Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

Optimizing drone-assisted victim localization and identification in mass-disaster management: a study on feasible flying patterns and technical specifications

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 14 No. 4 (2024)

DOI
10.11591/ijece.v14i4.pp4097-4109
ISSN
2722-2578, 2088-8708
Published
2024-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

The prompt emphasizes the importance of identifying victims in a disaster area within 48 hours and highlights the potential benefits of using drones in search and rescue missions. However, the use of drones is limited by factors such as battery life, processing speed, and communication range. To address these limitations, the paper presents a detailed research study on the most effective flying pattern for drones during search and rescue missions. The study utilized energy consumption and coverage area as performance metrics and collected precise images that could be analyzed by the forensic team. The research was conducted using OMNET++ and fieldwork at Pulau Sebang, Melaka, in collaboration with search and rescue agencies in Malaysia. The results suggest that the square flying pattern is the most effective, as it provides the highest coverage area with reasonable energy utilization. Both simulation and fieldwork results showed coverage of 100% and 97.96%, respectively, for this pattern. Additionally, the paper provides technical specifications for rescue teams to use when deploying drones during search and rescue missions.

Collaboration network of the authors

21 authors · 44 co-authorship links · 9 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universiti Teknologi MARA
  • Universiti Teknikal Malaysia Melaka
  • Malaysian Nuclear Agency
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Mohd Sabri MinhatMalaysian Nuclear Agency4
Megat Syahirul Amin Megat AliUniversiti Teknologi MARA2
Aisyah Hartini JahidinUniversiti Teknologi MARA2
Mohd Nasir TaibUniversiti Teknologi MARA2
Azlina IdrisUniversiti Teknologi MARA2
Nor Syazwani Mohd PakhrudinUniversiti Teknologi MARA2
Norsuzila Ya’acobUniversiti Teknologi MARA2
Ahmad Azhari Mohamad NorUniversiti Teknologi MARA2
Ibnu HajarUniversiti Teknologi MARA2
Fadila LazimUniversiti Teknologi MARA1
Hajar Ja’afarUniversiti Teknologi MARA1
Suziyani RohafauziUniversiti Teknologi MARA1
Ilham RustamUniversiti Teknologi MARA1
Mohamad Taib MiskonUniversiti Teknologi MARA1
Darmawaty Mohd AliUniversiti Teknologi MARA1
Wan Haszerila Wan HassanUniversiti Teknikal Malaysia Melaka1
Juwita Mohd SultanUniversiti Teknikal Malaysia Melaka1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Optimizing drone-assisted victim localization and identification in mass-disaster management: a study on feasible flying patterns and technical specifications</dc:title><dc:creator>Azmi, Intan Nabina</dc:creator><dc:creator>Kassim, Murizah</dc:creator><dc:creator>Mohd Yussoff, Yusnani</dc:creator><dc:creator>Md Tahir, Nooritawati</dc:creator><dc:description>&lt;jats:p&gt;The prompt emphasizes the importance of identifying victims in a disaster area within 48 hours and highlights the potential benefits of using drones in search and rescue missions. However, the use of drones is limited by factors such as battery life, processing speed, and communication range. To address these limitations, the paper presents a detailed research study on the most effective flying pattern for drones during search and rescue missions. The study utilized energy consumption and coverage area as performance metrics and collected precise images that could be analyzed by the forensic team. The research was conducted using OMNET++ and fieldwork at Pulau Sebang, Melaka, in collaboration with search and rescue agencies in Malaysia. The results suggest that the square flying pattern is the most effective, as it provides the highest coverage area with reasonable energy utilization. Both simulation and fieldwork results showed coverage of 100% and 97.96%, respectively, for this pattern. Additionally, the paper provides technical specifications for rescue teams to use when deploying drones during search and rescue missions.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2024-08-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v14i4.pp4097-4109</dc:identifier><dc:identifier>10.11591/ijece.v14i4.pp4097-4109</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 14 No 4 (2024); 4097</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/34766/17526</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>