Design and Development of a Software-Integrated Thermal Night Vision for Military Field Operations/ Mark Joshua B. Cabangbang, John Lester Luis Cruz, Britgitte Jhay Linsangan, Kriscel Ann Marie C. Noay, and Cris Lester C. Sumalpong..-

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Cabangbang, Mark Joshua B [Author]

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Material type: Text

TextPublication details: Manila: Technological University of the Philippines, 2025.Description: ix, 88 pages: 29cmContent type:

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BTH QA 76.9 C33 2025

Dissertation note: College of Industrial Technology..- Bachelor of Engineering Technology Major in Computer Engineering Technology: Technological University of the Philippines, 2025. Summary: The study describes the creation of a software-integrated thermal night vision system using a FLIR Lepton 3.5 thermal camera and a Raspberry pi NoIR camera to improve the visibility of targets surfaced during military field operations in low-light and zero-light conditions. A portable tripod- or strap attachment prototype includes a 7.4 V Li-Po battery to power the device, along with solar-assisted charging, DC-DC conversion, and a Raspberry Pi 5 processing unit. The software architecture consists of Python backend processing, image analysis, and/or OpenCV-based AI object detection capabilities with a JavaScript web interface, to support remote dashboard capabilities. Cloud integration leverages Render for backend deployment, MongoDB Atlas for a secure cloud implementation, and Cloudflare for DNS routing, CDN acceleration, and edge security. This allows remote syncing, telemetry logging, scalability of data, and offline operation in the field. System performance was assessed on the basis of a lot of factors including accuracy and reliability of the image data, thermal range consistency, system responsiveness, reliability of the user interface and operation. Performance data were collected and analyzed using descriptive statistics. This study aligns with the Technological University of the Philippines’ (TUP) research agenda on Defense and Security Systems, the Department of Science and Technology’s (DOST) priority areas on emerging technologies, and the United Nations Sustainable Development Goal (SDG) on Peace, Justice, and Strong Institutions (Goal 16) by contributing to technological advancements that enhance safety, situational awareness, and field operational support. Keywords: Thermal Imaging, Night Vision, Dual-Vision Camera System, FLIR Lepton 3.5, Raspberry Pi 5

List(s) this item appears in: CIT-BET- Computer Engineering Technology

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Item type	Current library	Shelving location	Call number	Status	Date due	Barcode
Bachelor's Thesis CIT	TUP Manila Library	Thesis Section-2nd floor	BTH QA 76.9 C33 2025 (Browse shelf(Opens below))	Not for loan		BTH0006960

Bachelor's Thesis

College of Industrial Technology..- Bachelor of Engineering Technology Major in Computer Engineering Technology: Technological University of the Philippines, 2025.

Includes bibliographic references and index.

The study describes the creation of a software-integrated thermal night vision system using
a FLIR Lepton 3.5 thermal camera and a Raspberry pi NoIR camera to improve the
visibility of targets surfaced during military field operations in low-light and zero-light
conditions. A portable tripod- or strap attachment prototype includes a 7.4 V Li-Po battery
to power the device, along with solar-assisted charging, DC-DC conversion, and a
Raspberry Pi 5 processing unit. The software architecture consists of Python backend
processing, image analysis, and/or OpenCV-based AI object detection capabilities with a
JavaScript web interface, to support remote dashboard capabilities. Cloud integration
leverages Render for backend deployment, MongoDB Atlas for a secure cloud
implementation, and Cloudflare for DNS routing, CDN acceleration, and edge security.
This allows remote syncing, telemetry logging, scalability of data, and offline operation in
the field. System performance was assessed on the basis of a lot of factors including
accuracy and reliability of the image data, thermal range consistency, system
responsiveness, reliability of the user interface and operation. Performance data were
collected and analyzed using descriptive statistics. This study aligns with the Technological
University of the Philippines’ (TUP) research agenda on Defense and Security Systems,
the Department of Science and Technology’s (DOST) priority areas on emerging
technologies, and the United Nations Sustainable Development Goal (SDG) on Peace,
Justice, and Strong Institutions (Goal 16) by contributing to technological advancements
that enhance safety, situational awareness, and field operational support.

Keywords: Thermal Imaging, Night Vision, Dual-Vision Camera System, FLIR Lepton
3.5, Raspberry Pi 5

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