Chaurina, Agfanadita Rezkia Pengukur Ketinggian Air Bendungan Karangkates Dengan IoT Terintegrasi AWS EC2 Dan RDS. Project Report (Praktek Kerja Lapang). UPN Vetetan Jawa Timur. (Unpublished)
![[img]](https://repository.upnjatim.ac.id/style/images/fileicons/text.png) |
Text (Cover)
21081010138_Cover.pdf Download (364kB) |
|
Text (Bab 1)
21081010138_bab 1.pdf Download (13kB) |
|
Text (Bab 2)
21081010138_bab 2.pdf Restricted to Repository staff only until 20 September 2026. Download (35kB) |
|
Text (Bab 3)
21081010138_bab 3.pdf Restricted to Repository staff only until 2026. Download (710kB) |
|
Text (Bab 4)
21081010138_bab 4.pdf Restricted to Repository staff only until 20 September 2026. Download (174kB) |
|
Text (Bab 5)
21081010138_bab 5.pdf Download (8kB) |
|
Text (Daftar Pustaka)
21081010138_dapus.pdf Download (4kB) |
|
Text (Lampiran)
21081010138_lampiran.pdf Restricted to Repository staff only Download (205kB) |
Abstract
The Karangkates Dam Water Level Measurement Project with IoT Integrated with AWS EC2 and RDS aims to develop a real time reservoir water level monitoring system using Internet of Things (IoT) technology. This system employs the ESP8266 microcontroller and HC-SR04 ultrasonic module to measure water levels, with data transmitted via the MQTT protocol to the HiveMQ broker and stored in a MySQL database hosted on AWS RDS. The backend application, built using Node.js and Express.js running on AWS EC2, processes the data and presents it through an interactive web interface, with data visualization using Chart.js and WebSocket via the Socket.io library. This project provides an efficient and accurate monitoring solution, assisting reservoir managers in making decisions related to water management and flood risk mitigation. The system enables more efficient monitoring, early detection of potential flood hazards, and support for faster and more accurate decision-making. Despite facing challenges such as limited AWS lab access and lack of active participation from some team members, the implemented solutions successfully addressed these obstacles through improved team communication, resource optimization, and the use of edge computing technology. Further development suggestions include extending AWS lab access, enhancing the user interface, and adding features such as dam height status identification and real-time notification systems. Integration with weather monitoring systems is also proposed to provide more accurate predictions, while improving data analysis algorithms with machine learning or AI can offer deeper insights. Overall, this project demonstrates the significant potential of IoT technology in more effective and responsive water resource management. Keywords : Water Level Measurement, IoT, AWS, Karangkates Dam
| Item Type: | Monograph (Project Report (Praktek Kerja Lapang)) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Contributors: |
|
||||||||
| Subjects: | A General Works > AI Indexes (General) | ||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||
| Depositing User: | Agfanadita Rezkia | ||||||||
| Date Deposited: | 16 Jun 2025 04:54 | ||||||||
| Last Modified: | 16 Jun 2025 04:54 | ||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/29866 |
Actions (login required)
 |
View Item |