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

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

“…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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Smart agriculture: precision farming through sensor-based crop monitoring and control system by Mohamad Hakhrani, Asyful Azhim, Abdul Hamid, Syamsul Bahrin

“…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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Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment by Ahmed Hamza, Manar, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, S. Alotaibi, Saud, Mahgoub, Hany, S. Mehanna, Amal, Motwakel, Abdelwahed

“…Here, the novelty of the work is the application of MVO algorithm in fine-turning the hyperparameters involved in BiGRU model. …”
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Trust-aware authentication and authorization for IoT: a federated machine learning approach by Ahmed, Kazi Istiaque, Tahir, Mohammad, Lau, Sian Lun, Habaebi, Mohamed Hadi, Ahad, Abdul, Mughees, Amna

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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

“…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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Software agent as an effective tool for managing the Internet of thing data complexity by Mustafa, M.B., Yusoof, M.A.M.

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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Adaptive security architecture for protecting RESTful web services in enterprise computing environment by Beer, M.I., Hassan, M.F.

“…A novel security component named â��intelligent security engineâ�� is introduced which learns the possible occurrences of security threats on SOA using artificial neural networks learning algorithms, then it predicts the potential attacks on SOA based on obtained results by the developed theoretical security model, and the written algorithms as part of security solution prevent the SOA attacks. …”
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Securing IoT networks using machine learning-resistant physical unclonable functions (PUFs) on edge devices by Sheikh, Abdul Manan, Islam, Md. Rafiqul, Habaebi, Mohamed Hadi, Zabidi, Suriza Ahmad, Najeeb, Athaur Rahman, Baloch, Mazhar

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Smart attendance system with Iot based face recognition using deep learning approach by Seah, You

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Selective of IoT applications for water quality monitoring in Malaysia by Zainuddin, Ahmad Anwar, Amir Hussin, Amir 'Aatieff, Annas, Ammar Haziq, Bharudin, Mohamad Syafiq Asyraf, Abdul Rajat @ Abdul Razak, Alin Farhain, Mahazir, Muhammad Nur Badri, Ahmad Puzi, Asmarani, Handayani, Dini Oktarina Dwi, Abdul Raziff, Abdul Rafiez

“…Overall, this paper proposes a comprehensive overview of IoT-based applications for water quality monitoring in Malaysia’s aquaculture with the advancements in IoT technology and its potential impact on improving water quality management practices.…”
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Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

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Design and implementation of a deep learning based hand gesture recognition system for Rehabilitation Internet-Of-Things (RIOT) environments using MediaPipe by Mohd Dhuzuki, Nurul Hanis, Zainuddin, Ahmad Anwar, Kamarul Zaman, Nur Anis Sofea, Ahmad Razmi, Alin Nur Maisarah, Kaitane, Wonderful Shammah, Ahmad Puzi, Asmarani, Johar, Mohd Naqiuddin, Yazid, Maslina, Mohd Nordin, Nor Azlin, Sidek, Shahrul Naim, Mohd Zaki, Hasan Firdaus

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Botnet Detection in IoT Devices Using Random Forest Classifier with Independent Component Analysis by Akash, Nazmus Sakib, Rouf, Shakir, Jahan, Sigma, Chowdhury, Amlan, Uddin, Jia

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Detection of DDoS attacks in IoT networks using machine learning algorithms by Abdulrahman Alwan, Alwan Ahmed, Shah, Asadullah, Abdulrahman Alwan, Alwan Abdullah, Laghari, Shams Ul Arfeen

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A Review on Attack Graph Analysis for IoT Vulnerability Assessment: Challenges, Open Issues, and Future Directions by Almazrouei O.S.M.B.H., Magalingam P., Hasan M.K., Shanmugam M.

“…In this review, core modeling techniques for IoT vulnerability assessment are highlighted, such as Markov Decision Processes (MDP), Feature Pyramid Networks (FPN), K-means clustering, and logistic regression models, along with other techniques involving genetic algorithms like fast-forward (FF), contingent fast-forwards (CFF), advanced reinforcement-learning algorithms, and HARMs models. …”

Water quality monitoring using machine learning and IoT: a review by Hasan, Tahsin Fuad, Kabbashi, Nassereldeen Ahmed, Saleh, Tanveer, Alam, Md. Zahangir, Abd Wahab, Mohd Firdaus, Nour, Abdurahman Hamid

“…The paper explores various ML algorithms, including supervised and unsupervised learning and deep learning, along with their applications, and discusses the use of IoT sensors for real-time monitoring of water quality parameters such as pH, dissolved oxygen, temperature, and turbidity.…”
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Intrusion detection system for the internet of things based on blockchain and multi-agent systems by Liang, Chao, Shanmugam, Bharanidharan, Azam, Sami, Karim, Asif, Islam, Ashraful, Zamani, Mazdak, Kavianpour, Sanaz, Idris, Norbik Bashah

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Internet of Things (IoT) intrusion detection by Machine Learning (ML): a review by Dehkordi, Iman Farhadian, Manochehri, Kooroush, Aghazarian, Vahe

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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.

“…As the chosen model to be implemented in this analysis, the Q-learning algorithm proposal offers a possible solution for addressing evolving IoT environments and configurations. …”
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