Building Secure and Scalable dApps: Challenges and Best Practices (Blockchain-based Apps)
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Сontinuing our exploration in the fleet industry, our next focus will be on improving document management in this field. In this blog post, we’ll review the importance of the digitizing documents to boost efficiency, and introduce our solution for the rapid digitization of one of the key documents for fleet employees – a driver’s license.
In our previous blog posts (see Fleet Management Software and AI for Fleet Management posts), we have already highlighted the importance of a properly structured document flow for fleet companies. Indeed, document digitization and automation, particularly when integrated with Fleet Management Systems (FMS), offer numerous benefits that positively impact various aspects of fleet business management.
At its core, the whole range of advantages that we can get with document workflow automation/digitization includes quick and convenient access to information presented in documents of various types, formats, and volumes.
Moreover, digitizing a document does not always mean simply obtaining a digital copy of it to store on our computer as a file. Instead, we can go further and get a smarter solution, such as the ability to automatically read data directly from a document, and then store this data in a more accessible and organized format. For these purposes, we have recently developed a parser that reads the necessary information from a photo or scan of driver’s license. See below.
In the fast-paced world of fleet management, every second counts. Keeping track of drivers’ information and ensuring regulatory compliance can be a challenging task. To assist businesses with this demands, we have taken another step forward in automating fleet management processes by developing a driver’s license parser.
A driver’s license is probably the number one document when it comes to fleet management. Its data is needed when onboarding new drivers, managing licenses and compliance, maintaining insurance records, tracking the liability, assigning vehicles, and more. That’s why we decided to start with this type of document.
We implemented an OCR (Optical Character Recognition)-based solution as a quick way to get the required data from a photo of driver’s license. This allows the data to be used for various purposes for fleet management. The process is simple: you can snap a photo of a driver’s license using a smartphone or any camera-equipped device; our app then identifies which US state the driver’s license belongs to, and retrieves all the required data for use in other apps.
Yes, the app supports the processing of driver’s licenses from different US states. This is always taken into account when recognizing information. In addition, our solution is capable of processing pictures taken at an angle, in poor quality, and under other undesirable conditions.
Each image goes through a series of enhancements before the data is read. This includes denoising, scaling, increasing contrast and etc. All this in order to ensure the text is read as accurately as possible.
🔧 The tech stack used to develop the Driver’s License Parser includes Python, OpenCV library, OCR Tesseract, JSON, matplotlib.pyplot, NumPy, RE.
Here are some of the advantages our solution offers:
And of course, with this application we can get most of the benefits from the digitization of document flow that we discussed in the first part of the blog post!
This solution offers numerous applications and scalability options: from organizing scanned data into a convenient table for its further receiving and filtering in a matter of seconds, to full integration with a fleet management system to automate various related processes. Additionally, we plan to enhance this application by incorporating recognition for other types of documents and potentially expanding into other industries.
To summarize, we can say that digitization and then automation of document management in the fleet industry are essential for boosting efficiency, reducing routine tasks for human resources, and minimizing expenses.
Also, ensuring the secure storage of digitized data is crucial for fleet-related businesses, as this information is highly sensitive. To safeguard this data, we implement robust encryption methods both at storage and in transfer, making unauthorized access is nearly impossible. Using secure cloud storage solutions that comply with industry standards, along with regular security audits, provides an extra layer of protection . These processes are essentially for compliance with widely accepted regulations such as GDPR and CCPA, which mandate strict data protection measures and grant individuals rights over their personal information. Adhering to these regulations not only helps in avoiding significant fines but also builds trust with users and stakeholders, reinforcing the company’s commitment to data security and privacy.
In this post, we have seen how many factors can be improved with the introduction of document automation technologies. The parser we developed is one of the ways to achieve significant improvements in efficiency, optimize routine tasks , and reduce expenses. Contact us if you are interested in such type of automation or want to explore more innovative business-oriented solutions. We’re here to help you transform your business operations.
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