Streetfighter - Streetlight-integrated Sensor Platform - Live deployment trial

Full description

The Streetfighter live trial included a traffic and environmental sensor platform integrated into a streetlight housing on a campus road.

The project investigated the traffic detection performance of low-cost sensors to determine if a streetlight-integrated system would be viable in a ubiquitous deployment. This system included a passive-infrared (PIR) sensor for motion-based traffic detection, and sonar and lidar sensors for distance-based detection.

• The HC SR-501 PIR motion sensor typically undercounted traffic due to its detection mechanisms being ill-suited to the changing speeds and density of vehicular traffic.
• The MB1240 sonar was operating beyond its rated range and did not produce useful data.
• The LidarLite v1 lidar could detect a limited number of traffic events due, but missed most traffic due to improper mounting.

This dataset consists of the following folders/files available via a CloudStor link:

• StreetFighter Video 2015-10-08: contains 20 video files in Audio Video Interleave (.AVI) format (1.2 GB) - 2015-10-08 Med39 Traffic (01) - (20)
• StreetFighter Video 2015-12-08: contains 29 video files in Audio Video Interleave (.AVI) format (1.9 GB) - 2015-12-08 TrafficCam (01) - (29)
• StreetFighter Traffic Events 2015-10-08.zip: contains 3, 707 compressed image files in JPEG (.jpg) format (92.4 MB) - motion 2015-10-08 08.24.14 - 17.54.36
• streetfighter_sensor_data: 1 file in comma-separated values (.csv) format (379.9 MB). 
• streetfighter_sensor_data_metadata: 1 file in Markdown (.md) format (2 KB). The metadata file is also saved in PDF format and attached.
• streetfighter_video_2015-10-08: 1 file in comma-separated values (.csv) format (36 KB) - video_events_time variable

The streetfighter_sensor_data CSV file exceeds row limits for opening in Microsoft Excel. It can be handled in a number of ways e.g. imported into an Access database, opened in a text editor such as Notepad++ or opened in the 'R' software environment by using the "read.csv" function.