Leveraging artificial intelligence (AI) technology for enhanced border surveillance at the Malaysia-Thailand land border

Despite various initiatives taken by the government, Malaysia shows a trend of increasing migrant smuggling. Weaknesses in the border control management have resulted in the escape of smugglers at the border gate. Thus, this article aims to assess the potential application of artificial intelligence...

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Main Authors: Norilyani Md Nor,, Marina Abdul Majid,, Andika Ab. Wahab,
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2024
Online Access:http://journalarticle.ukm.my/24675/1/%5B54-65%5D%2076662-267930-1-PB.pdf
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spelling my-ukm.journal.246752025-01-10T03:32:46Z http://journalarticle.ukm.my/24675/ Leveraging artificial intelligence (AI) technology for enhanced border surveillance at the Malaysia-Thailand land border Norilyani Md Nor, Marina Abdul Majid, Andika Ab. Wahab, Despite various initiatives taken by the government, Malaysia shows a trend of increasing migrant smuggling. Weaknesses in the border control management have resulted in the escape of smugglers at the border gate. Thus, this article aims to assess the potential application of artificial intelligence (AI) technology at the Malaysia-Thailand land border in enhancing border security. Based on a series of interviews with relevant ministries, enforcement agencies, technology experts, academic experts and other stakeholders, as well as secondary sources, this study found that AI technology has the potential to overcome issues pertaining to weak border control management faced by the Royal Malaysian Police (RMP), the main enforcement agency that manages the Malaysia-Thailand land border along with other enforcement agencies. Among the issues are a lack of enforcement, integrity concerns and limited manpower to control Malaysia’s porous borders. However, some strategies should be taken to adapt AI to our border security system. Thus, this article analyses the concept of Integrated Border Management (IBM) to obtain coordination and cooperation among all relevant authorities and countries involved in the adaptation of AI technology at the Malaysia-Thailand land border. This article also analyses how Malaysia should respond to the ethical implications of AI technology. This study will help promote a cross-border collaboration network between Malaysia and related foreign countries in dealing with migrant smuggling issues. Penerbit Universiti Kebangsaan Malaysia 2024-11 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/24675/1/%5B54-65%5D%2076662-267930-1-PB.pdf Norilyani Md Nor, and Marina Abdul Majid, and Andika Ab. Wahab, (2024) Leveraging artificial intelligence (AI) technology for enhanced border surveillance at the Malaysia-Thailand land border. e-Bangi Journal of Social Sciences and Humanities, 21 (4). pp. 54-65. ISSN 1823-884x http://ejournal.ukm.my/ebangi/index
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Despite various initiatives taken by the government, Malaysia shows a trend of increasing migrant smuggling. Weaknesses in the border control management have resulted in the escape of smugglers at the border gate. Thus, this article aims to assess the potential application of artificial intelligence (AI) technology at the Malaysia-Thailand land border in enhancing border security. Based on a series of interviews with relevant ministries, enforcement agencies, technology experts, academic experts and other stakeholders, as well as secondary sources, this study found that AI technology has the potential to overcome issues pertaining to weak border control management faced by the Royal Malaysian Police (RMP), the main enforcement agency that manages the Malaysia-Thailand land border along with other enforcement agencies. Among the issues are a lack of enforcement, integrity concerns and limited manpower to control Malaysia’s porous borders. However, some strategies should be taken to adapt AI to our border security system. Thus, this article analyses the concept of Integrated Border Management (IBM) to obtain coordination and cooperation among all relevant authorities and countries involved in the adaptation of AI technology at the Malaysia-Thailand land border. This article also analyses how Malaysia should respond to the ethical implications of AI technology. This study will help promote a cross-border collaboration network between Malaysia and related foreign countries in dealing with migrant smuggling issues.
format Article
author Norilyani Md Nor,
Marina Abdul Majid,
Andika Ab. Wahab,
spellingShingle Norilyani Md Nor,
Marina Abdul Majid,
Andika Ab. Wahab,
Leveraging artificial intelligence (AI) technology for enhanced border surveillance at the Malaysia-Thailand land border
author_facet Norilyani Md Nor,
Marina Abdul Majid,
Andika Ab. Wahab,
author_sort Norilyani Md Nor,
title Leveraging artificial intelligence (AI) technology for enhanced border surveillance at the Malaysia-Thailand land border
title_short Leveraging artificial intelligence (AI) technology for enhanced border surveillance at the Malaysia-Thailand land border
title_full Leveraging artificial intelligence (AI) technology for enhanced border surveillance at the Malaysia-Thailand land border
title_fullStr Leveraging artificial intelligence (AI) technology for enhanced border surveillance at the Malaysia-Thailand land border
title_full_unstemmed Leveraging artificial intelligence (AI) technology for enhanced border surveillance at the Malaysia-Thailand land border
title_sort leveraging artificial intelligence (ai) technology for enhanced border surveillance at the malaysia-thailand land border
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2024
url http://journalarticle.ukm.my/24675/1/%5B54-65%5D%2076662-267930-1-PB.pdf
http://journalarticle.ukm.my/24675/
http://ejournal.ukm.my/ebangi/index
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score 13.23239