Control of object prediction using smart optimized water indication (sonic) algorithm for flood detection

Abstract

This paper presents the development of a new algorithm in the field of image processing that enables the detection of flood disasters quickly and accurately, using the SONIC (Smart water indication optimizer) method. Concentrated detection in online real-time camera systems has been performed by several tests consisting of classifying camera objects, thermal cameras, and learning cameras. The introduction to the RTC web enables real-time and multiplatform data delivery systems on devices comprised of computers and android gadgets, on object classification using the SONIC algorithm. The object consists of humans, yellow balls, and green balls, with each sample having 50 points of view. The experiments showed test results up to 100% per age with real-time camera capture speeds.

Performance analysis of flood control buildings Mati river watershed area

“…The results of this flood analysis form the basis for analyzing the capacity of rivers and other flood control structures. Many methods can be used to calculate design floods such as the Nakayasu method, Gama I and the rational method (Sarminingsih, 2018;Gunawan et al, 2020;Utomo et al, 2021;Adoe et al, 2021). Figure 3 shows an analysis of the design flood analysis with the Nakayasu method.…”

Pengembangan Sistem Deteksi Otomatis FOD dengan YOLOv5 di Lingkungan Landasan Bandara

“…Sistem cerdas, seperti kecerdasan buatan (Artificial Intelligence/AI), machine learning, dan deep learning, telah merevolusi cara kita bekerja, berkomunikasi, dan berinteraksi dengan lingkungan (Sakti et al, 2021) . Metode yang paling populer dalam deteksi objek adalah menggunakan teknik deep learning (Utomo et al, 2021). YOLO (You Only Look Once) adalah salah satu model deep learning yang telah menjadi sangat terkenal dalam deteksi objek.…”