Enhancing Efficiency in Logistics: The Role of OCR and AI

According to the McKinsey report, the US economy only loses up to 95% billion US dollars a year due to delivery delays. These numbers arise from lost parcels, miscommunication, or long parcel processing.

AI technology promises to minimize losses and enhance the productivity of operations. AI solutions and OCR make logistic processes faster, more innovative, and less expensive. Optical character recognition, or OCR, is a technology that converts images into texts. This tech promises enormous benefits in many business areas, including transportation. Yet, applying OCR and AI in logistics and supply chain requires a profound understanding of the business specifics.

In this article, we shall speak about the benefits of AI in logistics, describe the successful business cases of the successful implementation of the OCR software, and check the existing limitations for OCR in logistics.

Let’s get started!

Understanding the Logistics Landscape

Despite the pandemic-related decline in the past several years, the aerial logistics landscape is recovering. According to the US Bureau of Transportation Statistics, the Freight Transportation Index in October 2023 was up 8,2% from the same month the previous year, and the long-term prognoses indicate the constant growth of the industry.

The forecast growth will require profound technological advancements to curb the needs of the industry. Therefore, 81% of freight forwarders hope technology will influence their businesses positively in the following years. Yet, despite the hopes, 80% of warehouse operations are still held manually.

The increase in delivery volume, tight delivery schedules, complex supply chains, and cargo handling operations lead to unnecessary delays and disruption that can be diminished by adopting AI and, mainly, OCR in logistics.

The Basics of OCR and AI in Logistics

OCR technology is a branch of artificial intelligence responsible for converting different data types into text, like scans, handwritten documents, and PDFs. These data are formatted as text and are faster and easier to read and process. Like many other applications of AI in logistics and supply chain, optical character recognition may help considerably.

So, how can OCR help in logistics?

Transportation is always connected with a lot of paperwork that is done manually. This process is time-consuming and prone to errors. Not to mention the periods of peak loads when all the problems get multiplied. OCR automates data extraction from invoices, lading bills, parcel labels, and handwritten notes, which is otherwise done manually. This reduces time spent on parcel processing from minutes to seconds. For example, an OCR logistic  tool, PackageX, cuts the 7 minutes of parcel processing into several seconds.

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The Synergy of OCR and AI in Logistics

The combination of OCR and AI in logistics and supply chain

Optical character recognition can recognize and process handwritten, printed, or typed text, images and symbols, bar- and QR codes, etc. When combined with other AI solutions, OCR has become a powerful tool to eliminate unnecessary manual labor in logistics.

OCR software can automatically extract and process information from receipts and checks, scan written documents into editable checks, perform quality control, and more. For example, a Singapore-based company, Speedcargo, has developed an optical character recognition tool called Cargo Eye and Assemble, which scans cargo dimensions and the number of cargos in the inventory, reads labels and images to provide an automated digital record of freight and then utilizes AI-powered analysis to create an optimal plan of building a palette, organizing storage, or transportation.

So, how does optical character recognition work?

There are different ways OCR software is used to read text. The algorithm often treats each written or typed character as an individual image. After the text is broken into images, a system uses pattern recognition to identify characters one by one. Sometimes, optical recognition software uses template matching or other machine learning techniques.

Benefits of Optical Character Recognition for Aviation Companies

The application of optical character recognition in linguistics brings about numerous benefits, which include:

  • Improved accuracy in data processing: OCR readers processing cargo labels provide a higher level of accuracy in multiple situations. One of many is damaged parcel reporting. Airports use OCR gates, which scan cargo barcodes, labels, and overall look. This way, the software detects damaged boxes and automatically reports them. This ensures an accurate picture of the cargo’s state.

  • Reduced manual errors and delays: Airport workers usually have to check kilometers of freight manually. Recently, a London-based company, Oxbotica, has launched an OCR-empowered robot truck to do the same. The robot, equipped with optical character recognition devices, operated at Heathrow Airport for three weeks and managed to scan 200km of cargo, considerably enhancing cargo handling speed and accuracy. 

  • Enhanced visibility and real-time tracking of shipments: optical character recognition scanners create digital records of physical assets at each point of delivery, which helps to update inventory levels faster and

  • Cost savings through automation and precision: An AI tool called Amplifi helps to optimize load space. It scans the freight weight and size and calculates fees and used capacity on airplanes. This maximizes the freight that can be safely loaded on a plane.

The Merge of OCR and AI in Logistics and Supply Chain: Future Trends and Possibilities

The future growth of OCR and its potential in logistics will take several directions: Deep Learning OCR – all the current optical character recognition software depends on character matching algorithms. That means the algorithms depend on historical patterns. With the development of deep learning, OCR tools will learn to understand the contexts behind the text. Deep learning OCR will enable one to read characters that are confusingly similar or will enable one to read unclear writing. Application of smarter algorithms – intelligent character recognition (ICR) and intelligent word recognition (IWR) present technologies that can read images and words better and faster. Together, they will become the next step of AI in logistics and supply chain, such as multi-lingual OCR, able to solve the existing limitations. For example, current OCR software cannot read blurry images, rare alphabets, or Arabic fonts such as Nastaliq. Instant capture OCR – we already have some optical character recognition apps that read images on the fly. Yet, the wide use of instant check OCR scanners in logistics is yet to come. OCR and augmented reality – although the merge of OCR and AR is in the phase of imagination, the potential of such technology is huge. For instance, such a device will let airport workers visually check the content of a box without unpacking it. These are just a few possible applications of optical character recognition and AI in aviation logistics and supply chains. Those who harness their benefits first will be the leaders in the air cargo business niche due to higher speeds, accuracy, and overall cost savings. If you are interested in how OCR solutions can enhance your business, contact eNest for a free consultation and advice! Our team will gladly share their expert vision of your business problem and provide a cost and timeline outline for its solution. Book a call now
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Jagdeep Chawla

MS in Data Science
NorthWestern Univeristy, Illinois

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