# Transportation Mode Classification from Smartphone Sensors via a Long-Short-Term-Memory Network

arXiv: https://arxiv.org/abs/1910.04739 · HTML: https://mlsanity.com/paper/1910.04739/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Oct 2019.

## Built on by (most cited first, 1 of 1)

- [Estimator: An Effective and Scalable Framework for Transportation Mode Classification over Trajectories](https://mlsanity.com/paper/2212.05502/) (2022)

## Abstract (arXiv)

This article introduces the architecture of a Long-Short-Term Memory network for classifying transportation-modes via Smartphone data and evaluates its accuracy. By using a Long-Short-Term-Memory Network with common preprocessing steps such as normalisation for classification tasks a F1-Score accuracy of 63.68% was achieved with an internal test dataset. We participated as Team 'GanbareAM' in the 'SHL recognition challenge'.