Artificial intelligence to the rescue: Assisting the shipping container crisis
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Artificial intelligence to the rescue: Assisting the shipping container crisis

By Frankie Youd 18 Nov 2021

The shipping industry is continuing to struggle with the ongoing shipping container shortage with many companies trying to adjust and adapt to the issue. However, could artificial intelligence guide shipping back to smooth sailing?

Artificial intelligence to the rescue: Assisting the shipping container crisis
The shipping industry is continuing to struggle with the ongoing shipping container shortage with many companies trying to adjust and adapt to the issue. Credit: AurelioaPhoto.

With Christmas right around the corner media outlets from across the globe have been highlighting the ongoing shipping container crisis which has shown little, if any, signs of stabilising. With millions of people around the world concerned for the festive season when it comes to gifts and certain food items, the industry has been working hard to adjust shipping methods and get products shipped where possible.

Alongside methods the industry has been taking such as repurposing containers, re-using older models and more, maritime navigation company ORCA AI believe that the implementation of artificial intelligence is the right way forward to tackle the crisis.

We speak to Dor Raviv, co-founder & CTO, Orca AI, to find out more about the artificial intelligence  solutions which can assist the container crisis as well as the key benefits that this technology brings.

Credit: Orca AI.

 

Frankie Youd (FY): When looking at the ongoing shipping container crisis do you think that AI is a solution to this problem?

Dor Raviv (DR): The container crisis has been caused by a combination of lack of staff and lack of equipment – AI can help support both of these areas.

Part of the importance of introducing technology throughout the industry is to increase automation – not only on ships for improved visuals and traffic updates, but also for port operators to increase efficiency. Automating part of the logistics chain reduces reliance on people where there are shortages, making the entire process more efficient through processing multiple data points at any given time, empowering the chain with new, unique insights.

It also significantly opens up communication between fleets and ports, with sensors and real time data being fed into a central point that is accessible to those on land and on sea, ensuring no ship is isolated. While it’s not an overnight solution, it will help lessen the strain on what is being labelled ‘Containergedon’ and can be the catalyst for driving forward future innovation throughout the shipping world.

 

How would you suggest that AI is implemented into the industry to assist with the issue?

First, the industry needs to become familiar with the concept of data and its importance for decision making. Then, sensors and cameras installed on board a vessel can generate data for the individual responsible on the ship, creating visibility on decision making, presenting, and prioritizing information.

These sensors can be used to provide live updates to the ports, allowing them to advise ships to slow their approach and delay their arrival, which will help reduce idling ships waiting to get into port. Over time, this data can also be analysed to predict future incidents and provide the essential insight to prevent them.

Trials are already underway for automated cranes and vessels. The pilot of the automated driverless container trucks by Cosco Shipping Ports Limited can massively help reduce the time spent unloading ships, which can also be applied to cranes.

 

At Orca AI, we are working closely with shipping companies and oil majors to create a new safety system for autonomous cargo ships. This will create a new lookout support system for vessels by providing improved visibility in difficult conditions, prevent human error, and enable crews to make truly informed decisions. In the future, as more stakeholders adopt these data driven solutions, a data ecosystem will enable informed decisions throughout the entire supply chain.

 

Why do you think that maybe AI has not been included sooner to help with this issue?

Shipping is a very traditional industry, lagging behind the likes of the automotive and aviation industries when it comes to technological innovation. The recent pandemic has helped accelerate the maritime industry’s acceptance of technology, such as AI, but we are still years behind other industries looking to achieve the same thing, with the technology still seen as a mystery to many.

“Shipping is a very traditional industry, lagging behind the likes of the automotive and aviation industries when it comes to technological innovation.”

However, the potential is vast and exciting. There are dozens of proofs of concepts being trialled across the globe that, in time, will bring us up the standard of planes where nearly all commercial airlines now have a partially automated cockpit, where in-between take-off and landing, the pilots are not actively having to fly the plane.

At Orca AI, we are working towards projects that are able to achieve feats for the shipping industry, such as NYK and providing new data for the maritime insurers, and are excited at the future given the impact we’ve had in a relatively short time period.

 

What are the main benefits of using AI to help with this issue?

Captains, co-Captains and navigational officers on board have extremely difficult and complex jobs. To avoid dangerous objects and collisions while sailing, navigators currently use binoculars and multiple sensors such as radar, to visually recognise and prioritise dangerous objects. This job is made even harder with inexperienced crew members. Looking at the statistics – nearly 4,000 maritime accidents occur annually, and the majority are caused by human error.

With AI, this process for identifying obstructions and prioritising risks is made far easier under most conditions. The more traffic and complex the scenario, the more the AI excels as opposed to humans, mainly due to the fact it can process multiple data points at blinding speeds.

Thermal imaging cameras and AI-enabled visual support systems provide instant feedback, helping them analyse situations and provide them with all the data they need to give them a full understanding of what they need to do at any given moment in time.

 

Could you explain how the company is currently alleviating some issues through JIT?

In order to provide the whole suite of safety solutions, our technology uses AI both for the vessel, and also to process multiple data points on the fleet level. For example, AI can generate actionable insights due to its ability to identify trends, anomalies and benchmarks between vessels and fleets. It automatically clusters dangerous areas, pointing to distances, speeds, locations, and weather in order to create a comprehensive representation of the risk level.

Credit: Orca AI.

 

This information can then be relayed to the rest of a fleet or even to ports, creating a more streamlined form of communication. Live updates and timings from the port to the ships will help reduce the backlog at entry as vessels will be able to reduce their speed to delay arrival, subsequently reducing their carbon footprint and fuel costs, while also relieving pressures on berth capacity.

Additionally, the data gained can be used by insurance providers to create a more accurate pricing structure that accurately reflects the ship’s risk rates.

 

What do you think the future will hold for this shipping container crisis?

The pandemic has unfortunately put our industry under undue pressure, with the rising demand for products and shortage of skilled crew, and this problem is not going to go away overnight.

“The pandemic has unfortunately put our industry under undue pressure, with the rising demand for products and shortage of skilled crew, and this problem is not going to go away overnight.”

There are certainly a number of short-term solutions out there, such as opening 24/7 ports and adjusting delivery schedules so that empty containers are removed before new ones are brought in, but ultimately the solution can only come with further investment into new technologies, especially data driven solutions.