A low-cost iot platform for crowd density detection in Jakarta commuter line

Syafiq Abdillah Umarghanis, Fariz Darari, Ari Wibisono

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

The increasing number of Commuter Line passengers calls for innovation as to how the crowd density across the carriages of Commuter Line trains can be better distributed. We develop an IoT system to detect the crowd density of Commuter Line trains so that (incoming) passengers can be better informed regarding which carriage is best to get in, hence ameliorating the train density distribution. We investigate two different approaches for density detection: CNN and YOLO+KNN. Moreover, we also analyze the impact of different single-board computers, that is, Raspberry Pi 3B and NVIDIA Jetson Nano, and that of different camera angle settings. In total, there are 20 different scenario combinations. We comparatively evaluate the density detection performance as well as the business value for each scenario.

Original languageEnglish
Title of host publication2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages121-128
Number of pages8
ISBN (Electronic)9781728192796
DOIs
Publication statusPublished - 17 Oct 2020
Event12th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020 - Virtual, Depok, Indonesia
Duration: 17 Oct 202018 Oct 2020

Publication series

Name2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020

Conference

Conference12th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020
Country/TerritoryIndonesia
CityVirtual, Depok
Period17/10/2018/10/20

Keywords

  • CNN
  • Commuter Line
  • Density Detection
  • Embedded System
  • IoT
  • KNN
  • YOLO

Fingerprint

Dive into the research topics of 'A low-cost iot platform for crowd density detection in Jakarta commuter line'. Together they form a unique fingerprint.

Cite this