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

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

“…These sensors provide real-time data about the crops’ environment, which is then sent to a central hub or cloud platform. Advanced algorithms and machine learning processes this data to determine the ideal irrigation and fertilization needs. …”
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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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Brewing perfection: real-time monitoring of arabic coffee using iot and machine learning by Abuzaraida, Mustafa Ali, A. L. gaud, Sarah, Abrahim Hneish, Hamza, Attarbashi, Zainab

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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

“…Our disease detection system utilizes real-time sensors, machine learning algorithms, and IoT technology to swiftly identify pathogen indicators. …”
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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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Intelligent decision support systems: transforming smart cities management by Ahmed, Zeinab E., Hassan Abdalla Hashim, Aisha, Mokhtar, Rania A., Saeed, Mamoon M.

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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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Home intruder detection system using machine learning and IoT by Sahlan, Fadhluddin, Feizal, Faeez Zimam, Mansor, Hafizah

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Real-time and predictive analytics of air quality with IoT system: A review by Nurmadiha, Osman, Mohd Faizal, Jamlos, Fatimah, Dzaharudin, Aidil Redza, Khan, You, Kok Yeow, Khairil Anuar, Khairi

“…(iv) Data analytics for Air Pollution Index (API) prediction along with IoT, with various communication protocols can as-sist in the development of real-time, and continuous high precision environmen-tal monitoring systems. v) Machine Learning (ML) Regression algorithm is suit-able for prediction and classification of concentration gas pollutant, while ANN and SVM algorithm is used for forecasting.…”
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Development of IoT-based automated dynamic emergency response system against fire incidents in academic building by Al-Hady, Syed Mohammed Zakaria, Islam, Md Rafiqul, Rashid, Muhammad Mahbubur

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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

“…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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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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