Prognosis and Filtering: Benchmark Carbon offers a future prognosis feature that predicts the CII of vessels up to 2035. Users can filter vessels based on any specific year to identify ships that meet their carbon emission requirements.

5. Comprehensive CII Reports: The platform allows users to generate comprehensive CII reports for any ship in the world fleet. These reports provide detailed information on carbon intensity, emissions ratings, and other relevant data, assisting customers in making informed decisions.

6. Customer Base: Benchmark Carbon caters to various stakeholders in the maritime industry, including shippers, cargo owners, operators, banks, ship owners, equipment/service suppliers, yards, and insurance companies. Each customer group benefits from the platform's unique features based on their specific needs and objectives.

7. Sensor Data Integration: Benchmark Carbon provides the option to connect sensor data, enabling users to compare their emissions data with competitors or any other defined group within the world fleet. This feature allows for benchmarking and performance analysis, aiding in identifying areas for improvement.

Overall, Benchmark Carbon offers a comprehensive solution for monitoring and analyzing carbon emissions in the maritime industry. It helps stakeholders make informed decisions, assess asset quality, compare fleets, identify business opportunities, and offer appropriate solutions based on carbon efficiency.

🔎 Who do we think should be interested in Benchmark Carbon?

Financial institutions 🏦

Ship Finance Managers: Evaluate the carbon efficiency of vessels seeking financing.

Risk Analysts: Assess environmental risk and make informed lending decisions.

Sustainability Officers: Ensure ship finance aligns with sustainability commitments.

Relationship Managers: Provide insights to clients and foster sustainable partnerships.

Compliance Officers: Ensure compliance with environmental regulations and standards.

Marine Insurers 🚢

Hull Underwriters: Assess environmental risk and determine insurance coverage and terms.

Risk Analysts: Evaluate vessel carbon footprint and calculate potential liabilities.

Chief Data Officers: Monitor environmental impact of insured fleet and align with sustainability goals.

Claims Managers: Evaluate carbon performance during incidents or damages.

Product Development Managers: Develop innovative insurance products addressing environmental risks.

🌍 Join the Future of Maritime Carbon Monitoring! 🚢🌱

Be among the first to experience the power of Benchmark Carbon, a brand new solution for monitoring carbon emissions in the maritime industry. Sign up now for our beta user access test and unlock the following exclusive benefits:

🔍 Monitor accurate historic and current CII for all vessels in the world fleet.
📈 Track the year-to-date trend and future prognosis of carbon intensity.
🌐 Access the UN register and compare fleets and individual ships.
📊 Generate comprehensive CII reports tailored to your needs.
💡 Connect your sensor data to gain deeper insights and benchmark against competitors.

🗓️ Deadline for submissions: July 6th 2023

Ready to make a significant impact on carbon emissions in the maritime industry? Sign up for our beta access test and take action with Benchmark Carbon today! 🌍🌱🚢

Harnessing Historical AIS data for Machine Learning 🚢 🤖📖

In this recent webinar by Spire.com the audience is taken on a deep dive into the world of machine learning and its applications in the maritime industry. The presenters explore machine learning as a branch of artificial intelligence that utilizes data sets and algorithms to continually improve accuracy over time. The typical components of a machine learning model, including the decision process, error function, and method optimization process, are examined to demonstrate how they work together to analyze data sets and identify patterns.

Highlights:

• Machine learning as a branch of AI for improving accuracy over time

• Components of a machine learning model: decision process, error function, and method optimization process

• Importance of historical data, focusing on AIS (automatic identification system) data in the maritime industry

• Use cases of machine learning with AIS data: predictive maintenance, route planning optimization, emissions tracking, commodity trading analysis, identifying inefficiencies in supply chains, risk assessment, fraud detection, and risk mitigation in marine insurance

• Requirements for effective use of AIS data in machine learning models

• Freightflows showcases practical utilization of AIS data for building geospatial data sets and tracking commercial activities

The webinar emphasizes the importance of historical data for training machine learning models, particularly focusing on the utilization of AIS data. AIS, known as automatic identification system, enables ships to transmit their position and other relevant information to other vessels. Spire Maritime, a prominent player in the field, collects AIS data from its own satellite constellation and third-party providers to ensure comprehensive coverage. The various use cases for machine learning with AIS data are explored, such as predictive maintenance of vessels, route planning optimization, emissions tracking, predictive analysis for commodity trading, identification of bottlenecks and inefficiencies in supply chains, as well as risk assessment, fraud detection, and risk mitigation in the marine insurance industry.

The webinar also delves into the requirements for AIS data to be effectively used in machine learning models and highlights the role of Spire in this process. Spire boasts over 10 years of historical AIS data and continuous improvement in coverage. They offer the data in different formats, including raw NMEA format, decoded format, and combined post-processed format. Additionally, Spire provides flexible data delivery options and dedicated support teams to assist customers with their specific needs.

To provide a practical demonstration of AIS data utilization, Freightflows, a predictive analytics company specializing in global trade, shares insights. They explain how they leverage AIS data to build a comprehensive geospatial data set and create dynamic polygons representing port and berth areas. By analyzing ship movements and clustering the data, Freightflows accurately tracks commercial activities and provides valuable insights to its customers.

Overall, the webinar replay offers a comprehensive and informative exploration of machine learning, AIS data, and their applications in the maritime industry. It caters to a wide range of interests, including predictive maintenance, route optimization, emissions tracking, commodity trading, supply chain optimization, and marine insurance. Attendees have the opportunity to gain valuable insights and stay ahead in the rapidly evolving world of maritime technology.

What does the new EU sanctions package means for maritime compliance 🇪🇺

In a recent post by Ami Daniel, Ceo of Windward.ai, he explained why he thought the proposed 11th package of EU sanctions was a game changer for maritime compliance, and we agree.

This follows the 20+ year trend of the United States increasing their use of sanctions as a foreign policy tool and/or military responses.

The number of US government sanction designations grew from 912 to 9,421, skyrocketing by 933%, in the two decades from 2000 to 2021, according to economist Timothy Taylor’s review of OFAC data.

🔎 ⚠️ So how might this effect Maritime Compliance teams?

Increased complexity 😓🔍: The proposed sanctions package will introduce additional measures related to ship-to-ship transfers and vessels going dark. Maritime compliance teams will face the challenge of detecting and preventing illicit activities without sophisticated technology to automatically identify such behavior in real-time.

Compliance technology demand 🚢💻: The need for advanced compliance technology will surge as maritime organizations strive to meet the requirements of the sanctions package. Compliance teams will require robust systems capable of detecting dark activity and complex GNSS manipulations, minimizing false positives, and ensuring adherence to sanctions.

Criminalization of sanctions ⚖️🚢: As sanctions in Europe become increasingly criminalized, maritime compliance teams may face the responsibility of monitoring and enforcing sanctions alongside law enforcement and customs agencies. They will continue to need to identify violations and prevent designations, balancing the need for robust enforcement with the avoidance of significant economic disruptions.

Enhanced tracking and understanding 📈🌍: The sanctions package will expand the list of prohibited items for export to Russia, necessitating improved vessel tracking and a deeper understanding of transshipments.

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Thank you for your time.

Best regards,

Rory Proud

Co-Founder

[email protected]