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.
Interested to check how OCR can improve operations in your company?
ook a free consultation with our specialist and discover how you can leverage the offerings of AI-powered technology in your business!
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
Have a question?
Speak to Data Scientist
Jagdeep ChawlaMS in Data Science
NorthWestern Univeristy, Illinois
MS in Data Science
NorthWestern Univeristy, Illinois
Get Notified ⤵
More Articles
-
Speech to text solution for document handling in aviation logistics
Discover how the latest speech to text solution is revolutionizing document handling in aviation logistics. Speech to text solution for document handling in aviation logistics Su... more -
Insurance Fraud Prevention via Deep Learning
Learn how deep learning technology is revolutionizing the fight against insurance fraud. Preventing Insurance Fraud with Deep Learning Insurance fraud costs the US about $308.6 b... more -
Driving Efficiency: Computer Vision for Autonomous Vehicles
Explore the potential of computer vision in revolutionizing autonomous vehicles and driving efficiency. Driving Efficiency: Computer Vision for Autonomous Vehicles It’s not jus... more
We are ranked in Top 1%
.NET software engineer staffing
