Baharudin, Muhamad Lutfiashraf (2021) Weather monitoring system for drone docking station. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)
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Weather monitoring system for drone docking station.pdf - Submitted Version Download (2MB) |
Abstract
The key goals of Weather Monitoring System for Drone Docking Station was to assist drone pilots in accessing and obtaining weather data. The weather monitoring technology allows the drone to dock anywhere in real time. Drones have both autopilot and manual flight modes. In comparison to manual drones, autoflight allows drones to fly and dock autonomously. However, in order to focus on weather monitoring, this project only used manual piloting. To study the weather and climate, atmospheric conditions like wind, rain, humidity and temperature are measured using weather station facility. The information provided can be used to predict weather forecast for the drone to dock safely. Without a weather station, users can’t be alerted of the strong winds, heavy rain, heat waves, or any other weather-related emergency. As a result, the drone suffers damage, perhaps costing additional money to repair. Different sensors are used as a device to collects data related to the weather and environment for the weather station. To overcome the problems faced, there are techniques that can be implemented to assist this project. Internet of Things with sensors will be used to build a weather station for the project. The weather station can help provide data for forecasts in order to use drone. The user can view the history of information as well once a weather station is connected. Command prompt is used to connect the IP address with the system. The Ip will receive and react to the ping and command to enter the raspberry pi. Finally, the result will show at command prompt and at the IoT program.
Item Type: | Final Year Project (Project Report) |
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Uncontrolled Keywords: | Weather, Drone, Sensors, Monitoring, Drones, Dock, Manual, Rain |
Divisions: | Library > Final Year Project > FTKEE |
Depositing User: | Sabariah Ismail |
Date Deposited: | 29 May 2023 08:27 |
Last Modified: | 26 Nov 2024 00:02 |
URI: | http://digitalcollection.utem.edu.my/id/eprint/27433 |
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