Wi-Fi Pocket Sensor Mobility Analysis System

📐 Methodology

🔗 Website

Photo credit: https://www.jriss.jp/
đŸ–„ïž Systems
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Jriss

JRISS (Japan Research Institute for Social Systems) focuses on methodologies and research for risk assessment and resilience of infrastructures and urban systems. The organization develops analytical frameworks and modeling tools to support evidence-based decision-making for resilient cities and critical infrastructure.

Context and problem statement

Cities need accurate and up-to-date information on how people and vehicles move within urban environments. However, traditional traffic surveys and manual observation methods are often costly, limited in scope, and unable to provide continuous monitoring.

Urban planners and public authorities increasingly require data-driven insights into pedestrian and vehicle flows in order to support mobility planning, tourism management, and infrastructure optimisation.

JRISS developed sensor-based mobility monitoring solutions to address these challenges and provide cities with more precise information about urban movement patterns.

Solution overview

The JRISS Wi-Fi Packet Sensor system captures signals emitted by Wi-Fi-enabled devices such as smartphones and other connected devices to analyse patterns of presence, movement, and dwell time in specific areas.

By analysing these signals, the system can estimate:

  • pedestrian flows
  • movement between locations
  • duration of visits in specific areas

The collected data is processed in a way that does not include personal information or communication content, ensuring privacy protection.

This type of analysis enables cities and organisations to better understand urban dynamics and make more informed decisions regarding infrastructure planning, public transport operations, and event management.

Functional Scope and Features

  • Sensor-based mobility detection: Wi-Fi sensors detect devices with active wireless connectivity and measure the number of devices within a given area, allowing estimation of pedestrian density and movement patterns.
  • Movement and flow analysis: By analysing device signals across multiple sensors, the system can identify movement between locations, travel paths, and patterns of urban mobility.
  • Dwell time analysis: The solution can estimate how long visitors remain within specific locations, providing insights into the attractiveness or usage of urban spaces.
  • Privacy-preserving data processing: To ensure privacy protection, device identifiers are anonymised using hashing methods before analysis, preventing identification of individual users.

 

 

Use Cases and Deployments

JRISS mobility monitoring solutions have been deployed in multiple urban and transport contexts.

  • Urban mobility analysis: The system has been used to analyse traffic flows around railway stations and busy urban areas to support city planning initiatives.
  • Tourism and visitor flow monitoring: Cities and tourism organisations use the data to understand how visitors move through urban districts and public spaces.
  • Transport infrastructure planning: Transport operators can analyse mobility data to optimise services and improve passenger information systems.
  • Large-scale events: Mobility data platforms developed by JRISS have also been used for analysing visitor flows during large events such as the Osaka–Kansai Expo 2025, where mobility and crowd patterns are visualised through dedicated dashboards.

Related Challenges

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Related Pilots

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