Research Data

StreetFighter controlled trials - Pedestrian

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General
Title
StreetFighter controlled trials - Pedestrian
Type
Dataset
Date Record Created
2018-11-30
Date Record Modified
2019-01-04
Language
English
Coverage
Date Coverage
2017-03-24 to 2017-03-25
Time Period
(no information)
Geospatial Location
  • Reid Park, Townsville, Queensland, Australia
Description
Descriptions
  1. Type: full

    Sensor detection accuracy test of the StreetFighter traffic sensor platform using controlled traffic.

    This dataset contains the information specific to pedestrian testing.

    The dataset contains recorded sensor events from the following sensors:

    • 1 Panasonic AMN33111J Narrow spot motion detection
    • 2 HC-SR501 wide area motion detectors
    • 1 LidarLite v1 lidar

    Each sensor was mounted at a position six metres above the road surface, facing downwards towards the road.

    This dataset consists of the following folders/files:

    • Overpass- Pedestrian Tests: 1 data file in OpenDocument (.ods) format (88 KB) - analysis of collected results
    • Pedestrian Events.zip: contains 159 compressed image files in JPEG (.jpg) format (3.3 MB) and a CSV file (TafficLog) (3 KB) - detections counted by computer vision
    • Data.zip: contains 18 files in comma-separated values (.csv) format and a metadata file in markdown (.md) format (80.3 KB) - data collected from each sensor over the course of testing. The markdown file (sensor data metadata)┬áis also saved in PDF format and attached.

    The Cloudstor link includes the files listed above (Pedestrian Test Results.ods has been renamed as Overpass-Pedestrian tests.ods in the attached files) as well as:

    • Raw.zip: contains 8 log files (.log) and a CSV file for wifi_devices-combined (114 KB)
    • Video.zip: contains 10 MOV (.mov) video files (7.2 GB)
Related Publications
  1. Mohring, Karl, Myers, Trina, and Atkinson, Ian (2018) A controlled trial of a commodity sensors for a streetlight-mounted traffic detection system. In: Proceedings of the Australasian Computer Science Week Multiconference. From: ACSW'18: Australasian Computer Science Week Multiconference, 29 January - 2 February 2018, Brisbane, QLD, Australia.
Related Websites
  1. Tripwire code library - Lidar algorithm
  2. Test platform firmware
  3. PIR code library
  4. Thermal tracking code library
  5. Thermal tracking firmware
Related Data
(no information)
Related Services
(no information)
Technical metadata
(no information)
People
Creators
  1. Owned by: Mr Karl Mohring , karl.mohring@jcu.edu.au , College of Business, Law & Governance, eResearch Centre
Primary Contact
Mr Karl Mohring, karl.mohring@jcu.edu.au
Supervisors
  1. A/Prof Trina Myers , trina.myers@jcu.edu.au
  2. Prof Ian Atkinson , ian.atkinson@jcu.edu.au
Collaborators
(no information)
Subject
Fields of Research
  1. 090601 - Circuits and Systems (090601)
Socio-Economic Objective
  1. 890199 - Communication Networks and Services not elsewhere classified (890199)
Keywords
  1. commodity sensors
  2. internet of things
  3. traffic detection
Research Activity
(no information)
Research Themes
Industries and Economies in the Tropics
People and Societies in the Tropics
Rights
License
CC BY-NC-SA 4.0: Attribution-Noncommercial-Share Alike 4.0 International
License - Other
(no information)
Access Rights/Conditions
Open access. If the data is not freely accessible via the link provided, please contact the nominated data manager or researchdata@jcu.edu.au for assistance.
Type
open
Rights
(no information)
Data
Data Location
Online Locations
  1. https://cloudstor.aarnet.edu.au/plus/s/hILTx7gJRK1GkqN
Attachments
  1. Pedestrian Events.zip (Storage Attachments, Public)
  2. Data.zip (Storage Attachments, Public)
  3. metadata.pdf (Supporting Material, Public)
  4. Overpass - Pedestrian Tests.ods (Storage Attachments, Public)
Stored At
(no information)
Citation
Cite:
Mohring, K. (2018). StreetFighter controlled trials - Pedestrian. James Cook University. (dataset). http://dx.doi.org/10.25903/5c1c71f11f3ba
Digital Object Identifier (DOI):
10.25903/5c1c71f11f3ba