Transforming a Customized Drone into an Advanced Forensic Investigation Platform
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Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study deals with the process of transforming a specially designed drone into an advanced forensic investigation platform. First, the details and features of the drone system design are analyzed. This design process is particularly notable for its lightweight structure, high maneuverability and long flight time. These features make the drone an ideal platform for forensic investigation operations. The system design also includes the integration of various sensors. These sensors include high-resolution cameras, imaging devices and air quality measurement sensors. In particular, the use of cameras provides detailed visual data during the forensic investigation process and optimizes evidence collection. Thermal imaging devices, on the other hand, work effectively at night and in harsh weather conditions, increasing the success of forensic investigation operations. In addition, air quality measurement sensors are used to detect explosives, harmful gases and other potentially hazardous substances. These sensors contribute to reliable results by automating the collection and analysis of air samples. In conclusion, this study presents a significant advancement in the field of forensic investigation, focusing on the system design and integration of sensors to enhance the usability of a specially designed drone in forensic investigation operations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Açıklama
International Conference on Advanced Engineering, Technology and Applications, ICAETA 2024 -- 24 May 2024 through 25 May 2024 -- Catania -- 323259
Anahtar Kelimeler
air quality measurement units, autonomous control, drone system design, sensor calibration
Kaynak
Lecture Notes in Networks and Systems
WoS Q Değeri
Scopus Q Değeri
Q4
Cilt
1138 LNNS
