Navigating obstacles in maritime transport with Flo.w

Navigating obstacles in maritime transport with Flo.w

Emu Analytics was announced as one of the 28 winners of funding through the Geospatial Commission’s SBRI competition in December 2020 with the focus “to use location data to solve transport challenges”. Within the supply chains category, Emu will collaborate with the UK’s General Lighthouse Authority to analyse and visualise (& ultimately predict) shipping patterns through UK waters in order to determine how the plans for the rapid expansion in offshore wind farms will influence shipping routes.

Navigating ships and renewable energy

The UK is committed to building a green and environmentally sustainable future in which clean power generation plays a key role. Since its ambitious implementation of offshore wind farms, it comes to no surprise that this expansion has led to 2020 being the greenest year of electricity production. Despite this remarkable success, the adoption hasn’t come without its challenges. The growing spread of turbines positioned across the coastline makes it harder for ships to navigate through turbulent waters across the coast. This is why this considerable hazard to ships that could cause costs, disruptions and delays calls for an innovative solution. As part of the Department for Transport, the General Lighthouse Authority has invited applicants to present their data solutions to enhance the transport network across British waters.

Emu Analytics Solving Geospatial Challenges

Emu Analytics is a young, innovative software company that offers geospatial data analytics and visualization. The software was developed to tackle infrastructure challenges that depend on a real-time data approach having served a broad range of private and public clients, ranging from trains, planes, energy, and telecommunications to local authorities. Across multiple accelerator programs, Emu has demonstrated the transformative power for operations and supply chains through geospatial data enabling real-time and predictive insight to make operations more efficient and safe.

Data-Driven Shipping Routes & Creating A Shipping Network for the UK

The project will be a conducted as a collaboration between Emu Analytics and the General Lighthouse Authority. Emu Analytics will implement and adapt its real-time data analytics and visualisation platform Flo.w (which is already used in many aviation sector projects, analysing aircraft flight paths) to ingest, analyse and present insights on behaviours and patterns of ship movements. Flo.w’s intuitive and highly visual interface provides users with beautiful, engaging maps whilst its powerful analytics engine is able to process and analyse the vast volumes of location data being constantly generated by ships in UK waters and beyond. This will then be analysed in the context of existing and planned sea-based obstacles, namely offshore wind farms.


Image A – Temporal mapping and exploring of UK wind farms and marine infrastructure status together with historical ship movements from AIS Data

A geospatial data-driven approach will equip the maritime industry with insights and tools to enable future navigational systems to be ready for the impacts of planned wind farms. Different to car highway routes, which are literally set in stone, the nature of shipping routes is much more flexible, requiring a corresponding approach that accommodates the conditions of the British sea. Especially given the growing number of water segments along the coast host numerous wind turbines making it dangerous territory for ships to continue their established routes across these wind farms. Although the longstanding expertise of captains and mariners permits individual ships to modify their trips around these new constraints, Emu Analytics will provide a data-centered solution to develop a comprehensive national shipping network that encompasses new alterations to varying obstructions to support the UK shipping industry and transport system at large.

Using AIS data (data generated by automatic tracking systems for ships of a particular size) Emu will analyse and illustrate the range of travel routes of ships to present a large scale understanding of shipping behaviour before and after the introduction of wind farms. Drawing on machine learning techniques such as neural networks, Emu not only identifies the most common routes through patterns across the data but also explores scenarios to find what the safest, fastest and cost effective routes are. The broad adjustments and amendment of shipping navigation, Flo.w’s predictive analytics and neural networks enable to assess and locate risky areas through simulating new journey paths in order to offer new route recommendations. To prevent all these new routes from crashing the neural networks equally took this into account by coordinating and reconciling trips into a smooth, ceaseless system. In the upcoming weeks Emu seeks to advance maritime route development by exploring AIS data in regards to the implications of weather and tide conditions for ship behaviour and inform route recommendations with marine expertise.


Image B – Generating, mapping and analyzing predicted shipping route patterns using geospatial and machine learning algorithms

Working on this project grants the opportunity for Emu to prove its versatility and effectiveness in the maritime industry and to contribute to both an environmentally sustainable future and safe shipping. In the first three months Emu will gain a full picture of the challenges and possibilities in determining and incorporating the necessary data and concluding the right solutions from it. Building on this, Flo.w’s capacity will have demonstrated its value to the maritime industry in order to hopefully expand its application to further cases.

Get In Touch with Emu Analytics

If you would like to find out more about the project or how Emu’s real time data analytics software may be applied to your organisation, please contact our Business Development Executive Martine Skaret