Challenges

Tsukuba faces increasing disparities between its central urban areas and surrounding suburban zones, leading to unequal access to services, infrastructure, and economic opportunities. The city seeks integrated solutions to improve connectivity, accessibility, and balanced territorial development.

In major hubs like Istanbul and Helsinki, intersections are critical bottlenecks causing severe congestion and safety risks. Currently, monitoring is largely manual and fragmented, leading to slow response times. The AI4LIFE challenge implements an AI-based management system that integrates IoT infrastructure with real-time analytics. By automating the detection of abnormal traffic situations and consolidating multiple tools into a single hypervisor, the solution reduces response times, lowers emissions from idling, and enhances road safety for millions of commuters.

Urban Heat Islands have become a growing challenge for cities across Europe and globally, driven by climate change, increasing urban density, and the prevalence of highly mineralised urban environments. Recent European studies indicate that around 7% of heat-related mortality in cities can be attributed to the Urban Heat Island effect, highlighting urban heat as a significant public health risk, particularly during extreme heat events.

Fujisawa City faced a surge in maintenance reports for its public parks, but fragmented data made it difficult to prioritize interventions. This challenge introduced a mobile reporting system for staff and citizens, integrated into a smart city hypervisor. By centralizing GPS-tagged incident reports and applying AI-driven analytics, the city transitioned from reactive repairs to proactive, data-driven management. This optimizes municipal resources while ensuring higher safety and quality of life in urban green spaces.

Managing urban freight in dense areas like the Metropolitan Area of Barcelona (AMB) is complex due to fragmented data and a lack of unified monitoring tools. The EyeDecide challenge addresses this by transforming raw data from the SPRO logistics app into actionable insights via an integrated AI platform. It enables the AMB to monitor freight activities, detect illegal parking, and forecast parking availability across nine municipalities. This data-driven approach optimizes logistics operations, reduces traffic congestion, and supports more sustainable urban mobility.

Urban intersections are high-risk zones where diverse users like cars, pedestrians, cyclists, and micro-mobility, interact in complex ways. This challenge seeks a low-latency, privacy-compliant solution using edge computing and AI to detect and analyze dangerous situations in real time. By processing data locally and sharing only anonymized insights, the system will improve safety, enable rapid responses, and support data-driven urban planning.