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Device Intelligence, computing and Communication Technologies, (DICCT), International Conference on

作者： Vimal Kumar Stephen Sanjiv Sharma Zaina Rashid Salim Al-Jufaili Senthil Jayapal College of Computing and Information Sciences University of Technology And Applied Sciences Ibra Oman

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

In this study, machine-learning technique is used to collect environmental data in real time and measures other aspects like soil moisture, temperature, water level, humidity. Water use efficiency has recently increased because to new agricultural techniques, sophisticated sensors as Micro Controller, and Wireless Sensor Network (WSN). Irrigation Fault Detection method based on XGBoost (IFD-XGBoost) Algorithm used as proposed method as robust to missing values imputing them naturally during tree splitting. The Suggested method is optimized for speed, using parallel and distributed computing to make predictions faster compare to other Regression Algorithm and avoid over fitting. Using Min-Max Normalization, features with different sizes and units can affect the efficacy of several machine learning algorithms. By warping the statistical relationship between features, removal of noisy data and error detection can reduce the machine learning models' efficiency. Lasso Regression is a linear model that combines regularization and feature selection. Additionally, less data will be kept in the centralized cloud as a result. Using the IFD-XGBoost Algorithm's ability to handle missing data, learn from past errors, and adjust parameters, our proposed approach would be the best model to implement. It outperform from other algorithm in Predictive accuracy, making it reliable for calculating water needs and forecasting weather. Investigating the implementation of several machine learning models that can offer the best real-world irrigation decision management is the main goal of this article. The comparative analysis to evaluate the IFD-XGBoost method yielded a minimum RMSE of 0.3524, MAE of 0.1832, MAPE of 4.24 with the highest accuracy of 99.2%, precision of 96.2% and AUC-ROC of 95%, indicates when combined, these metrics provide insightful data about each model's ability to anticipate future developments in irrigation systems.

关键词： Temperature sensors Temperature measurement Irrigation Wireless sensor networks Machine learning algorithms Soil moisture Machine learning Humidity Prediction algorithms Data models

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Enhancing Medical Image Segmentation Through Knowledge Transfer

Enhancing Medical Image Segmentation Through Knowledge Trans...

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2024 International Conference on Optimization computing and Wireless Communication, ICOCWC 2024

作者： Raghavendra, R. Abrol, Monika Tripathi, Ramesh Chandra Department of Computer Science and Information Technology Bangalore India Sanskriti University Department of Applied Science Uttar Pradesh Mathura India Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India

ISBN: (纸本)9798350383348

Clinical image segmentation is a challenge that identifies a selected organ or anatomical structure in a given scientific image which can be of radiographic or other modality. Expertise switch is an essential side of clinical image segmentation as medical practitioners may additionally possess information about the patient's anatomy or physiology that could contribute to the segmentation process. Understanding transfer to a deep mastering version, such as a convolution neural community, can allow the model to perform correct segmentation compared to other tactics. In this paper, we explore strategies and packages of expertise switches for scientific photograph segmentation, discuss its blessings and challenges, and eventually advise a singular method based totally on understanding fusion. We increase a two-step framework to fuse photo-degree features and segmentation labels with medical data before segmentation. The proposed approach demonstrates advanced segmentation accuracy in assessing the present strategies... © 2024 IEEE.

关键词： comparison contribute important information segmentation

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Automating Weed Detection Through Hyper Spectral Image Analysis

Automating Weed Detection Through Hyper Spectral Image Analy...

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2024 International Conference on Optimization computing and Wireless Communication, ICOCWC 2024

作者： Bharadwaj, Shambhu Prabhu, A. Solanki, Vipin Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India Sanskriti University Department of Applied Science Uttar Pradesh Mathura India

ISBN: (纸本)9798350383348

Weed detection is an essential assignment in agricultural settings. Negative environmental results, crop yield loss, and mechanical weeding hard work prices related to weed management have necessitated the improvement of automation solutions to discover and treat weeds. Hyperspectral imaging (HSI) is a promising method that can produce abundant statistics about the spectral residences of flowers. This generation has been used in weed detection packages to classify weeds from crops, and these days deep mastering has been used to provide high accuracy prices in this discipline. In this abstract, we explore the utility of HSI for weed detection. We define current demanding situations that require further research earlier than automatic weed detection structures using HSI grow to be widely available. In particular, the presently available algorithms lack robustness and scalability, and further improvements in gadget-gaining knowledge of algorithms and techniques are wished to conquer those constraints, in addition to advancing the computational capabilities of these structures. Moreover, we discuss the potential of HSI as a weed detection answer in various contexts, including agroforestry and precision farming. In conclusion, we advise that the software of HSI for automatic weed detection has the massive capability to reduce labor fees related to weed manipulation, improve farming performance, and in the end, boom crop yields. Weed detection is a first-rate challenge inside the agricultural enterprise, as guide weed control is costly, time-consuming, and the correct identity of weeds is rigid. Hyper Spectral photo evaluation (HSIA) offers an alternative to guide weed detection, considering the rapid and effective mapping of weed-infested land without the need for guide labor. HSIA may be used to routinely detect the spectral signature of weed species, allowing for correct identity and brief remedy. This method uses hyperspectral scanners to gather spectral records, whic

关键词： accuracy crops harm measures promising

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The Impact of Control Plane Attacks in Software Defined Networks Environments 1

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International Conference on Advances in Communication technology and Computer Engineering, ICACTCE 2023

作者： Kumar, M. Anand Muthusamy, Senthilkumar Ashik, Mohamed Karthikeyan, R. Sundaravadivazhagan, B. School of Information Science Presidency University Bangalore India Department of Engineering University of Technology and Applied Sciences-Al Mussanah Muladdah Oman College of Computing and Information Sciences University of Technology and Applied Sciences - Salalah Salalah Oman Vardhaman College of Engineering Telangana Hyderabad India Department of Information Technology University of Technology and Applied Sciences-Al Mussanah Muladdah Oman

ISBN: (数字)9783031371646

ISBN: (纸本)9783031371639

The Internet of Everything (IoE) and 5G are two initiatives that have embraced Software-Defined Networking (SDN), a model that is intensely changing communications systems. Even though SDN has been around for more than 20 years, it is still improving, and the technology industry is placing more and more demands on SDN networks to make them more creative, adaptable, and reliable. Unfortunately, there is an enormous security flaw in the SDN architecture’s components that might be used by intruders to execute critical attacks which disrupt the components and their operations. SDN networks have several benefits for managing infrastructure and predicting development. The supply of services was made easier with centralized control, which offers a comprehensive and in-depth perspective of the network. Due to the enormous advantages, SDN is deployed in several applications instead of traditional network architecture. As far as large-scale applications are concerned, there is a huge demand to implement strong security strategies in information allotment and resources across different platforms. Even though several recent research works are recently concentrated on finding the limitations of SDN architecture components, types of security attacks, and possible solutions to overcome the limitations. SDN has encountered several security issues like man-in-the-middle attacks, host hijacking ARP poisoning, and saturation attacks. This research work mainly focuses on control plane attacks that affect the total operations of network devices, including switches and the SDN controller. It was also identified that these attacks have a huge impact on the network components of SDN environments. Experimental results provide a detailed analysis of control plane attacks and their impact on the SDN networks. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Controllers

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Fog computing in Optical Access Networks: An Energy-efficient and Deadline-aware Task Scheduling Mechanism 13

Fog Computing in Optical Access Networks: An Energy-efficien...

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13th International Conference on Information technology in Asia, CITA 2023

作者： Ahmad, Fathiyah Haji Shah Newaz, S.H. Sankar, D.S. Ramlie, Rudy Nafi, Nazmus Shaker School of Computing and Informatics GadongBE1410 Brunei Kaist Institute for Information Technology Convergence Daejeon34141 Korea Republic of School of Applied Sciences and Mathematics GadongBE1410 Brunei Boeing Defence Australia AdelaideSA5111 Australia

ISBN: (纸本)9798350326208

Fog computing is paving the way for catering latency stringent applications (e.g., augmented reality and virtual reality) at the customer premises. Fog computing nodes are located between the end user devices and remote cloud. They are lightweight and small-scale storage and processing system deployed closer to the data source, allowing faster processing as well as providing privacy and security of the data. We have been witnessing a growing number of solutions that integrate Passive Optical Network (PON) with the fog computing. Along this research line, there are some solutions considering fog computing nodes are co-located with the Optical Line Terminal (OLT), the central intelligence of a PON system, and Optical Network Unit (ONU), a customer premises equipment. There are some solutions, on the other hand, that propose to embed computing and storage functionality within PON equipment itself. In this paper, we particularly focus on the later approach. Here, we propose an energy conserving solution for a PON system with fog computing enabled ONUs, i.e., the ONUs are equipped with additional computing and Storage Units (CSUs). Our solution aims at minimizing energy consumption of a PON system by keeping only the required number of CSUs active and allowing the ONUs to move into sleep mode (whenever possible) by taking into account task arrival rate and task completion deadline. © 2023 IEEE.

关键词： Energy efficiency

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Implementing an Intelligent Irrigation System in Oman Using Machine Learning Technique 3

Implementing an Intelligent Irrigation System in Oman Using ...

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3rd IEEE International Conference on Device Intelligence, computing and Communication Technologies, DICCT 2025

作者： Stephen, Vimal Kumar Sharma, Sanjiv Al-Jufaili, Zaina Rashid Salim Jayapal, Senthil University of Technology And Applied Sciences College of Computing and Information Sciences Ibra Oman

ISBN: (纸本)9798331543358

关键词： Distributed cloud

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A Case of Study on the Role of Internet of Things technology in Enhancing the Efficiency of Converting Agricultural Waste into Organic Fertilizer

A Case of Study on the Role of Internet of Things Technology...

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computing and Data Analytics (ICCDA), International Conference on

作者： Sundos Ali Al-Fulaiti Aya Salim Hamed Al-Hakmani Amira Suliaman Al-Breiki Shahla Anwar Al-Khanbashi AlHanouf Ibrahim Al-alawi Imran Qureshi Collage of computing and information sciences University of Technology and Applied Sciences Mussanah

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

Agriculture has grown to be an important field for the Internet of Things, which is marked by rapid and wide application [20]. In this work, results on methodology to evaluate temperature, humidity, pH, electrical conductivity, as well as the concentrations of potassium (K), phosphorus (P), and nitrogen (N) in bio-organic fertiliser with the use of a sensor system. [20]. The MCU ESP32 with incorporated Wi-Fi facilitates the transmission of data to the cloud platform known as ThingSpeak [20]. This work engages in cooperative effort with local farmers, community enterprises, and Raja Mangala University of technology Than Aburi (RMUTT) in the issue of agricultural waste management and its ecological implications by mitigating soil nitrate concentrations to generate bio-organic fertilisers from agricultural byproducts [20]. This project integrates an IoT sensor system with a view to improving the quality and quantity of the product, utilising advanced sensors for continuous monitoring of critical biological and physical parameters [20].

关键词： Temperature sensors Waste management Cloud computing Temperature Humidity Soil Sensor systems Internet of Things Wireless fidelity Fertilizers

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Deriving a Power-Law Model for Aggregating Data with Head Based Clustering

Deriving a Power-Law Model for Aggregating Data with Head Ba...

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2024 International Conference on Optimization computing and Wireless Communication, ICOCWC 2024

作者： Solanki, Vipin Rastogi, Ajay Raghavendra, R. Sanskriti University Department of Applied Science Uttar Pradesh Mathura India Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

Head-based Totally Clustering is a technique of grouping facts and factors with similar traits using a rooted tree structure. The research paper Deriving an electricity-law version for Aggregating facts with Head primarily based Clustering outlines an energy-law model for creating clusters of facts points in a head-based totally hierarchy that may be used to efficiently mixture groups of related information. The authors used a topological distance technique to generate the clusters and implemented the method on an objective global dataset of web pages. The proposed model is designed to lessen the complexity of incorporating records from a pre-described tree shape with electricity regulation. The effects confirmed a widespread discount in computational time and aid utilization. Additionally, the approach could increase aggregated facts' accuracy by incorporating numerous information points in a head-based hierarchy. The look gives a similar understanding of the potential application of a strength-regulation model for aggregating statistics with head-primarily based Clustering. © 2024 IEEE.

关键词： aggregating computational Head based incorporating technique

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Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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Computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah Song Jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

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The Terms Estimation of S Robotics using MTRS as well as FEM 4

The Terms Estimation of S Robotics using MTRS as well as FEM

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4th IEEE International Conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Gopal, R. Mudhafar, Mustafa Hashem, Amjad Ramalingam, Venkadeshan Bordoloi, Dibyahash Khan, Muhammad Numan Ali Adnan, Myasar Mundher Abdulhussain, Zahraa N. University of Buraimi Information and Communication Engineering College of Engineering Oman University of Kerbala Faculty of Medical Applied Sciences Department of Medical Physics Karbala56001 Iraq Al-kunooze University College Computer Engineer Department Basra Iraq University of Technology and Applied Sciences Network Computing College of Computing and Information Sciences Shinas Oman Dept of Cse Graphic Era Hill University Uttarakhand Dehradun India Graphic Era Deemed to Be University Uttarakhand Dehradun India University of Technology and Applied Sciences Network Computing College of Computing and Information Sciences Shinas Oman The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq National University of Science and Technology College of Technical Engineering Dhi Qar64001 Iraq

ISBN: (纸本)9798350360165

This look at addresses the critical project of reaching dependable and precise proprioception in soft robots, it really is essential for his or her effective deployment in complicated environments. By integrating multi-tap resistive sensors in the robot's form, our technique lets in for the distinct sensing of nearby deformations at various factors throughout the robotics' frame, moving beyond traditional techniques that anticipate steady curvature. We beautify the decision of these deformations and couple the sensory facts with a strong finite detail technique (FEM) model. This included framework allows the correct estimation of the smooth robot's form and the significance of outside forces applied to it, attaining a mean relative inaccuracy of about 4%. Additionally, our technique proves its software program in tender manipulation structures, in which it achieves thirteen% relative mistakes in external force estimation inside diverse zero to five N. The approach gives a promising direction for enhancing robotic interactions in sensitive and dynamic responsibilities, providing massive enhancements in robotic proprioception without reliance on outdoor monitoring generation. © 2024 IEEE.

关键词： Microrobots

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