Iot-Based Real-Time Landslide Detection Using Fuzzy Logic

Nur Tihani Faqihah, Nuruddin Kamal (2023) Iot-Based Real-Time Landslide Detection Using Fuzzy Logic. Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah.

[img]
Preview
Pdf
CD20084.pdf - Accepted Version

Download (2MB) | Preview

Abstract

The goal of this senior project is to create a smart landslide detection system that will provide early warning and landslide mitigating measures. Effective monitoring and detection systems are required because landslides represent a serious hazard to infrastructure, human lives, and the environment. To build a reliable and intelligent system, the project makes use of cutting-edge technology including IoT (Internet of Things), data analytics, and fuzzy logic. The project starts with a thorough assessment of the approaches, technologies, and literature related to landslide detection. The project pinpoints the weaknesses and restrictions of the existing systems through this evaluation and suggests creative solutions to deal with these issues. The system design consists of a network of sensors, strategically placed in landslide-prone locations, including rain gauges, soil moisture sensors, accelerometers, and tilt sensors. The initiative also stresses the value of early warning systems and mitigation plans. The technology automatically informs and notifies the appropriate authorities, emergency response teams, and local populations if a potential landslide is detected. This makes it possible to quickly evacuate and to put mitigation measures in place to lessen the effects of landslides. The results of this study will have a big impact on people living in landslide-prone regions, urban planners, and disaster management organisations. The created system offers a trustworthy and effective instrument for landslip early detection, warning, and mitigation, improving public safety and lowering the potential harm brought on by these natural hazards.

Item Type: Undergraduates Project Papers
Additional Information: SV: Ts. Dr. Mohd Izham Bin Mohd Jaya
Uncontrolled Keywords: Internet of Things (IoT), data analytics, fuzzy logic
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computing
Depositing User: Mr. Nik Ahmad Nasyrun Nik Abd Malik
Date Deposited: 15 Mar 2024 02:48
Last Modified: 15 Mar 2024 02:48
URI: http://umpir.ump.edu.my/id/eprint/40685
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item