SmartMove Analytics: AI-Driven Urban Mobility Data Platform for Pedestrian and Cyclist Modal Split

SmartMove Analytics is an advanced AI and edge computing-based platform designed for real-time monitoring and analysis of pedestrian and cyclist flows in urban environments.

Through a network of IoT sensors, smart cameras, and integration with municipal infrastructure data, the solution delivers predictive analytics and interactive visualizations to support decision-making in urban planning, safety, sustainability, and public health.

The system is scalable, secure, and participatory, enabling authorities, technicians, and citizens to co-create more efficient and livable cities.

- Urban Planning: Data-driven design of safer and more efficient pedestrian and cycling infrastructure.

- Safety: Proactive identification of risk areas and hazardous behaviors, enabling preventive measures.

- Sustainability: Promotion of active transport and reduction of emissions aligned with climate and health goals.

- Public Health: Encouragement of healthy habits and measurement of active mobility program impacts.

- Economic Development: Identification of areas with potential for commercial and tourism revitalization.

- Transparency and Participation: Building trust and shared responsibility through open data and participatory processes.

- Scalability and Efficiency: Ready-to-scale architecture reducing marginal costs as coverage expands.

LIS Data Solutions is a leading company in advanced analytics, artificial intelligence, and smart city solutions with extensive experience in European innovation projects. LIS has developed flagship solutions such as REPOSAT (AI and data science for environmental and agricultural management, EU-supported), DIGITbrain (digital twins and industrial process optimization, Horizon 2020), PRECEDENT (industrial data spaces and sustainability, NextGenerationEU), and was a finalist in the European Data Incubator (EDI) with an AI-based predictive maintenance solution. The multidisciplinary team combines engineers, mathematicians, and citizen engagement experts, ensuring robust, secure solutions aligned with European interoperability and sustainability standards.

References:
- REPOSAT: AI and data science for environmental and agricultural management (EU, FEDER)

- DIGITbrain: Digital twins and industrial optimization (Horizon 2020)

- PRECEDENT: Industrial data spaces and sustainability (NextGenerationEU)

- European Data Incubator (EDI): Big Data and AI for industry and mobility (Horizon 2020)

- Phase 1: Stakeholder Co-Design & Pilot Area Mapping
Participatory workshops and needs definition, following REPOSAT methodologies.
Estimated duration: 1 month
Estimated cost: €15,000

- Phase 2: Sensor Network Deployment & Edge Integration
Installation of IoT sensors, AI cameras, and infrastructure setup, leveraging DIGITbrain and PRECEDENT experience.
Estimated duration: 2 months
Estimated cost: €28,000

- Phase 3: AI Model Training & Dashboard Customization
Development and training of predictive models, dashboard personalization as demonstrated in DIGITbrain and EDI.
Estimated duration: 2 months
Estimated cost: €22,000

- Phase 4: Public Dashboard Launch & Community Engagement
Implementation of open dashboards and citizen participation tools, based on PRECEDENT best practices.
Estimated duration: 1 month
Estimated cost: €12,000

- Phase 5: Scaling to Additional Zones & Open Data Publication
Modular expansion to new urban areas and release of aggregated datasets for policymaking, focusing on cost-efficiency and scalability.
Ongoing deployment
Estimated cost: €10,000 per additional zone

- Total estimated cost for initial deployment (pilot area): €87,000
- Cost per additional zone: €10,000 (with progressive cost reductions as platform scales)

This proposal integrates LIS Data Solutions’ real EU project experience, delivering a robust, scalable solution aligned with the highest standards of sustainability, participation, and urban digitalization.