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When it comes to deploying automatic license plate recognition (ALPR) systems, the choice between cloud, edge, on-premise, or hybrid architectures depends heavily on regional needs, regulations, and customer priorities. At a recent virtual summit, experts from Axis Communications joined FF Group to share perspectives from Europe, the Middle East, and Africa on how these approaches are shaping the future of vehicle data collection.
In the European Union, privacy regulations and strict data handling requirements are driving more analytics toward the edge. Cameras increasingly process recognition tasks locally to minimize access to video streams. As Tobias Ekberg, Chief Sales Officer at Observit explained:
“We try to put as much as possible on the edge to limit the access of video… we want to deploy the analytics on the edge.”
In the Middle East, regulatory restrictions make cloud deployments rare, with most projects remaining on-premise. Hybrid models are sometimes adopted to improve performance, but compliance remains the deciding factor. According to Chebel Bou Chebel, Technology Partner Manager at Milestone Systems:
“The most common deployment is more on-prem… the foundation is to be on-prem to ensure compliance, because due to regulation, if you don’t meet compliance, you’re out of the game.”
South Africa, meanwhile, is seeing older server-based systems phased out in favor of edge analytics, supported by hybrid setups that use the cloud for larger-scale insights. As Heino Hacke, Architectural and Engineering manager at Axis Communications noted:
“Legacy analytics servers are dying out, and it’s all becoming edge-based analytics… but the future is hybrid: edge for capture, on prem for control, and cloud for aggregated data insights.”
AI is shaping how these architectures are chosen. With advanced processing now possible on the edge, cameras can run deep learning models directly and reduce the need for expensive server infrastructure. At the same time, cloud-based AI offers broader analysis of trends, such as identifying suspicious vehicle behavior across multiple sites.
This balance explains why hybrid deployments are becoming the most practical solution: edge for speed and resilience, on-prem for control, and cloud for scalability and integration with third-party data sources.
The panel also examined how financial models influence decisions. Private sector clients often prefer operational expenditure (OPEX) models such as cloud subscriptions, while governments and larger institutions lean toward capital expenditure (CAPEX) for greater control. However, attitudes are shifting as subscription models make advanced technology more accessible.
Cybersecurity was another recurring theme. Customers increasingly demand penetration testing, code reviews, and full solution audits before adopting cloud services. Reliability of the entire chain, from cameras to infrastructure to software, is seen as critical.
Sustainability goals are also playing a growing role. Edge and hybrid systems are considered more energy efficient since they reduce the need for large GPU-powered servers and minimize cooling requirements in data centers. As Bou explained, this approach “reduces the consumption of power as well as cooling” while still supporting scalability.
While accuracy and scalability remain key metrics, the discussion also emphasized the importance of usability. Systems must be simple enough for operators in the field to trust and use effectively. As Heino Hacke observed, even the best technology fails if staff cannot interpret the data.
Ultimately, the choice between cloud, edge, and on-prem is not about replacing one with another, but about combining them to meet different needs. By aligning compliance, cost, security, and sustainability, ALPR solutions can provide not just recognition, but valuable intelligence for both policing and city management.
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