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INSIGHTS

Smart parking revolution: How video analytics is outpacing RFID

Smart parking revolution: How video analytics is outpacing RFID
Industry leaders are advocating for ANPR’s broader adoption in large-scale parking operations, citing its advantages over RFID technology in both cost and performance.
As urban centers grow increasingly congested, parking solutions are becoming more sophisticated, leveraging automation and technology to improve efficiency.
 
Among the leading innovations, video analytics-based Automatic Number Plate Recognition (ANPR) is emerging as a formidable alternative to Radio-Frequency Identification (RFID) systems, offering a more scalable, cost-effective, and flexible approach.
 
Industry leaders are advocating for ANPR’s broader adoption in large-scale parking operations, citing its advantages over RFID technology in both cost and performance.

Challenges in video analytics-based parking systems

While ANPR-based parking solutions are gaining momentum, they are not without their challenges. Variability in lighting conditions is a major issue, with factors such as glare, shadows, and low-light environments impacting accuracy.
 
Variable lighting conditions, such as glare, shadows, or low light, can affect the accuracy of ANPR systems, according to Ashish Dhakan, MD & CEO of Prama Hikvision India.
Inconsistent illumination can make it difficult for cameras to capture plate numbers clearly, requiring sophisticated image processing techniques to compensate for environmental conditions.
 
Another obstacle is the readability of vehicle plates. Plates that are partially obscured, damaged, or worn down over time can interfere with recognition accuracy.
 
“Partially occluded or damaged number plates can reduce ANPR accuracy,” Dhakan noted.
 
 Moreover, regional variations in plate designs, fonts, and colors create further complications, necessitating the development of adaptable algorithms capable of recognizing diverse formats.
 
The angle and speed at which vehicles approach a checkpoint also influence recognition performance.
 
“High-speed vehicles or those approaching at an angle can make ANPR more difficult,” Dhakan added.
 
Higher speeds and extreme angles make capturing a clear image more difficult, requiring advanced camera positioning and motion compensation techniques.
 
Beyond optical and environmental factors, operational challenges such as system calibration, data management, and integration with parking management software must also be addressed.

Regular maintenance and software updates are critical to ensure long-term reliability, while seamless integration with existing parking infrastructure is essential for streamlined operations.

Comparing video analytics with RFID technology

Both ANPR and RFID systems have been used for parking management, but they differ significantly in terms of performance, scalability, and cost-effectiveness. One key advantage of ANPR over RFID is its non-intrusiveness.
 
“RFID systems require vehicles to stop or slow down, whereas VCA-based ANPR systems are non-intrusive,” Dhakan pointed out. RFID systems often require vehicles to slow down or stop at designated points for tag scanning, whereas ANPR operates passively, allowing for a smoother flow of traffic.
 
Accuracy is another area where ANPR systems demonstrate a significant edge, particularly in high-traffic environments. Since RFID relies on physical tags attached to vehicles, missing or malfunctioning tags can cause disruptions.
 
ANPR, in contrast, eliminates this dependency by recognizing vehicles purely through optical means. “VCA-based ANPR systems can achieve higher accuracy rates than RFID systems, especially in high-traffic areas,” Dhakan said.
 
Scalability is a further consideration. ANPR can be easily integrated into existing surveillance infrastructure, making it more adaptable to large-scale operations.
 
In contrast, RFID deployment requires the installation of readers at every checkpoint, along with the distribution and maintenance of tags for every registered vehicle, making it less flexible and more expensive over time.
 
When assessing security, ANPR systems also present fewer vulnerabilities. “VCA-based ANPR systems are less vulnerable to security threats, such as RFID tag cloning or tampering,” Dhakan pointed out.
 
RFID tags can be cloned or tampered with, creating potential loopholes in security. In contrast, ANPR systems operate without direct physical components attached to vehicles, making them less susceptible to fraud.

Cost, maintenance, and long-term viability

From an investment standpoint, ANPR and RFID systems follow distinct cost trajectories. RFID typically requires a higher upfront investment due to the need for dedicated readers, infrastructure, and vehicle tags.
 
 In contrast, ANPR can often leverage existing CCTV installations, reducing the overall cost of implementation.
 
The long-term cost of ownership also favors ANPR. “ANPR systems tend to have a lower total cost of ownership, as they require less hardware and maintenance,” Dhakan explained.
 
 While software licenses for ANPR systems can be expensive, the overall maintenance burden is lower compared to RFID, which requires continual monitoring and replacement of vehicle tags.
 
RFID readers also require periodic cleaning and maintenance, while ANPR cameras mostly need occasional calibration and firmware updates.
 
System downtime is another consideration. While both technologies are susceptible to occasional failures, RFID systems can face disruptions due to tag malfunctions or reader malfunctions.
 
ANPR systems, on the other hand, are primarily affected by camera-related issues, which can often be addressed through software-driven solutions.

Scaling for large parking facilities

For large parking operations, scalability is a crucial factor, and ANPR systems offer distinct advantages in this regard. Since they rely on a network of cameras rather than physical tags and readers, expanding the system to cover additional parking zones is relatively straightforward.
 
In contrast, RFID-based systems require additional readers and infrastructure for each new parking section, driving up costs and complicating deployment.
 
ANPR also provides greater flexibility, making it applicable to a variety of use cases beyond parking management. The same technology can be adapted for access control, traffic monitoring, and security applications, increasing its overall utility.
 
In contrast, RFID is largely limited to parking-related functions and would require additional systems to perform comparable tasks.
 
Looking ahead, ANPR systems are better positioned for future technological advancements. AI-driven analytics and cloud-based data management are making these systems increasingly intelligent, enabling features such as predictive analytics and automated enforcement.
 
Upgrading an ANPR system to incorporate new capabilities is often as simple as a software update, whereas RFID systems may require substantial hardware overhauls to remain current.

Enhancing parking management efficiency

To overcome existing challenges and further enhance the effectiveness of ANPR-based parking solutions, several best practices can be implemented.
 
Deploying high-resolution cameras with a wide field of view can significantly improve recognition accuracy, ensuring that plates are captured clearly under various lighting conditions. Advanced video analytics algorithms can also be employed to optimize performance and reduce false readings.
 
Regular maintenance remains a critical factor in long-term system efficiency. Keeping cameras clean, well-calibrated, and updated with the latest software ensures optimal performance.
 
Additionally, efficient data management strategies must be in place to handle the large volumes of information generated by ANPR systems, ensuring quick retrieval and processing.
 
Seamless integration with broader parking management systems is another key factor in maximizing efficiency.
 
“Ensuring seamless integration with parking management systems can optimize parking operations,” Dhakan emphasized. When properly synchronized with entry gates, payment systems, and real-time occupancy tracking, ANPR can significantly improve the overall flow of vehicles and reduce congestion.

Conclusion

A detailed analysis of ANPR and RFID parking management solutions highlights the superior cost-effectiveness, scalability, and flexibility of video analytics-based ANPR.
 
While RFID remains a viable option for smaller parking facilities, it becomes increasingly cost-prohibitive and difficult to scale for larger operations.
 
With rapid advancements in AI-powered video analytics and cloud-based management solutions, ANPR is set to play a pivotal role in the evolution of smart parking infrastructure.
 
As cities continue to expand and traffic volumes rise, efficient and automated parking solutions will be critical in shaping the future of urban mobility.
 
 
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