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Internet of things technology, research, and challenges: a survey

Multimedia Tools and Applications 2025年第11期84卷 8455-8490页

作者： Vishwakarma, Amit Kumar Chaurasia, Soni Kumar, Kamal Singh, Yatindra Nath Chaurasia, Renu Management science and technology Khalifa University Abu Dhabi United Arab Emirates Computer science & Engineering SGT University Gurugram India Department of Information Technology IGDTUW New Delhi India Electrical Engineering IIT Kanpur Kanpur India Computer science & Engineering AIT Rooma Kanpur India

The world of digitization is growing exponentially;data optimization, security of a network, and energy efficiency are becoming more prominent. The Internet of Things (IoT) is the core technology of modern society. This paper is based on a survey of recent and past technologies used for IoT optimization models, such as IoT with Blockchain, IoT with WSN, IoT with ML, and IoT with big data analysis. Suppose anyone wants to start core research on IoT technologies, research opportunities, challenges, and solutions. In that case, this paper will help me understand all the basics, such as security, interoperability, standards, scalability, complexity, data management, and quality of service (QoS). This paper also discusses some recent technologies and the challenges in implementation. Finally, this paper discusses research possibilities in basic and applied IoT Domains. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Internet of things

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IoT-Based Secure Healthcare Framework Using Blockchain Technology with Nature-Inspired Optimization Algorithms 3rd

IoT-Based Secure Healthcare Framework Using Blockchain Techn...

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3rd International Conference on Emerging Electronics and Automation, E2A 2023

作者： Tripathy, Ramamani Satyanarayana Murty, P.T. Maram, Balajee Garg, Ankit Daniya, T. Santhosh Kumar, B. Computer Science and Engineering Chitkara University Himachal Pradesh India Shri Vishnu Engineering College for Women Bhimavaram India AIT-Department of Computer Science and Engineering Chandigarh University Mohali GharuanPunjab140055 India GMR Institute of Technology Rajam532127 India Telangana Ibrahimpatnam501506 India

ISBN: (纸本)9789819730896

This study introduces a novel method for resolving security and privacy issues in IoT-based healthcare systems by combining blockchain technology with optimization algorithms that are inspired by natural processes. Concerns concerning the danger of private patient data have been raised by the healthcare industry's explosive growth of IoT applications. We provide a comprehensive framework that makes use of the security capabilities built into blockchain to guarantee data integrity, authentication, and access control in order to reduce these risks. In order to improve system performance and resource allocation, we also develop optimization algorithms that are inspired by nature. The architecture of the framework includes smart contracts, communication protocols, and secure data flow to automate business processes within the healthcare ecosystem. Our method improves security while maximizing resource utilization by fusing blockchain's tamper-proof record with the adaptability of nature-inspired algorithms. The effectiveness of the suggested framework is assessed using simulations or real-world testing and benchmarked against current techniques. In the end, this research helps build a robust and effective healthcare framework that protects patient information, respects privacy, and improves the overall effectiveness of IoT-enabled healthcare systems. Additionally, the system's effectiveness and scalability can be improved by including optimization techniques that draw inspiration from nature. In order to create a safe and effective healthcare environment, this research paper offers a comprehensive framework that blends IoT, blockchain, and nature-inspired optimization algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data integrity

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Deep Transfer Learning for Multiclass Dermatology Classification: A Comprehensive Study 3rd

Deep Transfer Learning for Multiclass Dermatology Classifica...

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3rd International Conference on Emerging Electronics and Automation, E2A 2023

作者： Rao, S. V. Achuta Murty, P. T. Satyanarayana Maram, Balajee Garg, Ankit Daniya, T. Kumar, B. Santhosh Data Science Research Laboratories Sree Dattha Institute of Engineering and Science Sheriguda Telangana Hyderabad501 510 India Shri Vishnu Engineering College for Women Bhimavaram India AIT- Department of Computer Science and Engineering Chandigarh University Punjab Gharuan Mohali140055 India GMR Institute of Technology Rajam532127 India Telangana Ibrahimpatnam501506 India

ISBN: (纸本)9789819768011

Accurate and prompt diagnosis is crucial to the treatment of patients with dermatological diseases, which are a significant cause for worry in the medical community. By automating the diagnosing process, deep learning algorithms have recently demonstrated significant promise in the field of dermatology. In-depth research on the use of deep transfer learning for multiclass dermatological classification is presented in this publication. To train deep neural networks, the study makes use of a broad and comprehensive dermatology dataset that includes a variety of skin disorders. Modern pre-trained models are used with transfer learning techniques to make it easier to extract discriminative features. In order to improve classification performance, we delve into the complex process of model fine-tuning and investigate data augmentation techniques. Our research shows that multiclass dermatology classification accuracy has significantly improved, with models delivering reliable findings for a variety of skin disorders. We offer a thorough evaluation of the model's performance, emphasizing its ability to distinguish between disorders that appear to be visually identical and assisting dermatologists in their diagnostic procedures. The field of dermatology will be significantly impacted by the study's findings. Our work helps to the creation of precise, effective, and available dermatological diagnostic tools by bridging the gap between conventional diagnosis techniques and cutting-edge deep learning technologies. We also go over potential difficulties, ethical issues, and prospective future research routes, highlighting how crucial it is to keep this field innovative. This thorough study highlights the importance of artificial intelligence in improving patient care in the field of dermatology and the possibility of deep transfer learning to revolutionize dermatology diagnosis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Medical imaging

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Providing Security Solutions to IoT Devices Using Micro Version of Security Protocols over Wireless Networks

Providing Security Solutions to IoT Devices Using Micro Vers...

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Power, Control and Computing Technologies (ICPC2T), Conference on

作者： C Satisha Raghav Mehra M. Giri Department of Computer Science Bhagwant University Ajmer Rajasthan India Department of CSE AIT Chandigarh University Chandigarth India Department CSE Siddharth Institute of Engineering and Technology Puttur Andhra Pradesh India

ISBN: (数字)9798331530402

ISBN: (纸本)9798331530419

In this research paper proposed micro version of Security protocol for IoT environment, it consist of three phases, in first phase all IoT devices must be registered with server to get user login credentials, in second phase the IoT devices which are really wants to access with server must be authenticated by server, and in third phase data is transferred through secure IoT channel by providing integrity, security and confidentiality. Data security is provided with twenty rounds of sub keys. In security context, to hide the probabilistic relation between transmitted data to cipher text we can use diffusion matrix. Diffusion matrix is used to protect from attacks and in our study we calculated diffusion matrix by varying p and q values. We observed that change of one bit in a single block may change many bits in cipher text.

关键词： Ciphers Protocols Power measurement Data security Wireless networks Power control Probabilistic logic Security Internet of Things Servers

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Providing Security Solutions to IoT Devices Using Micro Version of Security Protocols over Wireless Networks 4

Providing Security Solutions to IoT Devices Using Micro Vers...

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4th International Conference on Power, Control and Computing Technologies, ICPC2T 2025

作者： Satisha, C. Mehra, Raghav Giri, M. Department of Computer Science Bhagwant University Rajasthan Ajmer India Department of CSE AIT Chandigarh University Chandigarh India Department CSE Siddharth Institute of Engineering and Technology Andhra Pradesh Puttur India

ISBN: (纸本)9798331530402

关键词： Wi-Fi

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Optimized Signcryption Mechanisms with SIMON and Ring Signatures for Healthcare Data Security

Optimized Signcryption Mechanisms with SIMON and Ring Signat...

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International Conference on ent Computing and Control Systems (ICICCS)

作者： Desetti Srinuvasa Rao Swathi Balija Rohit Kanauzia Ankit Garg K. Chandramouli Balajee Maram Department of CSE GMRIT Rajam Andhra Pradesh School of Computer Science and Artificial Intelligence SR University Warangal Department of Computer Science and Engineering Chandigarh University AIT-CSE UCRD Chandigarh University Mohali Punjab India Aditya Institute of Technology and Management(AITAM) Tekkali AP School of Computer Science and Artificial Intelligence SR University Warangal Telangana

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

With the rapid digitization in the health domain, needs arise to protect and safeguard sensitive information about patients in a secure, efficient, and prompt manner. This paper proposes an optimization mechanism for the protection of health data using techniques that apply ring signature-integrated lightweight block cipher SIMON. The SIMON encryption algorithm has wide-ranging speedy encryption that can be up to 25% faster than traditional block ciphers with a 30% saving in computational overheads and appropriate for resource-constrained environments. Ring signatures ensure there is anonymity of data yet authenticated in transmitting data. Therefore, this kind of proposed scheme will have higher integrity and confidentiality of data. The medical dataset was tested against the design; it even passed 98.5% attacks from cryptography. Encryption latency is still below 2 milliseconds. All the results ensure usability in modern systems of healthcare.

关键词： Ciphers Data privacy Quantum computing Scalability Medical services Encryption Usability Protection SIMO Optimization

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Energy efficient error rate optimization transmission in wireless sensor network

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Telkomnika (Telecommunication Computing Electronics and Control) 2016年第4期14卷 1368-1375页

作者： Sharada, K.A. Siddaraju Department of Computer Science Engineering JJT University Rajasthan India Department of CSE Dr. AIT VTU Karnataka India

Wireless Sensor Network is a collection of independent nodes and create a network for monitoring purposes in various scenarios like military operation, environmental operation etc. WSN network size is increasing very rapidly these days, due to large network size energy consumption is also increased and it has small battery, lifetime of network decreases due to early death of nodes and it impact the overall system performance. Clustering is a technique for enhance the network lifetime in WSN. Here in this paper we propose a new multi-objective adaptive swarm optimization (MASO) technique for clustering and computes the maximum number of clusters, which is best suited for the network. Each cluster has cluster head and cluster members and performed the task of local information extraction. Cluster head gathers all the extracted information from member nodes and send it to the base station, where base station performed global information extraction from all the cluster head nodes and generate some useful result. In MASO technique, object is used to find the best global position for the node and compare with existing position value. If new value is better than the old value, than node moves to a new position and object update their table for this new position. We are considering error probability in transmission of data packet in one hop communication. Here obtained the results are compared with other research in terms of overall network lifetime and effect on network lifetime when the size of the network is changed. We have fine tuned the node's decay rate and throughput of the network. © 2016 Universitas Ahmad Dahlan.

关键词： Base stations

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Text Region Identification in Indian Street Scene Images Using Stroke Width Transform and Support Vector Machine

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SN computer science 2021年第5期2卷 1-15页

作者： Shiravale, S.S. Sannakki, S.S. Jayadevan, R. Department of Computer Engineering MMCOE Pune India Department of Computer Science and Engineering GIT Belagavi India Department of Computer Engineering AIT Pune India

Detecting the presence of text in street scene images is a very crucial task for many applications and its complexity may vary from script to script due to the unique characteristics of each script. A technique to detect and localize text written in Devanagari script from scene images is presented in this paper. Initially, candidate regions are localized using low-level features like edge and colour. Due to the complex nature of scene images, these regions may contain irrelevant information. Stroke Width Transform (SWT) and geometric features are then extracted from these localized regions for correctly identifying the text regions. An efficient technique is proposed in this paper for the extraction of stroke width from dark text (foreground) on a light background as well as from light text (foreground) on dark background. Methods based on heuristic rules are inefficient for text and non-text identification due to the nonlinearity of extracted features. It has been observed that Support Vector Machines are the most popular and efficient classifiers for text/non-text classification. Also, an attempt is made here to explore other computationally less expensive classifiers like Bayesian due to its simplicity and Decision Tree due to its pure class partitioning power. Hence SVM, Bayesian and Decision Tree classifiers are used for the classification of text and non-text regions and the results are compared. An image dataset containing 1250 scene images has been created for experimentation. It is clear from the experimental results that the technique proposed in this paper outperforms some of the existing techniques in terms of accuracy. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Colour-based segmentation Devanagari script Natural scene images SVM Text detection Text extraction

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Image Encryption Using 4D Chaotic Map, Random Pixel Permutation, Image as a Key & DNA Encoding on Multiple Layers of a Chaotic Sequence

Image Encryption Using 4D Chaotic Map, Random Pixel Permutat...

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2023 International Conference on Computational Intelligence, Networks and Security, ICCINS 2023

作者： Aishworyann Kansal, Shrey Mishra, Vibhor Rarhi, Krishnendu Chandigarh University Ait Department of Computer Science & Engineering Punjab India

ISBN: (纸本)9798350313796

Digital security of an image cannot always be guaranteed using conventional encryption methods like symmetric and asymmetric ciphers. The study we performed is based on novel dynamic systems (4D chaotic maps), Random number permutation, key image, and DNA encoding. The suggested approach combines novel 4D chaotic maps having the concept of key image encryption in which an image is used as a key which is common for both the sender and the receiver. Based on the Random number Permutation, row and column vectors are generated using random numbers, and the channels of plain image are independently block-scrambled by scrambling column & row separately as per the random vectors, and XORed with the treated chaotic sequences. After that, key image which has a higher degree of content unpredictability is XORed with the chaotic sequence, and in the scheme culminating stage, DNA encoding was applied to further encrypt the image and corroborate the security. © 2023 IEEE.

关键词： Pixels

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Cloud Based Virtual Reality Training Platform for Occupational Safety 2

Cloud Based Virtual Reality Training Platform for Occupation...

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2nd International Conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Kirti Talwandi, Navjot Singh Thakur, Rakesh Singh, Kalpana Department of APEX Computer Science and Engineering AIT-CSE Chandigarh University Mohali India Department of APEX Computer Science and Engineering AIT-CSE UCRD Chandigarh University Mohali India

ISBN: (纸本)9798331541217

The impartial of this schoolwork remained to appraise how effectively simulated realism (VR) can be cast-off aimed at care exercise. user carried out a systematic examination of the works using a variety of information analysis techniques and resources, including Scopus, Google Scholar (via Harzing's "Publish or Perish"), and Web of science. The results of our investigation, which was approved obtainable utilizing technologies like VOSviewer, MAXQDA, BibExcel, and CiteSpace, showed that VR-based safety instruction is significantly more successful than conventional approaches and actively engages learners. We also investigated drawbacks such HMD accessibility and linguistic hurdles, and we suggested future study areas. In addition to highlighting VR's significant potential in safety training, this work offers a model for systematic reviews. © 2024 IEEE.

关键词： Virtual environments

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