IEEE Technology and Society Magazine - September 2023 - 89

Figure 1. Overview of data and model for DWF industry.
depicts the overview of data and models used in
the DWF industry.
HAR technology can provide valuable insights
into labor exploitation and abuse in Taiwan's DWF
industry. However, it is essential to carefully consider
the limitations and challenges of this approach [5].
HAR is a technique that allows computers to understand
and identify human actions. The fishermen are
often abused by their employers, who exploit them
for cheap labor. They are often forced to work long
hours without being paid overtime wages and work in
unsafe conditions with no safety gear. This research
article analyzes the labor exploitations of migrant
fishermen by their employers through HAR technology.
The article will first provide a background on
the fishery industry in Taiwan before discussing how
this technology can be implemented to monitor the
exploitation of these workers. The global fishing watch
(GFW) [6] is a system that allows fishermen, conservationists,
government officials, and the public to detect
illegal fishing in near real-time. Last year, new features
were added to the system that allows fishing vessels
to be monitored by satellite. These two features have
helped expose labor exploitation and environmental
crimes. The GFW provides application programming
interface (API), which can be used to access the vessel's
location, vessel id, name, and fisher details from
the satellite-based vessel monitoring system.
September 2023
The data generated by the GFW gives an overview
of fishing operations. The data is not based on
real-time worker work hours. Real-time work hours
verification is also a complicated task. The real-time
work is analyzed using CCTV data. It is challenging
because the videos are captured during the night
and in a very unstable environment with water
splashing aboard, and all fishermen are dressed in
raincoats, rain boots, rain caps, etc. Thus, it is tough
to detect humans accurately in such videos. Recognizing
human actions also becomes quite challenging
due to the multiple occlusions in the working
areas such as fishing equipment and fish processing
tools, so we are motivated to develop a fisherman
action recognition model to solve labor exploitation
and abuse [7], [8], [9], [10].
Methodology
We have implemented a comprehensive system
combining CCTV and the mobile face verification
application system (MFVAS) to monitor and recognize
fishermen's actions effectively. By utilizing
computer vision and deep learning algorithms,
we can analyze the CCTV video footage and accurately
identify specific actions or behaviors performed
by the fishermen. Through this integrated
system, we can actively monitor the work of the
89

IEEE Technology and Society Magazine - September 2023

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