10.03.2026

How to Collect Mobility Data: From Paper Surveys to Smartphone Apps

Every trip carries a decision — a mode, a route, a reason. Capturing those decisions at scale is the foundation of transport planning. Without this data, it is impossible to design effective public transport, set realistic emission targets, or evaluate the impact of new mobility services. But collecting it has traditionally been costly, slow, and methodologically limited.

The Traditional Approach: Household Travel Surveys

For decades, the gold standard for mobility data collection was the household travel survey (HTS). Families would be recruited and asked to record every trip they made in a paper diary over one or two days — where they went, how long it took, which mode they used.

The results were rich in detail but came with significant problems:

• High cost — recruiting, printing, distributing, and processing paper diaries is labour-intensive
• Respondent burden — participants frequently underreport short trips and walking stages
• Short capture window — single-day diaries miss weekly travel patterns (e.g. different commute days, leisure trips on weekends)
• Long lead times — from survey design to usable datasets typically takes 12–18 months

The GPS Revolution

The arrival of GPS-enabled devices changed what was possible. Passive GPS logging eliminated the need for respondents to manually record trips — instead, movement was captured automatically and processed afterward to infer transport modes and activity stops.

Early GPS-based surveys used dedicated logger devices given to participants. While more accurate than paper diaries, they were still expensive to operate at scale, required device retrieval and charging, and were limited to short deployments.

Smartphone-Based Travel Survey Platforms

Smartphone apps represent the current frontier. Nearly everyone already carries a GPS-enabled device, eliminating the need for dedicated hardware. A well-designed travel survey app can:

• Passively collect GPS, accelerometer, Wi-Fi, and cell signal data in the background
• Use machine learning algorithms to automatically detect trips, classify transport modes, and identify activity stops
• Capture multiple weeks of data per participant, revealing weekly and seasonal travel patterns
• Deliver prompted recall surveys at the right moment — after a trip or at end of day
• Keep respondents engaged through personalised statistics (CO₂ footprint, distance per mode, progress toward survey goals)

This is exactly the approach behind MobyApp, MobyX's smartphone-based travel survey platform. The platform uses GPS, GSM, Wi-Fi, and accelerometer data, processed through ML algorithms, to automatically generate activity and travel diaries — significantly reducing respondent burden while improving data quality.

What MobyApp Has Been Deployed For

MobyApp has been used in surveys across Europe by public authorities and research organisations:

• Municipality of Turin, Italy — multi-day travel data collection for urban planning
• Oxfordshire County Council, UK — travel behaviour monitoring and SUMP support
• Bologna, Italy — citizen engagement and travel diary collection under the SPINE EU project

The platform is built following privacy-by-design principles and produces GDPR-compliant datasets ready for transport modelling and SUMP development.

Integrating Questionnaire Surveys with Passive Tracking

Passive GPS tracking tells you what people did — but not always why. MobyApp addresses this by integrating with LimeSurvey™ to allow survey managers to deliver custom questionnaires to participants at any point in the data collection process: before the survey begins (for demographics), after individual trips (for trip purpose), or at survey end (for attitudes and stated preferences).

This combination of passive objective data and active subjective data produces richer, more usable datasets for transport modelling.

Choosing the Right Approach

The best data collection method depends on your goals:

• For population-level SUMP data: smartphone-based passive collection with multi-day diaries gives the richest longitudinal picture
• For citizen engagement and feedback: a white-label citizen app (like CitizenApp) allows municipalities to brand their own data collection tools and engage residents directly
• For research and academic studies: the MobyApp Trial tier allows smaller-scale studies and proof-of-concept deployments

Want to explore which approach fits your project? Contact the MobyX team — we work with city authorities, transport consultancies, and research institutions across Europe.