Description

The application of indoor crowd sensing to monitor and encourage physical separation between individuals — primarily for infectious-disease control. Social distancing compliance overlaps with contact-tracing (which records who got close to whom) but emphasizes real-time density and pairwise-distance estimation, often coupled with feedback signage or app notifications. This is the application context in which BLE proximity estimation and crowd-density-estimation gained their broadest attention during 2020–2022.

Why it's hard

  • BLE pairwise-distance estimation is noisy at the relevant 1–2 m thresholds.
  • Aggregate density bounds compliance only weakly — two people at 1.5 m in a low-density room is non-compliant.
  • The framing is politically and behaviorally contested; consent and adoption are non-technical bottlenecks.
  • Cross-modal fusion with crowd-monitoring systems is needed but rarely deployed cleanly.

Common approaches

  • BLE-based pairwise proximity flagging.
  • Camera + computer-vision pose-distance estimation as a high-accuracy baseline.
  • Aggregate density thresholds with zone-level alerting.
  • Mobile-app feedback consuming venue-deployed sensing.

Source Papers

  • darsena2023_50b7 — sensing technologies for crowd management in public transport.
  • agnelli2023_ea3a — spatial kinetic crowd-evacuation with infectious-disease contagion.

1 vault paper address this problem

Titles and DOIs only — no abstracts, no analyses.

  • Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review 2023 DOI ↗