Search Results - (( iot applications learning algorithm ) OR ( based application based algorithm ))*

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    IOT-based fertigation system / Mohamad Amir Furqan Darus by Darus, Mohamad Amir Furqan

    Published 2024
    “…The Fertigation, the precise application of water and fertilizers in agriculture, has evolved with the integration of Internet of Things (IoT) technology. …”
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    Student Project
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    Applications of deep learning algorithms for supervisory control and data acquisition intrusion detection system by Balla, Asaad, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Mubarak, Sinil

    Published 2022
    “…For each algorithm, prior works have been identified, examined, and described based on their conceptual similarities. …”
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    Article
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    Determination of suitable resource discovery tool and methodology for high-volume internet of things (IoT) by Jamal, A.A., Bakar, M.T.A.

    Published 2021
    “…Q-learning is one of the successful techniques available for the exploration of IoT nodes, but context based problems have already been established and simplified as issues of dedicated server management, IoT object data acquisition issues, and unique application requirements. …”
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    Conference or Workshop Item
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    Smart agriculture: precision farming through sensor-based crop monitoring and control system by Mohamad Hakhrani, Asyful Azhim, Abdul Hamid, Syamsul Bahrin

    Published 2024
    “…Notably, prevalent smart agriculture systems predominantly emphasize either IoT components for data monitoring and control or machine learning components for data analysis. …”
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    Article
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    A comprehensive survey of deep reinforcement learning in UAV-assisted IoT data collection by Ahmed Amodu, Oluwatosin, Althumali, Huda, Mohd Hanapi, Zurina, Jarray, Chedia, Raja Mahmood, Raja Azlina, Adam, Mohammed Sani, Bukar, Umar Ali, Abdullah, Nor Fadzilah, Luong, Nguyen Cong

    Published 2025
    “…Unmanned Aerial Vehicles (UAVs) play a critical role in data collection for a wide range of Internet of Things (IoT) applications across remote, urban, and marine environments. …”
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    Article
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    A question-centric review on DRL-based optimization for UAV-assisted MEC sensor and IoT applications, challenges, and future directions by Ahmed Amodu, Oluwatosin, Raja Mahmood, Raja Azlina, Althumali, Huda, Jarray, Chedia, Adnan, Mohd Hirzi, Bukar, Umar Ali, Abdullah, Nor Fadzilah, Nordin, Rosdiadee, Ahmad Zukarnain, Zuriati

    Published 2025
    “…This paper aims to answer twelve important research questions relating to the research on DRL for Mobile Edge Computing (MEC)-based UAV-assisted sensor and IoT applications from 47 systematically selected articles. …”
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    Article
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    Deep reinforcement learning online offloading for SWIPT multiple access edge computing network by Teckchai, Tiong, Ismail Saad, Tze, Kenneth Kin Teo, Herwansyah Lago

    Published 2021
    “…More computation-intensive and low latency applications are emerging recently, and they are constrained by the computing power and battery life of internet of things (IoT). …”
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    Proceedings
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    Fog-cloud scheduling simulator for reinforcement learning algorithms by Al-Hashimi, Mustafa Ahmed Adnan, Rahiman, Amir Rizaan, Muhammed, Abdullah, Hamid, Nor Asilah Wati

    Published 2023
    “…Fog computing is a popular choice for Internet of Things (IoT) applications, such as electricity, health, transportation, smart cities, security, and more. …”
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    Article
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    IoT alarm system: detecting & preventing microsleep events by Azhar, Ahmad Mirza, Awang, Norkhushaini

    Published 2024
    “…Node-RED, a powerful visual programming tool used for developing IoT applications, facilitated the creation of an intuitive and informative dashboard.…”
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    Book Section
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    Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks by Rayner Alfred, Joe Henry Obit, Christie Chin Pei Yee, Haviluddin Haviluddin, Yuto Lim

    Published 2021
    “…We describe the data captured and elaborate role of machine learning algorithms in paddy rice smart agriculture, by analyzing the applications of machine learning in various scenarios, smart irrigation for paddy rice, predicting paddy rice yield estimation, monitoring paddy rice growth, monitoring paddy rice disease, assessing quality of paddy rice and paddy rice sample classification. …”
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    Article
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