# Toward Understanding Crowd Mobility in Smart Cities through the Internet of Things

arXiv: https://arxiv.org/abs/1909.08522 · HTML: https://mlsanity.com/paper/1909.08522/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Sep 2019.

## Built on by (most cited first, 4 of 4)

- [Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities](https://mlsanity.com/paper/2307.06687/) (2023)
- [IMAP: Individual huMAn mobility Patterns visualizing platform](https://mlsanity.com/paper/2209.03615/) (2022)
- [CrowdWeb: A Visualization Tool for Mobility Patterns in Smart Cities](https://mlsanity.com/paper/2305.12935/) (2023)
- [Real-time Object and Event Detection Service through Computer Vision and Edge Computing](https://mlsanity.com/paper/2504.11662/) (2025)

## Abstract (arXiv)

Understanding crowd mobility behaviors would be a key enabler for crowd management in smart cities, benefiting various sectors such as public safety, tourism and transportation. This article discusses the existing challenges and the recent advances to overcome them and allow sharing information across stakeholders of crowd management through Internet of Things (IoT) technologies. The article proposes the usage of the new federated interoperable semantic IoT platform (FIESTA-IoT), which is considered as "a system of systems". The platform can support various IoT applications for crowd management in smart cities. In particular, the article discusses two integrated IoT systems for crowd mobility: 1) Crowd Mobility Analytics System, 2) Crowd Counting and Location System (from the SmartSantander testbed). Pilot studies are conducted in Gold Coast, Australia and Santander, Spain to fulfill various requirements such as providing online and offline crowd mobility analyses with various sensors in different regions. The analyses provided by these systems are shared across applications in order to provide insights and support crowd management in smart city environments.