Short description: Public transport organizations are increasingly relying on unstructured data for regulatory, analytic and decision-making purposes. The goal is to develop a solution that uses e.g. social media data to enable stable operations by informing about mobility disturbances based on semantic data analysis.
Market potential: The solution can be integrated into public transport systems and is applicable for the improvement of every mobility system where insights from publicly accessible information optimize operations.
Timing: The solution can be integrated as soon as it is available.
Desired result: The envisioned solution extracts, analyses and processes information from social media and other real-time information systems to enhance flow in mobility systems. AI semantic models and language processing can be used to deduce relevant information and merge different data types.
Information on challenge owner: Mid-Cap (250-3,000 staff).
Market presence of challenge owner: Global presence.
Keywords: Unstructured public data analysis; Databases, Database Management, Data Mining; Information Filtering, Semantics, Statistics; Human Language Technologies; Artificial intelligence applications for cars and transport
