Water contamination analysis in IoT enabled aquaculture using deep learning based AODEGRU

Arepalli, Peda Gopi; Naik, K. Jairam

doi:10.1016/j.ecoinf.2023.102405

Cited by 8 publications

(2 citation statements)

References 21 publications

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“…Recording Wastewater Treatment Plant Outlet Water Discharge Using Google Sheets [17] Prototipo funcional IOT para determinar la viabilidad de instalación del modelo atrapanieblas tipo chileno en el municipio de Chiquinquirá Boyacá [20] Sistema IoT para el análisis de calidad de agua [4] Automation of Residential Water Flowmeter [16] Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning [21] Water contamination analysis in IoT-enabled aquaculture using deep learning-based AODEGRU [22] Internet of Things sensors and support vector machine integrated intelligent irrigation system for the agriculture industry [23] Critical review of water quality analysis using IoT and machine learning models…”

Section: Iot Flowmetermentioning

confidence: 99%

Implementation of IoT Sensors in Fog Collector Systems and Flowmeters for the Control of Eater Collection and Distribution

Carrera-Villacrés,

Gallegos-Ríos,

Chiliquinga-López

et al. 2024

Preprint

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This study describes the implementation of IoT sensors in drinking water systems and fog collector systems in low-income communities in Ecuador. The influence and handling of these sensors are analyzed, as well as the materials and methods used in their implementation. The importance of validating the accuracy and reliability of IoT sensors compared to professional devices, especially in mountain areas, is highlighted. In addition, it is mentioned that the cost-benefit of using IoT sensors in fog catchers and drinking water networks depends on several factors, such as the scale of the project, specific objectives, and available resources. Finally, it is highlighted that the use of IoT sensors in smart construction and water collection systems has proven to be beneficial in preventing effects on the operation.

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Section: Iot Flowmetermentioning

confidence: 99%

Implementation of IoT Sensors in Fog Collector Systems and Flowmeters for the Control of Eater Collection and Distribution

Carrera-Villacrés,

Gallegos-Ríos,

Chiliquinga-López

et al. 2024

Preprint

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“…One of the most significant aspects of IoT in spa care is the ability to monitor patients, both inside and outside spa facilities, in real-time through devices such as smartwatches, wristbands, or wearable sensors that collect data on heart rate, body temperature, blood oxygen levels and other vital indicators [24][25][26][27][28]. These data can be transmitted to a centralized monitoring system for accurate and timely analysis [29,30]. Telemedicine, using these technologies, enables timely intervention in case of abnormalities, improving the safety and effectiveness of spa treatment [31].…”

Section: Introductionmentioning

confidence: 99%

Integrating the Internet of Things (IoT) in SPA Medicine: Innovations and Challenges in Digital Wellness

Casillo,

Cecere,

Colace

et al. 2024

Computers

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Integrating modern and innovative technologies such as the Internet of Things (IoT) and Machine Learning (ML) presents new opportunities in healthcare, especially in medical spa therapies. Once considered palliative, these therapies conducted using mineral/thermal water are now recognized as a targeted and specific therapeutic modality. The peculiarity of these treatments lies in their simplicity of administration, which allows for prolonged treatments, often lasting weeks, with progressive and controlled therapeutic effects. Thanks to new technologies, it will be possible to continuously monitor the patient, both on-site and remotely, increasing the effectiveness of the treatment. In this context, wearable devices, such as smartwatches, facilitate non-invasive monitoring of vital signs by collecting precise data on several key parameters, such as heart rate or blood oxygenation level, and providing a perspective of detailed treatment progress. The constant acquisition of data thanks to the IoT, combined with the advanced analytics of ML technologies, allows for data collection and precise analysis, allowing real-time monitoring and personalized treatment adaptation. This article introduces an IoT-based framework integrated with ML techniques to monitor spa treatments, providing tailored customer management and more effective results. A preliminary experimentation phase was designed and implemented to evaluate the system’s performance through evaluation questionnaires. Encouraging preliminary results have shown that the innovative approach can enhance and highlight the therapeutic value of spa therapies and their significant contribution to personalized healthcare.

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Deep learning applications in the Internet of Things: a review, tools, and future directions

Raoufi,

Hemmati,

Rahmani

2024

Evol. Intel.

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Water contamination analysis in IoT enabled aquaculture using deep learning based AODEGRU

Cited by 8 publications

References 21 publications

Implementation of IoT Sensors in Fog Collector Systems and Flowmeters for the Control of Eater Collection and Distribution

Implementation of IoT Sensors in Fog Collector Systems and Flowmeters for the Control of Eater Collection and Distribution

Integrating the Internet of Things (IoT) in SPA Medicine: Innovations and Challenges in Digital Wellness

Deep learning applications in the Internet of Things: a review, tools, and future directions

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