Generative AI in Enhancing Hydroponic Nutrient Solution Monitoring

Generative AI for IoT Hydroponics Monitoring System for Smallholder Farmers in Developing Regions This is in an effort to support AI-based narrative feedback for real-time decision-making with reference to sensor data (TDS/EC, temperature) and plant context-the pertinent data are species and age. The system, therefore, consists of an ESP32 sensor device; a Flutter mobile application; and the cloud services being offered via Thingsboard and the Gemini API. A systematic approach was undertaken, including design, implementation, integration, and usability testing. The results show effective real-time data collection and secure communication, with accurate AI feedback validated by expert judgment. The results exhibited how AI and IoT could collude in aiding smart agriculture. Future work will concentrate on enhancing the accuracy of the model based on ground truth data and improving the accessibility of the platform.

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Publication Details

Journal
Jurnal Ilmiah Telsinas Elektro Sipil dan Teknik Informasi
Published
2025-04-20
DOI
https://doi.org/10.38043/telsinas.v8i1.6242
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.75
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article

Generative AI in Enhancing Hydroponic Nutrient Solution Monitoring

I Wayan Aditya Suranata, Tamanna Quraishi, Abdul Wajid Fazil, Musawer Hakimi et al.
1 citations
Jurnal Ilmiah Telsinas Elektro Sipil dan Teknik Informasi
Smart Agriculture and AI
1.75
article

Generative AI in Enhancing Hydroponic Nutrient Solution Monitoring

I Wayan Aditya Suranata, Tamanna Quraishi, Abdul Wajid Fazil, Musawer Hakimi, Wahidullah Enayat, Zakirullah Ezam, Abdul Wahid Samadzai
article en
1 citations

Abstract

Generative AI for IoT Hydroponics Monitoring System for Smallholder Farmers in Developing Regions This is in an effort to support AI-based narrative feedback for real-time decision-making with reference to sensor data (TDS/EC, temperature) and plant context-the pertinent data are species and age. The system, therefore, consists of an ESP32 sensor device; a Flutter mobile application; and the cloud services being offered via Thingsboard and the Gemini API. A systematic approach was undertaken, including design, implementation, integration, and usability testing. The results show effective real-time data collection and secure communication, with accurate AI feedback validated by expert judgment. The results exhibited how AI and IoT could collude in aiding smart agriculture. Future work will concentrate on enhancing the accuracy of the model based on ground truth data and improving the accessibility of the platform.

Jurnal Ilmiah Telsinas Elektro Sipil dan Teknik InformasiVol. 8(1)
Namangan State University (UZ), Kabul University (AF), Ondokuz Mayıs University (TR), Badakhshan University (AF), Sayed Jamaluddin Afghani University (AF), University of the People (US), Nasional University (ID)
Openalex Percentile: Top 16%
Smart Agriculture and AI
1.75
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Generative AI in Enhancing Hydroponic Nutrient Solution Monitoring — I Wayan Aditya Suranata, Tamanna Quraishi, et al. · Jurnal Ilmiah Telsinas Elektro Sipil dan Teknik Informasi (2025) | TGRS Research Map | TGRS