Abstract In Transport Mode Detection, a great diversity of methodologies exist according to
the choice made on sensors, preprocessing, model used, etc. In this domain, the …

Transport mode detection is a classification problem aiming to design an algorithm that can
infer the transport mode of a user given multimodal signals (GPS and/or inertial sensors). It …

Ubiquitous and diverse sensors have enriched the transportation field with a multitude of
data types and substantial semantic knowledge, significantly advancing the development of …

Transportation mode detection with personal devices has been investigated for over ten
years due to its importance in monitoring ones' activities, understanding human mobility, and …

Activity recognition and transportation mode detection are the key research areas for context-
aware systems. In smart environments such as cities, buildings, transportation systems etc …

Transportation is a significant component of human lives and understanding how individuals
travel is an essential task in many fields. Understanding the modes of transport individuals …

Transport mode identification (TMI), which infers the travel modes of user trajectories, is
essential to facilitate an understanding of urban mobility patterns and passengers' choice …

In recent years, with the diversification of people's modes of transportation, a large amount of
traffic data is generated when people travel every day, and this data can help transportation …

Transport Mode Detection (TMD) is a crucial component in the field of Intelligent
Transportation Systems (ITS), taking advantage of current advancements in Artificial …

Transportation mode detection from smartphone data is investigated as a relevant problem
in the multi-modal transportation systems context. Neural networks are chosen as a timely …