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IoT-based Ubiquitous Healthcare System with Intelligent Approach to an Epidemic

Recent Patents on engineering 2024年第9期18卷 34-47页

作者： Mohapatra, Subasis Yesubabu, Mannava Sahoo, Amlan Mohanty, Subhadarshini Mohanty, Sachi Nandan Department of Computer Science & Engineering Odisha University of Technology and Research Odisha Bhubaneswar India Hyderabad India VIT-AP University Andhra Pradesh India

Background: The recent pandemic has shown its different shades across various solicitations, especially in the healthcare sector. It has a great impact on transforming the traditional healthcare architecture, which is based on the physical approaching model, into the modern or remote healthcare system. The remote healthcare approach is quite achievable now by utilizing multiple modern technological paradigms like AI, Cloud Computing, Feature Learning, the Internet of Things, etc. Accordingly, the pharmaceutical section is the most fascinating province to be inspected by medical experts in restoring the evolutionary healthcare approaches. COVID-19 has created chaos in the society for which many unexpected deaths occur due to delays in medication and the improper prognosis at an irreverent plan. As medical management applications have be-come ubiquitous in nature and technology-oriented, patient monitoring systems are getting more popular among medical actors. Method: The Internet of Things (IoT) has achieved the solution criteria for providing such a huge service across the globe at any time and in any place. A quite feasible and approachable framework has evolved through this work regarding hardware development and predictive patent analysis. The desired model illustrates various approaches to the development of a wearable sensor medium that will be directly attached to the body of the patients. These sensor mediums are mostly accountable for observing body parameters like blood pressure, heart rate, temperature, etc., and transmit these data to the cloud storage via various intermediate steps. The storage medium in the cloud will be storing the sensor-acquired data in a time-to-time manner for a detailed analysis. Further, the stored data will be normalized and processed across various predictive models. Results and Conclusion: The model with the best accuracy will be treated as the resultant model among the numerous predictive models deployed in the cloud. During

关键词： Predictive analytics

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Multiple Redundant Weighted Clustered Scheme with Dynamic Weights Adjustment for Damaged S-UAV 29

Multiple Redundant Weighted Clustered Scheme with Dynamic We...

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29th IEEE International Workshop on computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2024

作者： Khayat, Grace Mavromoustakis, Constandinos X Batalla, Jordi Mongay Pitsillides, Andreas Department of Computer Science Nicosia Cyprus Warsaw University of Technology Warsaw Poland University of Cyprus Department of Computer Science Cyprus Department of Electrical & Electronic Engineering Science South Africa

ISBN: (纸本)9798350377644

Swarm of UAVs (S-UAVs) refers to an assembly of unmanned aerial vehicles (UAVs) working together to accomplish prearranged missions. In emergency scenarios, such as a fire, any UAV is susceptible to damage. Among the routing algorithms that S-UAVs utilize the most frequently is clustering, where UAVs are divided into clusters. Each cluster consists of a cluster head (CH) and cluster members (CM). The selection of the CH is a topic of continuous research because of its crucial significance in inter-cluster communication. We propose a clustered weighted method with dynamic weight modification and redundancy to ensure end-to-end communication despite non-functional CH. Interspace, speed, and performance indicators are combined into a weighted metric that is used to select the CH, redundant CHs, and CMs. The suggested technique optimizes UAV role selection by dynamically and autonomously adjusting the weights. Based on the results of the executed simulation, this is a promising strategy that minimizes data loss in an emergency situation and minimizes delay. © 2024 IEEE.

关键词： Vehicle routing

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Predicting Disaster Tweets using Enhanced BERT Model 7

Predicting Disaster Tweets using Enhanced BERT Model

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7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Duraisamy, Premkumar Duraisamy, M. Periyanayaki, M. Natarajan, Yuvaraj KPR Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Government Arts and Science College Department of Computer Science Tirupattur India

ISBN: (纸本)9798350397253

Twitter has become an essential means of communication in emergency situations. The widespread use of smart phones, anyone can immediately report any incident they witness. As a result, more agencies are interested in programmatically monitoring Twitter. Social media sites such as Twitter provide a common forum for sharing and exchanging personal experiences with others. Most of the people share personal experiences, neighborhood problems also the activities on social websites to let unwanted peoples to know. Many rescue organizations constantly monitor this kind of data to detect disasters and reduce the likelihood of casualties. However, humans cannot manually comb through vast amounts of data to uncover threats in real-time. To achieve this, many studies have proposed representing words in a form that computers can understand and applying machine learning techniques to the word representations to determine the sentiment of the text. Previous search techniques provide single embeddings or representations of words from a given document. However, the new Advanced Contextual Embedding is Bidirectional Encoder Representations from Transformers (BERT) method creates different vectors for the same expression with different settings. Although there are no specific studies on how BERT embeddings can help analyze catastrophe-type tweets, these representations have been successfully used in various Natural Language Processing (NLP) tasks. © 2023 IEEE.

关键词： Embeddings

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Prediction of Diseases in Potato Plant using Pre-trained and Traditional Machine Learning Models 4

Prediction of Diseases in Potato Plant using Pre-trained and...

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4th International Conference for Emerging technology, INCET 2023

作者： Sahu, Swati Laxmi Chintala Bhargavi, Renta Vellore Institute of Technology School of Computer Science and Engineering Chennai India Vellore Institute of Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350335750

Potato, among the most vegetables is commercially significant and well-known vegetable which is known for its high nutritional content and delicious flavor. India is one of the world's leading producers of potato. Unfortunately, plant diseases in potato have been one of the causes of decreased production. So, it is necessary to detect them. Collecting images of plants diseases is a big challenge as it is a very time-consuming process. Often, we do not have sufficient data to train our deep learning models, so data augmentation techniques are used for increasing the dataset which lead to poor generalization. This study focuses on detecting whether the plant is healthy or diseased. In this proposed method, limited dataset is used for potato plant disease classification without using any data augmentation techniques. Popular pre-trained models - VGG16, InceptionResNetV2, ResNet50V2 are used for feature extraction and traditional machine learning algorithms - XGBoost, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest are used as classifiers. From the study, it is observed that the combination of VGG16 model as a feature extractor and SVM as a classifier achieved the highest accuracy of 93% compared to rest of the combination of models and algorithms. The method proposed in this study can be used for potato plant disease detection with limited dataset. © 2023 IEEE.

关键词： Vegetables

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Farmer's Crop Welfare System 15

Farmer's Crop Welfare System

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Dhamodhar, G. Krishna, B. Vamsi Reddy, D. Sampath Reddy, A. Sameer Amutha, S. Ganesan, Kothai Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamilnadu Virudhnagar India Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore Dist. Tamil Nadu India

ISBN: (纸本)9798331300579

The "Farmer's Crop Welfare System" is a technology that uses advanced data analytics and artificial intelligence to improve crop management and yield. It combines crop prediction, disease detection, and fertilizer recommendation. Crop prediction uses historical and real- time data, while disease detection uses image recognition and deep learning to identify early signs of diseases, promoting sustainable farming practices. © Grenze Scientific Society, 2024.

关键词： Livestock

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VANET Handoff from IEEE 80.11p to Cellular Network Based on Discharging with Handover Pronouncement Based on Software Defined Network (DHP-SDN) 22nd

VANET Handoff from IEEE 80.11p to Cellular Network Based on ...

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22nd International Conference on Hybrid Intelligent Systems, HIS 2022 and the 18th International Conference on Information Assurance and Security, IAS 2022

作者： Sarvavnan, M. Narayanan, R. Lakshmi Kavitha, K. Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Networking and Communications SRM Institute of Science and Technology Chennai India Department of Computer Science and Engineering Kongu Engineering College Erode India

ISBN: (纸本)9783031274084

In Vehicular Adhoc Network (VANET) is an emerging domain with high dynamic mobility and disrupted network in Discharging with Handover Pronouncement based on Software Defined Network (DHP-SDN) with advance predictive management tool described in this work for discharging of vehicle-to-infrastructure communication with Software Defined Network (SDN) architecture. Various parameters were addressed in research articles like maintaining connectivity, identifying appropriate intermediate node for carrying signal and transferring of data but in the proposed model SDN monitors the discharging signal based on the speediness, terrestrial location, nearby vehicle RSU from the vehicle which has cellular and IEEE 802.11p network boundary. SDN regulator computes when the due time is to settle on a choice, chooses whether it is appropriate or not have the vehicle to handoff from cell organization to the ahead IEEE 802.11p organization. The simulation results that using DHP-SDN method maintains the networking quality by reducing the load and traffic congestion. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Vehicles

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An Improved Deadlock Recovery Policy of Flexible Manufacturing Systems Based on Resource Flow Graphs

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IEEE Access 2024年 12卷 65202-65212页

作者： Tseng, Ching-Yun Chen, Ju-Chin Pan, Yen-Liang National Kaohsiung University of Science and Technology Department of Electronic Engineering Kaohsiung807618 Taiwan R.O.C. Air Force Academy Mathematics and Physics Division General Education Center Gangshan Kaohsiung820009 Taiwan National Kaohsiung University of Science and Technology Department of Computer Science and Information Engineering Kaohsiung807618 Taiwan Chaoyang University of Technology Department of Aeronautical Engineering Taichung413310 Taiwan

The system deadlock problem of the flexible manufacturing system (FMS) needs to be solved urgently. Deadlocks may occur when resources are repeatedly requested by multiple working processes, where such competition causes a lack of resources, and the system cannot get into subsequent processes smoothly. In this paper, we build FMS by using a particular class of Petri Net (PN) model called a system of simple sequential processes with resources (S3PR) net, which features a high utilization rate of resources. When parts of resources are held by related processes and these processes wait for others to release resources to move on, a circular waiting situation occurs. Circular waiting is one of the conditions for system deadlocks occurring, where the system under this situation has a high probability of causing system deadlocks. The resources being held have to be released to break the waiting states. This paper develops a novel control transition-based deadlock recovery policy by combining graph theory and reachability graph analysis technique. The proposed approach firstly builds a subnet of the PN model called resource flow graph (RFG) and finds out all its hold and request circuits (HRCs), which may lead to a circular waiting situation. In addition, we design a new algorithm to obtain the minimal set of control transitions further. We introduce three PN models of FMS to demonstrate the proposed method. Through experimental results and comparison between related works, it is known that the proposed deadlock recovery uses fewer controllers and has the same performance. © 2013 IEEE.

关键词： Frequency modulation

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Smart and Advanced E-learning Methodology with IoT Device Integration 6

Smart and Advanced E-learning Methodology with IoT Device In...

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6th International Conference of Women in Data science at Prince Sultan University, WiDS-PSU 2023

作者： Shahbaz, Muhammad Altaf, Ayesha Iqbal, Faiza Shoaib, Shazia University of Engineering and Technology Department of Computer Science Lahore Pakistan

ISBN: (纸本)9781665477239

IoT has spawned numerous revolutionary innovations in the modern era. Now we have been introduced to the concept of self-operating, high-speed, high-altitude objects that operate solely on information technology. With the development of technology, IoT is being implemented not only in agriculture industries, healthcare sectors, and artificial intelligence, but also in education sectors. As the world is being completely digitized, the education system is also being digitized. Today, virtually all colleges and universities utilize a Learning Management System (LMS). These systems not only aid administrators in keeping track of the records of teachers, students, and attendance, but also assist students in preparing the subject-related materials provided by the teacher. Using sensors and actuators, we can produce even more intelligent classrooms. They collect student data by evaluating their facial expressions during class. The collected data can then be used to generate an alert to the relevant instructor regarding students' behaviors that are causing confusion during the lecture. The purpose of this paper is to propose a model that can observe student behavior in class using smart cameras and then upload that data to a learning management system (LMS) so that the instructor can make decisions about his teaching methodology. We have studied various techniques for implementing the proposed solution, and the results are approximately 40% more satisfactory than with the conventional learning mechanism. Finally, the paper identifies the security issues that may arise in online systems of this type. © 2023 IEEE.

关键词： Students

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Intrusion detection system using soft computing techniques in 5G communication systems

Intrusion detection system using soft computing techniques i...

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Dhanya, D. Shankari Kathir, I. Kuchipudi, Ramu Thamarai, I. Kumar, E. Rajesh Department of Computer Science and Engineering Mar Ephraem College of Engineering and Technology Tamil Nadu Kanyakumari India Department of Computer Science and Engineering RMK College of Engineering and Technology Tamil Nadu Thiruvallur India Department of Electrical and Electronics Engineering V.S.B. Engineering College Tamil Nadu Karur India Department of Information Technology Chaitanya Bharathi Institute of Technology Telangana Hyderabad India Department of Computer Science and Engineering Panimalar Engineering College Chennai City Campus Tamil Nadu Chennai India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India

ISBN: (纸本)9781032669663

The research deals with a thorough survey and starts by reviewing the fundamental knowledge of fuzzy systems over 5G communication. Future directions and scope can be used to demonstrate the desire for 5G communication networks to provide access to new applications and widespread connection. Therefore, the difficulties with the underlying technologies and hardware supporting them should allow for a greater level of service quality. The goal of this study is to create an intrusion detection system that employs fuzzy logic. This study proposes a model for a real-time intrusion detection expert system that seeks to find a variety of security breaches, from outsiders trying to break in to insiders breaking in and abusing the system. Analysis has also been done on the impact of changing the learning algorithms and membership function. The structure can manage very sizeable amount of data with the aid of data collection, storage, retrieval, and analysis, and it integrates the big data stream inside the network to enhance performance of the network. © 2024 The Author(s).

关键词： Intrusion detection

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DECODING TEXT AND IMAGE PLAGIARISM 2

DECODING TEXT AND IMAGE PLAGIARISM

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Valpadasu, Hema Tuniki, Sarika Manjusha, Bollimuntha Allam, Sangeetha Madgi, Manohar Tripathy, Hrudaya Kumar Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Cmr Engineering College India Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India School of Computer Science & Engineering Kle Technological University Bvb College Campus Vidyanagar India Kalinga Institute of Industrial Technology Deemed to Be University India

ISBN: (纸本)9798350370188

Copyright infringement location as a rule checks the text content by means of a significant number of the stages which are accessible for useful use dependably recognizing replicated text or close duplicates of text and these frameworks normally neglect to distinguish the pictures, and Documents counterfeiting since it is initially worked for text principally. We recommend a versatile, adaptable, extensible and vigorous technique for picture literary theft which is tried in plans gather from branch of design. In this strategy, we fundamentally think about the information (plans pictures) entered to the framework with informational indexes saved in the data set principally these plans are saved as element which is one of the man-made reasoning calculations and match by utilizing k-mean bunching and the likeness check is finished with limit utilized 40% which can be changed to an acknowledged levels when required. © 2024 IEEE.

关键词： Character recognition

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