ALPR gets a boost with Edge computing
Edge computing brings real-time accuracy to automated license plate recognition
Governments worldwide are adopting AI and Edge AI to streamline their urban management systems.
AI technology plays a crucial role in vehicle management, particularly with the development of Automated License Plate Recognition (ALPR).
ALPR systems use image processing and machine learning techniques to identify and recognize license plates, making it easier to manage traffic flow.
However, traditional ALPR that relies on network connection servers or cloud infrastructure has limitations such as image transmission delays, high bandwidth occupancy, and reduced capability in terms of frames per second.
Not to mention that traditional ALPR systems also face challenges such as variations in license plate styles, weather, and changing scenery, making it difficult to achieve accurate recognition.
Enter Edge computing (which involves installing embedded systems directly at the network’s edge to process and analyze data locally, in real-time).
By keeping data local, ALPR systems can save bandwidth and reduce image transmission delays.
In addition to its impact on traffic management, Edge-based ALPR technology significantly impacts store pick-ups or click-and-collect services, where customers can order products online from stores like Home Depot or Bunnings and pick them up at a physical store.
With the integration of Edge AI in ALPR, recognition can be performed in real-time, allowing retailers to quickly identify customers' vehicles and streamline the pick-up process.
This improves the customer experience, helps manage traffic flow, and optimizes operations.
Together, Edge solutions and ALPR are poised to play a key role in improving traffic management and streamlining pick-up processes.
By processing data locally, Edge-based ALPR offers significant benefits over traditional, centralized AI systems, making it a valuable tool for businesses and governments alike.
Check out the sources below to learn more about ALPR at the Edge.
Solving license plate recognition conundrums
When a global provider of automated car alignment solutions faced a challenge with its license plate recognition system, Sighthound found the solution.
The issue was that changes in license plate designs and formats were causing a significant drop in accuracy.
With Sighthound's privacy-focused approach and cutting-edge Deep Neural Network technology, the company was soon able to accurately identify vehicles with more than 90% accuracy without relying on its legacy recognition system.
Vehicle Identification Accuracy With Sighthound ALPR+ Means Bigger Profits
Effortless vehicle identification with ALPR and Edge AI
ALPR systems are popular video analytics applications for smart cities.
These systems can be used for various purposes, such as fast vehicle identification, congestion control, vehicle counting, law enforcement, automatic fare collection, and more!
The article below explores how Hailo’s ALPR system can be deployed on Edge devices using powerful Edge AI processors.
This results in improved accuracy, fast detection, a lower total cost of ownership, and increased data protection (by eliminating the need to send raw video to the cloud).
Automatic License Plate Recognition with Hailo-8
Edge-AI-powered ALPR system achieves incredible accuracy
The following article suggests an innovative way to improve the accuracy of ALPR systems.
This proposed Edge-AI-based solution provides real-time ALPR with high recognition rates at low computational costs, making it a valuable contribution to the development of intelligent transport systems.
Edge-AI-Based Real-Time Automated License Plate Recognition System
Some extra resources
Microsoft Edge gets smarter with AI technology
Microsoft has released a new version of its Edge web browser that includes exciting AI capabilities.
The browser allows users to summarize search results, converse with AI chatbots, and run comparisons (among a variety of other tasks).
The release of the updated Edge browser coincides with Microsoft's investment in OpenAI's GPT-4 model for its Bing search engine.
Microsoft’s Edge web browser gets ChatGPT-like features
Edge AI soars: Global market to reach $8 billion by 2027
According to a new report from Astute Analytica, the global Edge AI Software market will reach $8,050 million in 2027.
The report provides insights into the competitive market conditions to help firms make decisions for growth and profitability.
Edge Computing drives digital transformation
Edge computing is a method of distributing data storage and processing to bring compute and storage capabilities to devices, applications, and users.
This reduces latency and bandwidth costs and adheres to data privacy and governance policies by avoiding data transfer to central cloud servers.
As such, it’s crucial for enterprises to understand Edge computing and create a future-proof Edge strategy.
The Role of the Database in Edge Computing
Xailient’s newest article
Edge computing provides an efficient solution to the challenges posed by the IoT's growth and accompanying data increase.
But, like all technologies, Edge computing has difficulties. The good news is they can all be resolved with Xailient’s AI management platform, Orchestrait.
For more info, see our blog, The Rise of Edge Computing: Understanding Its Benefits and Drawbacks
Thanks for reading,
See you next week!