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All Journal Jurnal Teknik ITS JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Mnemonic Journal of Electrical Engineering and Computer (JEECOM) ALINIER: Journal of Artificial Intelligence & Applications Jurnal Fortech SinarFe7 JASTEN (Jurnal Aplikasi Sains Teknologi Nasional Magnetika: Jurnal Mahasiswa Teknik Elektro Jurnal FORTECH
Michael Ardita
Institut Teknologi Nasional Malang
Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Physics Other

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Journal : Journal of Electrical Engineering and Computer (JEECOM)

 1 
Water Level Detection and Flood Early Warning System Using Image Processing Ilmi, Muhammad Akmal; Somawirata, I Komang; Ardita, Michael
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10851

Abstract

Image processing is a crucial method in modern technology, enabling computers to analyze and extract information from images or videos. This study focuses on the application of image processing technology to detect river water levels using CCTV cameras as part of a flood early warning system in a smart city. The YOLO (You Only Look Once) algorithm is utilized for real-time object detection, such as water levels, aiming to enhance prediction accuracy. This implementation is expected to provide richer visual data compared to traditional sensors. The study involves designing and testing a system that integrates hardware (CCTV cameras and high-spec computers) and software such as OpenCV and Python. Data in the form of river images is processed using image processing algorithms to analyze water levels in real-time. The system's performance is evaluated in terms of accuracy, precision, recall, and processing speed (FPS), as well as the environmental impact on detection results. The results indicate that the YOLO-based image processing system achieves high accuracy in detecting water levels. Additionally, the system is capable of sending early warnings via digital notifications, allowing more time for disaster mitigation. These findings suggest that image processing-based systems offer practical, efficient, and cost-effective solutions to support smart city technologies.
Flood Early Warning System with Notification Using Telegram Bot Based on IoT System Rakhman, Aditya Djulqodri; Somawirata, I Komang; Ardita, Michael
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 1 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i1.10850

Abstract

Flooding is one of the disasters that often occurs in Indonesia, especially in areas with high rainfall, such as Malang City. To improve the effectiveness of early warning, this research develops an Early Warning System (EWS) information dissemination system based on the Internet of Things (IoT). This system combines Variable Message Sign (VMS) as a visual display media and a Telegram bot to provide real-time notifications to the public. NodeMCU ESP8266 is the main microcontroller connected to a WiFi network to access data on the server. Tests were conducted to assess the accuracy of VMS synchronization, the speed of notification response, and the effectiveness of the buzzer in providing warnings. The test results show that synchronizing two VMS with different internet networks has an average time difference of 1.16 seconds, while with the same network, it is only 0.03 seconds. In addition, the VMS and Telegram bot can deliver information quickly and accurately, while the buzzer functions according to the set warning level. With this system, the dissemination of flood early warning information becomes more effective and easily accessible to the public, especially those in vulnerable areas or on the move.
Co-Authors Abdul Muntolib Achmad Affandi Alfarid Alfarid Hendro Yuwono Alifi Ashofi, Muhamad Anis Artiyani Aqshal Jadhuk Prasetyo Aryuanto Soetedjo Bagas Septiyan Zainur Rohman F. Yudi Limpraptono Ferdi Nugraha Bhakti Fery Artha Nugroho I Komang Somawirata Ilmi, Muhammad Akmal Kartiko Adi Widodo M. Ibrahim Ashari Mappagio Mira Orisa mohzulfikarzauzi Muhammad Afif Nafi Isbadrianingtyas Rakhman, Aditya Djulqodri Ridwan karim, Lucky Marsel Rizqi Cahyo M Putra Rizqi Satrio, Nur Romadhon Parada Dian Palevi, Bima Romadhon PDP, Bima Sotyohadi Suryani Faradisa, Irmalia Widodo Pudji Muljanto Wilhan Jechovanda Susanto Yosep Trindo Anugrahita Sasgitra Ardi Yuli Wahyuni Yuli Wahyuni