Autonomous aerial survey platform
| dc.contributor.advisor | Huda, A.S. Nazmul | |
| dc.contributor.advisor | Taz, Nahid Hossain | |
| dc.contributor.advisor | Shams, Sharif Mohd | |
| dc.contributor.author | Kowshik, Md. | |
| dc.contributor.author | Nabil, Sultanul Arefin | |
| dc.contributor.author | Bushra, Mushfeka Anika | |
| dc.contributor.author | Shawn, Al Hossain | |
| dc.contributor.department | Department of Electrical and Electronic Engineering | |
| dc.date.accessioned | 2026-04-20T04:37:11Z | |
| dc.date.available | 2026-04-20T04:37:11Z | |
| dc.date.copyright | 2026 | |
| dc.date.issued | 2026-01 | |
| dc.description | Cataloged from PDF version of final year design project. | |
| dc.description | Includes bibliographical references (page 239-246). | |
| dc.description | This final year design project is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2026. | en_US |
| dc.description.abstract | The project explores the concept of developing an autonomous aerial survey drone with the ability to conduct an efficient and high-resolution survey using a minimum level of human involvement. The system combines with powerful navigation and mission planning algorithms to provide feasible information gathering across various terrains. The drone can operate according to predefined survey patterns, dynamic environments. It can autonomously control data collection, storage and transmission using onboard real time optimization for post processing. The results of the survey are anonymized imagery and multi sensor data that can be used in surveying and fast evaluation in fields like agriculture, infrastructure inspection, disaster response and environmental monitoring. The project focuses on safety, reliability, and scalability. Whereby the survey operations can be repeated at a low cost and used in decision support and continuous monitoring. | en_US |
| dc.description.degree | B.Sc. in Electrical and Electronic Engineering | |
| dc.description.statementofresponsibility | Md. Kowshik | |
| dc.description.statementofresponsibility | Sultanul Arefin Nabil | |
| dc.description.statementofresponsibility | Mushfeka Anika Bushra | |
| dc.description.statementofresponsibility | Al Hossain Shawn | |
| dc.format.extent | 347 pages | |
| dc.identifier.other | ID 20121020 | |
| dc.identifier.other | ID 20221030 | |
| dc.identifier.other | ID 21321070 | |
| dc.identifier.other | ID 22121073 | |
| dc.identifier.uri | http://hdl.handle.net/10361/27955 | |
| dc.language.iso | en | en_US |
| dc.publisher | BRAC University | en_US |
| dc.rights | BRAC University project reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. | |
| dc.subject | Automated data acquisition | en_US |
| dc.subject | Deep learning | en_US |
| dc.subject | Operational security | en_US |
| dc.subject | Automation. | en_US |
| dc.subject | Computer vision | en_US |
| dc.subject.lcsh | Deep learning (Machine learning). | |
| dc.subject.lcsh | Automatic data collection systems. | |
| dc.title | Autonomous aerial survey platform | en_US |
| dc.type | Project Report | en_US |