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All Journal RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Nazwa Aulia
Universitas Malikussaleh
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Development of Portable IoT-Based Fish Pond to Enhance Freshwater Aquaculture Efficiency Rifkial Iqwal; M Ishlah Buana Angkasa; Nazwa Aulia; Subhan Hartanto; Tejas Shinde; Muhammad Fikry; Zara Yunizar
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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Abstract

This paper presents the development of iPooL, a portable Internet of Things (IoT)-based fish pond system designed to optimize freshwater fish farming, particularly in resource-constrained and urban environments. By integrating real-time monitoring of essential water parameters—such as pH, temperature, dissolved oxygen, and ammonia levels—iPooL ensures that optimal environmental conditions are maintained for fish health and growth. The system employs IoT sensors connected to an ESP32 microcontroller, which processes and transmits data to a cloud platform, enabling farmers to receive real-time alerts and manage their ponds via a mobile app. Field trials demonstrated that the iPooL system reduces fish mortality by 20% and improves fish growth rates by maintaining stable water conditions. Additionally, the automation of feeding schedules and water management reduces operational costs, particularly in labor and feed, resulting in a 30% increase in profitability. With an estimated return on investment (ROI) within one year, iPooL offers a cost-effective solution for both small- and medium-scale fish farmers. The system also promotes environmental sustainability by optimizing water usage and reducing the need for chemical additives. Its portability allows fish farming in non-traditional environments, such as urban rooftops, contributing to decentralized food production and reducing the environmental impact of transporting fish to urban markets. iPooL’s scalability, combined with future integration of artificial intelligence and renewable energy sources, positions it as a transformative tool for the aquaculture industry, supporting both economic development and sustainable farming practices.
VIDEO TRANSCRIPTION DAN VOICE SYNTHESIS UNTUK SISTEM PENERJEMAH ISYARAT BAHASA INDONESIA: VIDEO TRANSCRIPTION AND VOICE SYNTHESIS FOR INDONESIAN LANGUAGE SIGN TRANSLATION SYSTEM Nazwa Aulia; Muhammad Fikry; Ar Razi
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.6608

Abstract

Communication is a way for humans to convey information, ideas, thoughts, feelings, or massages verbally or nonverbally. People with hearing impairments use expressions and symbols due to hearing limitations, the term tuna means less and rungu means hearing. To bridge communication, sign language translation through the development of systems such as text-to-speech can help improve accessibility between people with hearing impairments and spoken language users in various contexts of everyday life. The Indonesian Sign Language (SIBI) translation system in this study was built the waterfall research method in which each process will be carried out in stages and sequentially, starting from problem analysis and creating a conceptual system in order to strengthen the theorectical foundation and answer the formulation of the problems raised, this study uses the Keras deep learning model and the Convolutional Neural Network (CNN) approach. The test results show that the system is able to classify hand gestures and convert them into text and voice, in addition to the average respone time of less than one second, which is around 104 miliseconds per step. This shows that the system can operate in real-time with a fast and consistent response. Video transcription and voice synthesis for an Indonesian sign language translation system using the Python programming language were successfully implemented, supported by various libraries such as OpenCV, CVZone, and GTTS (Google Text-To-Speech). Testing results on 15 movement classes with 150 trials showed an average movement classification accuracy of 87%. Further research is recommended to increase the number of subjects and dataset diversity to improve the model’s generalizability.
Co-Authors Ar Razi M Ishlah Buana Angkasa Muhammad Fikry Muhammad Fikry Rifkial Iqwal Subhan Hartanto Tejas Shinde Zara Yunizar