ShopSafe is a concept mobile system for crowd management in shopping malls during COVID-19, designed during the Adobe Creative Jam at Capgemini. The brief: translate ambiguous government regulations into a clear, scalable experience for visitors, store staff, and mall administrators.
When shopping malls reopened during the pandemic, visitors faced fragmented information, unclear safety protocols, and significant anxiety. Mall operators needed a way to enforce occupancy regulations from the Maharashtra government without creating confusion at every touchpoint.
High stakes.
Low information.
No system of trust.
A connected mobile system that gives every stakeholder real-time visibility, turning compliance into clarity.
Given the short timeline and pandemic constraints, research was conducted through secondary sources: academic papers on crowd dynamics, government advisories, and behavioural research on public anxiety. The objective was to identify trust signals and information patterns that consistently reduced stress in high-risk environments.
"In high-anxiety environments, visibility is the design intervention. Users don't need more information. They need the right information at the right moment."
Research synthesis · ShopSafe project
ShopSafe was designed as a three-sided system. Each user type (visitor, store staff, mall admin) got a tailored interface, but all operated on a shared real-time data layer. The information that lowered visitor anxiety was the same data that helped staff manage queues and admins enforce occupancy.
Real-time crowd density per zone. Pre-visit slot booking aligned to government caps. In-mall navigation that routes around congested areas. Live alerts on store availability and safety protocols.
Per-store occupancy tracking. Inbound visitor previews from connected mall data. Queue management tools and direct staff-to-visitor communication for entry, wait times, and store-level guidance.
Live occupancy dashboards by zone and floor. Compliance reporting against government caps. Centralised communication to all stores and visitors. Operational analytics for peak-period planning.
The team agreed on four principles upfront. Every interface decision was tested against them, particularly when balancing compliance requirements against user experience.
The concept explored how emerging technologies (AI for crowd prediction, IoT sensors for occupancy detection, and AR for in-space navigation) could be applied pragmatically to a real operational problem rather than as standalone features.
Mobile-first visual design across the three user interfaces. The visual system prioritised glanceable data, clear status indicators, and accessible colour usage, critical in a context where users were anxious and decision-making had to be fast.
Designing visitor, staff, and admin interfaces as views into a single source of truth (rather than three disconnected apps) kept the system coherent and the design work tractable within the 4-month timeline.
Government occupancy caps and pandemic protocols were the strongest design inputs we had. Treating them as scaffolding rather than restrictions led to a tighter, more defensible solution than starting from an open canvas.
Pandemic restrictions and timeline pressure ruled out interviews and contextual inquiry. Secondary research and behavioural literature carried the validation load. Without primary signals, some assumptions about visitor decision-making remained untested.
The system relied on technologies (IoT sensors, AI density prediction, AR navigation) that would require significant operational investment to deploy at scale. The concept demonstrated direction; productisation would have surfaced sharper tradeoffs.
ShopSafe couldn't be designed as a mobile app alone: every screen depended on operational workflows happening offline, between stores, between teams, and across regulatory layers. The most valuable design work happened in mapping the system, not styling the interface.
The three-sided system framing. The discipline of designing every interface from a shared data model. The decision to treat regulatory constraints as a design input rather than a problem to work around.
Primary research: even brief structured interviews would have validated key visitor assumptions. A clearer feasibility framework for the technology stack, distinguishing concept-stage vision from MVP-stage scope. Service-design artefacts (journey maps, blueprint diagrams) as core deliverables, not supporting documentation.