A Hybrid Machine Learning and Embedded IoT-Based Water Quality Monitoring System

Adeleke, Ismail A.; Nwulu, Nnamdi; Ogbolumani, Omolola A.

doi:10.2139/ssrn.4330636

Cited by 3 publications

(10 citation statements)

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“…Kesimpulan pada bagian ini akan memberikan gambaran awal tentang arah dan implikasi pemanfaatan sistem cerdas dalam konteks pabrik AMDK yang dapat menjadi dasar untuk pengembangan penelitian lebih lanjut. [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38]…”

Section: Instrumen Dan Proses Analisisunclassified

“…Tabel parameter ini menjadi landasan untuk analisis dan pembahasan lebih lanjut terkait penerapan sistem cerdas dalam pengembangan metode monitoring kualitas air. [3], [4], [5], [6], [7], [9], [11], [14], [21], [23], [25], [26], [27], [30], [31], [32], [33], [34], [35], [36], [37], [38]. 2 Suhu [3], [4], [5], [6], [7], [8], [9], [11], [14], [17], [18], [19], [23], [28], [30], [31], [33], [34], [36], [37], [38].…”

Section: Hasil Dan Pembahasanunclassified

“…[3], [4], [5], [6], [7], [9], [11], [14], [21], [23], [25], [26], [27], [30], [31], [32], [33], [34], [35], [36], [37], [38]. 2 Suhu [3], [4], [5], [6], [7], [8], [9], [11], [14], [17], [18], [19], [23], [28], [30], [31], [33], [34], [36], [37], [38]. 3 Turbiditas (Kekeruhan)…”

Section: Hasil Dan Pembahasanmentioning

confidence: 99%

“…[3], [5], [6], [11], [14], [18], [20], [22], [23], [26], [27], [29], [30], [31], [34], [38]. 4 Dissolved Oxygen (DO) [5], [6], [7], [9], [11], [14], [17], [19], [20], [30], [31], [33], [36], [37], [38]. 5 Konduktivitas (EC) [3], [4], [5], [9], [11], [30], [31], [32], [33], [35], [36], [38].…”

Section: Hasil Dan Pembahasanmentioning

confidence: 99%

“…4 Dissolved Oxygen (DO) [5], [6], [7], [9], [11], [14], [17], [19], [20], [30], [31], [33], [36], [37], [38]. 5 Konduktivitas (EC) [3], [4], [5], [9], [11], [30], [31], [32], [33], [35], [36], [38]. 6 Debit Air [4], [8], [18], [22], [23], [24], [26], [28].…”

Section: Hasil Dan Pembahasanmentioning

confidence: 99%

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Kajian Awal Pemanfaatan Sistem Cerdas untuk Pemantauan Kualitas Air dalam Konteks Pembangunan Pabrik AMDK

Irfan Wahyu Ramadhan,

Firdaus

2024

ZTR

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Penelitian ini merupakan kajian awal yang mendalam terhadap literatur ilmiah yang membahas pemanfaatan sistem cerdas dalam pemantauan kualitas air, dengan fokus pada konteks pembangunan pabrik Air Minum Dalam Kemasan (AMDK). Melalui tinjauan berbagai jurnal, penelitian ini menyelidiki berbagai metode dan teknologi yang digunakan dalam pemantauan serta pengendalian parameter kritis air. Beberapa penelitian menawarkan solusi berbasis Internet of Things (IoT) dan kecerdasan buatan untuk pengolahan data, dengan parameter utama seperti pH, kekeruhan, suhu, dan Total Dissolved Solids (TDS). Hasil kajian menunjukkan bahwa implementasi sistem cerdas memberikan solusi yang efektif dalam mengatasi tantangan kritis terkait kualitas air, seperti pencemaran, pemantauan real-time, dan pengelolaan sumber daya air yang efisien. Analisis dalam kajian ini terfokus pada parameter kualitas air, sistem cerdas yang diadopsi, metode penetapan standar kualitas air, serta standar kualitas air yang diterapkan dalam literatur yang ditinjau. Dengan mengumpulkan dan menganalisis data dari sumber terpercaya seperti ScienceDirect, IEEE Xplore, dan Google Scholar, penelitian ini membuka perspektif baru terkait pemanfaatan sistem cerdas dalam merancang sistem monitoring kualitas air yang optimal pada tahap awal pembangunan pabrik AMDK.

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Section: Instrumen Dan Proses Analisisunclassified

Section: Hasil Dan Pembahasanunclassified

Section: Hasil Dan Pembahasanmentioning

confidence: 99%

Section: Hasil Dan Pembahasanmentioning

confidence: 99%

Section: Hasil Dan Pembahasanmentioning

confidence: 99%

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Kajian Awal Pemanfaatan Sistem Cerdas untuk Pemantauan Kualitas Air dalam Konteks Pembangunan Pabrik AMDK

Irfan Wahyu Ramadhan,

Firdaus

2024

ZTR

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Performance analysis of samplers and calibrators with various classifiers for asymmetric hydrological data

2023

IJATEE

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Water plays a crucial role in supporting the survival of all species on the globe. Access to clean, pristine water is essential for both humans and the environment [1,2]. Identifying potential sources of pollution is of great significance in predicting water contamination, as human activities have placed the quality of water at risk [3]. Over time, there has been a growing variety of water quality analyses. This has led to an increasing reliance on computational algorithms for predicting water quality and contamination.*Author for correspondence Prediction can be approached through various methods, each with its unique effectiveness [8]. A literature review reveals that most prediction studies have research gaps in the pursuit of more accurate

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An IoT-Based Hydroponic Monitoring and Control System for Sustainable Food Production

Ogbolumani,

Mabaso

2023

JD-FEWS

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The agricultural sector, historically the main source of food globally, faces unprecedented challenges due to decreasing soil fertility and unsustainable farming practices. This study presents a smart farming method, a tailored approach to cultivating food and arable crops, as a sustainable and innovative farming method. Hydroponics involves growing plants in nutrient water solutions rather than soil, establishing a controlled environment free from external conditions. We developed a sophisticated hydroponics system equipped with sensors monitoring temperature, humidity, pH, and light levels. Using IoT technologies, we enabled real-time data transmission from sensors to a dedicated web server - Amazon web services (AWS) and an Android mobile application powered by a Raspberry Pi3. This setup allows remote monitoring and control of the hydroponic system, reducing human intervention. The experiment validated the sensor network's efficiency in accurately transmitting data. The findings suggest that widespread adoption of hydroponic farming could substantially enhance global food security. Future advancements in this method could include real-time monitoring of plant growth rates by incorporating additional sensors, like carbon dioxide (CO2) sensors. This research is a significant step toward sustainable agriculture. It offers a technologically advanced solution capable of transforming food production methods and ensuring a more secure and sustainable food supply worldwide.

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A Hybrid Machine Learning and Embedded IoT-Based Water Quality Monitoring System

Cited by 3 publications

References 0 publications

Kajian Awal Pemanfaatan Sistem Cerdas untuk Pemantauan Kualitas Air dalam Konteks Pembangunan Pabrik AMDK

Kajian Awal Pemanfaatan Sistem Cerdas untuk Pemantauan Kualitas Air dalam Konteks Pembangunan Pabrik AMDK

Performance analysis of samplers and calibrators with various classifiers for asymmetric hydrological data

An IoT-Based Hydroponic Monitoring and Control System for Sustainable Food Production

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