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Beyond Footfall: How AI Video Analytics Is Unlocking Millions in Value at Paddington Square

Dec 31, 2025

Beyond Footfall: How AI Video Analytics Is Unlocking Millions in Value at Paddington Square

Paddington Square is one of London’s most ambitious new destinations - a place where transport, retail, and public space converge. We’re proud to share how PercepVision AI, in partnership with CIS Security, has transformed this landmark development into a data‑driven, intelligently managed environment.

This project demonstrates a simple truth: modern commercial properties no longer need more cameras - they need smarter ones. With PercepVision AI, every video stream becomes a strategic asset, delivering insights that drive operational efficiency, commercial performance, and public safety.

A Dual‑Purpose Destination With Dual Challenges

Our October 2025 case study revealed the unique rhythm of Paddington Square:

  • Weekday Commuter Power: Around 15,000 escalator journeys driven by office and rail traffic.

  • Weekend Leisure Shift: Approximately 13,000 escalator journeys, dominated by retail and leisure visitors.

This clarity enables:

  • Security and Facility Management (FM) teams to staff precisely for peak periods.

  • Leasing teams to justify rental values with transparent, evidence‑based footfall patterns.

Paddington Square isn’t just busy - it’s predictably busy, and that predictability is commercially powerful.

From Data to Revenue: Turning Insights Into Strategy

The real commercial uplift comes from PercepVision’s granular Occupancy Insights, which reveal how people actually use the space.

Key Findings & Strategic Opportunities

Zone

Finding

Strategic Opportunity

B1 Ticket Hall

Highest occupancy; the primary interchange between rail and retail.

A high‑performance zone ideal for premium tenants, targeted activations, and high‑value promotions.

Concourse (Escalator 4)

Least utilised; lower relevance in main circulation routes.

A growth zone perfect for experiential retail, events, and interventions designed to unlock untapped value.

These insights are already helping the estate team:

  • Validate the worth of high‑traffic areas

  • Identify underperforming spaces

  • Convert low‑engagement zones into new revenue opportunities

This is commercial strategy powered by real‑world behaviour, not assumptions.

Raising the Bar: From Reactive to Proactive Security

For CIS, our security and FM partner, PercepVision has become a cornerstone of their operational model.

“The advanced analytics are fundamental to our security protocols. Intrusion Detection, Loitering Detection, and Unattended Object Detection provide crucial proactive monitoring capabilities, instantly alerting our teams before activity can escalate… The platform has elevated our operational planning, asset value, and public safety standards.” Kuldeep Kainth, Director at CIS and Paddington Square Security Management

Key Safety Features in Action

  • Real‑Time Over‑Occupancy Monitoring
    Ensures safe crowd levels and enables proactive intervention.



  • Unattended Bag

    Prevent security incidents by alerting teams to suspicious packages, abandoned items, or potential threats that require immediate investigation and response.

  • Schedule‑Based Intrusion Detection
    Reduces false alarms while maintaining robust after‑hours protection.


  • Attribute Search
    Accelerates investigations by allowing teams to search historical footage using descriptors such as clothing colour.

These capabilities shift security from responding to incidents to preventing them.

Conclusion: A Blueprint for the Future of Smart Facilities

The Paddington Square project demonstrates what’s possible when AI video analytics is embedded into the fabric of a modern estate. By combining deep commercial insights with world‑class safety analytics, PercepVision is helping clients operate more efficiently, enhance asset value, and deliver exceptional visitor experiences.

This is the future of facility management - intelligent, proactive, and powered by real‑time data.