Muhammad Izzat, Zakaria (2023) Design and implementation of flood monitoring and warning system based on internet of things. Masters thesis, Universiti Malaysia Pahang (Contributors, Thesis advisor: Noorazliza, Sulaiman).
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Abstract
Floods are unavoidable phenomena that can cause massive loss of people's lives and the destruction of infrastructure. Flash floods rise rapidly in a flood-prone area, which results in property damage, but the impact on human lives is somewhat preventable by the presence of monitoring systems. Although there are many systems widely in practice by disaster management agencies in monitoring flood levels, most of these systems are limited in range. For example, some systems implementing the Long-Range Wide Area Network (LoRaWAN) have a maximum distance of 300m from the gateway. However, the maximum distance that LoRaWAN can reach is 1.5km. Then, the study on the parameter that involved in LoRaWAN for the Flood Monitoring and Warning System (FMWS) is limited. Furthermore, in most developing countries, the conventional flood gates in water canals are manually operated and suffer from the lack of real-time monitoring of water levels which might lead to an overflow in the channels and flash floods. On top of that, the lack of real-time data analysis in the system that can be accessed is one of the limitations in Malaysia. Therefore, this research design and implementation multiple LoRa-based smart sensors with a LoRaWAN gateway as a network testbed for monitoring flood levels and evaluating the parameter of LoRaWAN. Then, the LoRaWAN’s activation was compared and analysed to identify the best activation for the FMWS. Lastly, the real-time assessment of the risk due to the flood level has been enabled on the Tago.IO dashboard for triggering an early flood warning. The proposed FMWS with LoRaWAN uses an ultrasonic sensor with an Arduino microcontroller to measure water level, Long-Range (LoRa) as a communication module, and a single gateway. The end nodes have been tested in several scenarios to test the FMWS’s communication performance in terms of Received Signal Strength Indication (RSSI), Signal Noise Ratio (SNR), delay, and the Percentages of Data Received (PDR). The design of the sensing node involved the hardware and software with the solar panel as the power source. A 3 Dimension (3D) model for the end node was developed for casing the sensing node. The testing area for testing the performance of LoRaWAN is a 2km radius. Throughout the testing, the proposed system communicates up to 2km in single and multiple node cases. On top of that, the multiple nodes have higher overall SNR value compared to the single node where 56% of all result are positive for multiple nodes while the single node exhibit only 50%. In addition, the RSSI and SNR have impact on the PDR. However, the delay inversely perorational with RSSI, SNR and PDR values. The recommended activation for FMWS is Activation By-Personalization, (ABP) since it is over complete control, especially for achieving a high PDR. Lastly, the data on Tago.IO was accessed via webpages and Tago.IO mobile application. In conclusion, the FMWS able to communicate to the gateway at 1.5km distance. However, the higher the SF, the higher the network's performance at long distances. The ABP is the activation that is suitable for the proposed FMWS. Lastly, the warning system will trigger once the water level reaches the warning level.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | Thesis (Master of Science) -- Universiti Malaysia Pahang – 2023, SV: Dr. Noorazliza binti Sulaiman, NO.CD: 13428 |
| Uncontrolled Keywords: | flood monitoring system, internet of things (iot) |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology |
| Depositing User: | Mr. Nik Ahmad Nasyrun Nik Abd Malik |
| Date Deposited: | 14 Nov 2023 23:47 |
| Last Modified: | 14 Nov 2023 23:47 |
| URI: | http://umpir.ump.edu.my/id/eprint/39310 |
| Download Statistic: | View Download Statistics |
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