Connecting people with points of interest
Geospatial solution connecting digital and physical user data through phygital technology for unique user identification. Seeketing solves real-time optimisation, planning and traffic generation challenges in urban environments, intermodal transportation and gamification.
Seeketing technology
Based on patented radiofrequency fingerprinting, Seeketing generates anonymous pseudo-identifiers of smartphones to understand origin-destination journeys of citizens, visitors, travellers, commuters and tourism flows. It is positioned as a unique phygital solution for counting, origin-destination, intermodal data and interaction.
Performance comparison against existing technologies
The deck contrasts Seeketing with app-based solutions, cameras, telco data and Wi-Fi tracking. The core message is that existing alternatives cannot provide massive behavioural data, univocal digital user detection and good geospatial granularity at the same time.
- App-based solutions usually have less than 1% active-user penetration.
- Cameras count the same person several times and face GDPR limits in public areas.
- Telco data has low quality for local journeys and only partial market-share samples.
- Wi-Fi tracking does not work because of MAC randomization.
Case 1. Collecting quality people behaviour data
City mobility planners face recurring inefficiencies due to the disconnect between digital technology use and physical-world behaviour. Seeketing addresses origin-destination, intermodal transportation, on-demand services, geoposition-based assistance and traffic generation to destination points.
Pedestrian areas
Traffic flow measurements between urban points using fingerprinting mobile detection.
Train stations
Accurate area data inside hubs and differentiated traveller behaviour.
Bus / tram lines
Origin-destination and speed measured anonymously.
Car parking
Integration with local flows, park and ride and traffic generation.
Motor vehicles
Traffic data on points of origin and destination.
Bike parking
Multi-mode transport network visibility and active mobility support.
Features for mobility
Seeketing nodes generate comprehensive anonymous spatial datasets covering pedestrians vs travellers, car counting, origin-destination by transport type, mobility user profiles and trip-based multipoint datasets along transport routes.
Pedestrians vs travellers
Separate flows for cars, bicycles, buses and other traveller types.
Car counting data
Vehicle volumes and related traffic signals.
Origin-destination by mode
Bus, car, bicycle, train and metro chains.
Behavioural profiles
Transport patterns linked with digital behaviour in web and app.
Traveller capacity
Analysis of line success and contribution to network performance.
Supply planning
Auto-generated recommendations aligned with predicted demand.
Case 2. Transport systems and network planning
The deck focuses on transport-system optimisation, traveller capacity analytics, station behaviour, retail corner optimisation and traveller satisfaction through phygital data and proximity information.
- Measure which lines contribute most to network success.
- Plan transport supply and optimise capacity utilisation.
- Improve store mix, signage and screens in stations.
- Direct traffic to retail areas using phygital identifiers integrated with apps and websites.
- Send wait time, taxi and alternative route information.
Atocha Train & Metro Hub, Madrid, Spain
Atocha needed better passenger-behaviour knowledge to optimise operations. Camera data lacked sufficient granularity for origin-destination, waiting times and access behaviour. Nodes were placed across three station floors and monitored retail, taxi, public transport and parking access.
Challenge
Insufficient granularity and reliability from camera-based analytics.
Solution
Monitoring entrances, platforms, retail areas, taxi zones, public transport and parking flows.
Result
Confirmation of Seeketing's value as an operations-optimisation tool for large transport hubs.
Granularity
Street access to platforms and differentiated flow paths by floor.
Case 3. Traffic and mobility analytics
This section covers CO2 reduction, traffic-signal optimisation, dangerous pedestrian behaviour during major events, low emission zones and speed analysis in difficult highway conditions.
Reducing CO2
Real-time traffic around roundabouts during large city events helps smart street systems reduce congestion and emissions.
Protecting life
Pedestrians near dangerous traffic areas during football matches or concerts can be identified and targeted with safety campaigns or signage.
Low Emission Zones
Analyse whether fewer cars mean modal shift success or reduced city business and visitor dissatisfaction.
Speed analysis
Highway lighting can be adapted to real-time average speed under bad weather and poor visibility.
Habits and routes
Behavioural change can be measured after changes to streets, timetables, parking or event areas.
Phygital results
Combine physical behaviour and digital behaviour for a richer interpretation of mobility outcomes.
Case 4. Security and mobility analytics, crowd areas
Seeketing supports emergency situations, crowd monitoring, pedestrian-capacity control and incident-oriented analytics. The Ramblas attack, El Rocio and the identification of profiles involved in thefts or incidents are part of the examples shown.
- Know the exact number of people in endangered areas in real time.
- Send adequate emergency personnel to at-risk zones.
- Apply real-time capacity control to indoor and outdoor monitored areas.
- Display capacity info on screens and tablets to reassure the public.
- Provide origin-destination and multimodal matrices of travellers.
Case 5. Gamification and interaction with visitors
The deck frames many city issues as the result of human habits. Seeketing proposes changing those habits by sending relevant messages to the right people at the right place, without requiring users to install an app.
Residents, tourists, commuters and regular visitors are profiled based on patterns and recurrent flows.
Generate databases of visitors and use age, gender and online/offline behaviour for communication.
Use proximity messages to steer mobility, routes and choices toward better city outcomes.
Results and global challenge
Massive behavioural data is highly valuable for optimising municipal and commercial events, adapting campaigns to seasonality and improving impact. It also frames a global challenge of reducing CO2 footprint by 30% using phygital technology.
Company profile
Seeketing is certified in R&D by the Spanish Ministry of Industry, the Centre for Technological and Industrial Development and the Ministry of Economy and Innovation. The company delivers geospatial mobility and phygital communication solutions based on proprietary technology for detecting consumer mobile phones.
- Only truly phygital technology currently available worldwide.
- Proprietary AI technology overcoming Bluetooth, ibeacon and Wi-Fi tracking limitations.
- Experience in smart cities, municipalities, airports, railway stations and venues.
- Growing client base including leading companies in 14 countries.
Frequently asked questions
What makes Seeketing phygital?
It links individual digital behaviour and real-world movement through unique anonymous identifiers.
Which scenarios does it support?
Urban planning, transport networks, crowd safety, capacity control, active mobility and city-habit modification.
Why is it stronger than cameras?
It offers better origin-destination granularity, fewer legal constraints, lower deployment friction and interaction capabilities.
Semantic summary
Phygital City is Seeketing's English-language geospatial solution page for mobility analytics, transport-system planning, crowd safety, capacity monitoring, habit modification and CO2 reduction using phygital identifiers and radiofrequency fingerprinting.
Key entities include Seeketing, smart cities, mobility analytics, transport networks, crowd monitoring, Atocha, Madrid Light Train, El Rocio, low emission zones and active mobility.