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Journal : Bulletin of Electrical Engineering and Informatics

Control system development for monitoring nutrition of curly mustard plants in horizontal NFT hydroponic based-IoT Rusdiyana, Liza; Suhariyanto, Suhariyanto; Sampurno, Bambang; Ardiyanti Pratama, Tania
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7920

Abstract

Agricultural technology with a hydroponic system provides an alternative for farmers and communities who have limited land. This research aims to make innovations with a hydroponic monitoring system that can be done remotely via the internet that combines 2 systems, namely horizontal technique and nutrient film technique (NFT). The sample used in this study was curly mustard seeds. To combine the 2 systems, researchers designed a hydroponic prototype system using internet of things (IoT) in the form of smart hydroponics in the Blynk application. This research uses literature studies for research reference and flowcharts to regulate the flow of the program to be researched. The results showed that by using the IoT and the Blynk application, owners can monitor the nutrient content and pH of curly mustard greens remotely. The system automatically controls nutrients and pH according to the desired settings. In the growth control system of mustard curly, the use of smart hydroponics is proven to be better. Harvestable plants at the age of 34 days. Unlike the conventional system, the harvest period is at the age of 40–45 days. Therefore, smart hydroponics is more efficient because it shortens the harvesting time and saves labor.
Optimizing grouper catch efficiency using AI-controlled light fishing in Pamekasan Sampurno, Bambang; Sukma Adjie, Galih; Mashuri, Mashuri; Rusdiyana, Liza; Suhariyanto, Suhariyanto
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.10697

Abstract

Light fishing techniques are widely used to improve marine fish catches by adjusting the spectrum and intensity of light-emitting diodes (LEDs) to attract specific species. Grouper (Epinephelus spp.) are known to respond well to red light, although the optimal light intensity remains unclear. This study proposes a dual system consisting of a pulse-width modulation (PWM)-based red LED brightness controller and an artificial intelligence (AI) fish detection module using the YOLOv4 algorithm. LED brightness was varied at duty cycles of 50, 100, 150, 200, and 250 (1 kHz), producing luminous flux values between 120 and 650 lm. Field experiments conducted at the Pamekasan coast using 10 grouper samples showed that 80% of fish aggregated at a duty cycle of 150 (~420 lm at 1.5 m). ANOVA results (p0.05) indicated significant differences among light intensities, with the highest attraction observed at this level. These findings suggest the existence of an optimal light intensity threshold. Further studies with larger samples and multi-site experiments are required to validate these results and evaluate ecological impacts.