Improving Transparency with Technology in the Transportation of Illegal Wildlife
Osman, Khatra (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024053018255
https://urn.fi/URN:NBN:fi:amk-2024053018255
Tiivistelmä
This research-based thesis provides and insight on how to improve transparency in wildlife trafficking with the usage of advanced technology specifically artificial Intelligence and machine learning. The author will focus on the potential these technologies have in enhancing transparency between Asia and Africa. Wildlife trafficking is one of the top international trafficking crimes. Traffickers have been able to get away with their crimes due to corruption, bribery, and lack of officials at ports, and customs. Advanced technology will provide law enforcements and conservation organizations the monitoring and detection they will need to combat this ongoing criminal activity.
The literature review chapter includes what animal trafficking is and how it affects animals. This thesis focuses on the three most trafficked animal which are elephants, rhinos, and pangolins. The last part of the literature review discusses what artificial intelligence and machine learning are and what tools can be used in combating wildlife trafficking.
Mainly data was collected through secondary sources for example articles, research papers, and journals. The author conducted interviews with four different conservation organizations. Chapter 4 discusses findings on how transparency can be improved through AI, ML and blockchain. Challenges and limitation are discussed including data privacy concerns and doubts that some conservation have about the usage of advanced technology.
Author investigates new projects and innovations that are in works to stop wildlife trafficking including project from Microsoft using artificial intelligence and machin learning at customs. The key finding for this thesis was that it is possible to improve transparency in transportation using advanced technology, but this will need a strong collaboration between law enforcements, governments, and conservation organizations.
The literature review chapter includes what animal trafficking is and how it affects animals. This thesis focuses on the three most trafficked animal which are elephants, rhinos, and pangolins. The last part of the literature review discusses what artificial intelligence and machine learning are and what tools can be used in combating wildlife trafficking.
Mainly data was collected through secondary sources for example articles, research papers, and journals. The author conducted interviews with four different conservation organizations. Chapter 4 discusses findings on how transparency can be improved through AI, ML and blockchain. Challenges and limitation are discussed including data privacy concerns and doubts that some conservation have about the usage of advanced technology.
Author investigates new projects and innovations that are in works to stop wildlife trafficking including project from Microsoft using artificial intelligence and machin learning at customs. The key finding for this thesis was that it is possible to improve transparency in transportation using advanced technology, but this will need a strong collaboration between law enforcements, governments, and conservation organizations.