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Journal articles on the topic 'Virtual IoT device'
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1
Fadziso, Takudzwa, Harshini Priya Adusumalli, and Mahesh Babu Pasupuleti. "Cloud of Things and Interworking IoT Platform: Strategy and Execution Overviews." Asian Journal of Applied Science and Engineering 7, no. 1 (2018): 85–92. http://dx.doi.org/10.18034/ajase.v7i1.49.
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An IoT platform is a multi-layer system that enables linked device automation. IoT platforms are enabling software that connects various hardware devices, access points, and networks to other sections of the value chain. Virtual objects are now essential in any IoT platform. In this work, we design and create a cloud-based IoT platform that allows users to register and initialize virtual objects, then consume them via the IoT marketplace and integrate them into IoT applications. The proposed IoT platform differs from previous IoT platforms in that it provides both hardware and software services on a single platform. The proposed IoT platform is distinct from the IoT marketplace where users can buy and sell virtual things. Based on virtual items in CoT, IoT platform and IoT marketplace experiments are undertaken. The proposed IoT platform is easy to use, secure, and trustworthy. An IoT testbed and a case study for reusing virtual objects in a residential environment are developed. It allows for virtual object discovery and sharing. Virtual objects can monitor and operate IoT devices.
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Xue, Fan Gabriella, and Matthew Caesar. "Towards Immersive Cloud-Based IoT Education." ACM SIGCOMM Computer Communication Review 54, no. 3 (2024): 10–17. https://doi.org/10.1145/3711992.3711995.
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An increasing number of students are becoming interested in learning about the Internet of Things (IoT) space. However, today, we lack scalable and efficient ways to bring hands-on IoT learning to many due to hardware accessibility, system complexity, and deployment environment constraints. This paper presents ThingVisor, an IoT learning platform that enables hands-on IoT development in an immersive virtual space. Specifically, it allows users to design, test, and deploy IoT devices virtually in a simulated IoT world with static and dynamic software verification as a complementary tool to IoT education. ThingVisor consists of (1) a Device Design Stack to configure virtual IoT devices, (2) an Immersive Runtime Stack to interact with devices and environment, and (3) a Device Emulator, which is a runtime environment used to execute virtual devices to get their behaviors. Our experiments confirm the learning effectiveness and user satisfaction of our platform. Additionally, we have demonstrated the scalability and usability of the system through load testing and application of the System Usability Scale. Our results indicate that students can achieve up to a 32% improvement in their scores after engaging with ThingVisor for two weeks, irrespective of their prior experience.
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Sudip, Chakraborty, and S. Aithal P. "Virtual IoT Device In C# WPF Using Sinric Pro." International Journal of Applied Engineering and Management Letters (IJAEML) 6, no. 2 (2022): 307–13. https://doi.org/10.5281/zenodo.7473766.
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<strong>Purpose: </strong><em>IoT is becoming the leading player in the industrial automation environment. In most scenarios, We experiment with IoT using a physical device. We can also research using a virtual device that can perform as real hardware. Without buying any physical hardware, we can visualize the status of the operating load or device which is being triggered through the IoT server or client endpoint. The researcher who is not from an electronics background or does not have sufficient knowledge to continue IoT research can do experiments using it. This paper will show how we can create such kinds of virtual instruments or devices. We use the C# client application adopted from Sinric Pro. We simplified the client module for new researchers in the IoT field for easy understanding. We added some Graphical user elements to display the status of the devices in real-life we see. The code is available for customization. </em> <strong>Design/Methodology/Approach</strong>: <em>We create and configure the device inside the Sinric Pro IoT server. Download the C# client and customize it for better understanding. We added some graphical elements to display the status of the load. Then we trigger the load from any endpoint like Alexa, the server dashboard, or a mobile phone application.</em> <strong>Findings/Result: </strong><em>We get better load status visibility using the GUI element and a minimalistic code structure to send or receive the data to and from the IoT server. Through this concept, we made IoT development or demonstration easy. With slight modifications, we can use this procedure to communicate with any IoT server. </em> <strong>Originality/Value: </strong><em>V</em><em>arious clients of fake load for IoT are available. Here we are experimenting more realistic way. Fetching the status and triggers the load using visual indication as the real world does. So it will be more understandable to us, and also, we can trigger the load from our GUI, which has the feature to send the value to the respective load.</em> <strong><em>Paper Type: </em></strong><em>Experimental-based Research.</em>
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Ullah, Israr, Muhammad Sohail Khan, and DoHyeun Kim. "IoT Services and Virtual Objects Management in Hyperconnected Things Network." Mobile Information Systems 2018 (June 13, 2018): 1–19. http://dx.doi.org/10.1155/2018/2516972.
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In recent past, Internet of Things- (IoT-) based applications have experienced tremendous growth in various domains, and billions of devices are expected to be connected to the Internet in near future. The first step for development of IoT-based applications is to virtualize the physical devices by abstracting device properties in virtual objects. Later, these virtual objects can be combined to compose different services for diverse applications. Many existing systems provide virtualization service for physical devices and service composition. But, with the growth of the network, when too many devices and services are added in the IoT network, its management will become a cumbersome task. This paper presents an architecture of IoT services and virtual objects management in hyperconnected things network to facilitate the management tasks. We also have implemented a Service and Virtual Objects Management (SVOM) system prototype to effectively organize and monitor the physical devices through corresponding virtual objects and services composed in the IoT environment. The proposed system also provides interface for user interaction to perform supported control operations on selected device and check device operational and fault status. For scalability analysis of the proposed system, we have performed simulation in the OMNeT++ simulator to study impact of the IoT network size on key performance measures like response time, throughput, and packet delivery ratio. Simulation results reveal that with the growing network size, the gateway nodes become the performance bottleneck. We have also performed resources requirement analysis for virtual objects and control overhead analysis of the proposed management system. Simulation results reveal that control overhead is insignificant in normal scenarios; however, in extreme network conditions, we may have to sacrifice fewer bits which is, in fact, worth nothing when compared to the flexibility and control offered by the proposed management system.
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Mehmood, Faisal, Israr Ullah, Shabir Ahmad, and Do-Hyeun Kim. "A Novel Approach towards the Design and Implementation of Virtual Network Based on Controller in Future IoT Applications." Electronics 9, no. 4 (2020): 604. http://dx.doi.org/10.3390/electronics9040604.
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The Internet of Things refers (IoT) to the billions of physical devices around the globe that are connected to the Internet, collecting and sharing data. The overall Internet of Things market is projected to be worth more than 50.6 billion U.S. dollars in 2020. IoT devices possess low processing capabilities, limited memory, limited storage, and minimal network protocol support. With the help of cloud computing technology, we can overcome the limited resources of IoT devices. A lot of research has been conducted on IoT device virtualization to facilitate remote access and control. The concept of virtualization in IoT is to provide a virtual representation of physical devices in the form of virtual objects. IoT devices are more likely to be accessed and communicate through virtual objects in the near future. In this paper, we present the design and implementation of building a virtual IoT network for a smart home. The virtual network is based on virtual objects and IoT controller. We derived the concept from Software Defined Network (SDN) and separated the control plane and data plane in the virtual IoT network. This enhanced the rapid development of diverse applications on top of the virtualization layer by establishing a dynamic end-to-end connection between IoT devices. This article briefly explains the design and development of the virtual network. Results achieved during experiments and performance analysis show that IoT controller enhances the capabilities of a virtual network by dynamically controlling the traffic congestion, handling mapping requests, and routing mechanisms.
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Ullah, Israr, Shakeel Ahmad, Faisal Mehmood, and DoHyeun Kim. "Cloud Based IoT Network Virtualization for Supporting Dynamic Connectivity among Connected Devices." Electronics 8, no. 7 (2019): 742. http://dx.doi.org/10.3390/electronics8070742.
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Internet of Things (IoT) is considered one of the future disruptive technologies and has attracted lots of research attention in the recent past. IoT devices are tiny sensing or actuating devices attached to daily life objects, capable of sending sensing data and receiving commands. Cloud computing technology provides tremendous computing and storage capacity over the Internet to overcome limited resources of IoT devices. Many studies are conducted on IoT device virtualization in the cloud environment to facilitate remote access and control. In the future, IoT devices will be accessed through its corresponding virtual objects. Just like the network of physical devices, there needs to be a network of virtual objects in the cyber world. In this paper, we present a concept of building a dynamic virtual network in the cloud environment among connected IoT devices. The key idea is to provide a mechanism for building a virtual network among connected IoT devices from different domains through their corresponding virtual objects in the cloud environment. This will facilitate the sharing of resources and the rapid development of diverse applications on top of the virtualization layer by establishing a dynamic end-to-end connection between IoT devices. In this study, we present a detailed design of the proposed system for building a virtual IoT network. We have also implemented three application layers protocols in OMNET++ for simulation of a virtual objects network to conduct performance analysis of the proposed IoT network virtualization.
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Sudip, Chakraborty, and S. Aithal P. "Alexa Enabled IoT Device Simulation Using C# And AWS Lambda." International Journal of Case Studies in Business, IT, and Education (IJCSBE) 7, no. 3 (2023): 359–68. https://doi.org/10.5281/zenodo.8329375.
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<strong>Purpose: </strong><em>Nowadays, device operation using voice commands is becoming popular. Several voice command services are available. Among them, Alexa from Amazon is the most popular. Almost Every day, vendors are integrating Alexa into their new products worldwide. We need physical devices for the device operation or understanding of the process flow of Alexa. Sometimes, physical devices are costly, or availability is poor. Here, we demonstrated how to create a simulated Alexa-enabled IoT device. We used several Amazon cloud services to execute the process flow. Alexa's skill is developed inside the Alexa developer console. To process the command, we use the AWS Lambda function. AWS IoT cloud service is used to trigger IoT devices over MQTT. For simulated devices, we are using a C# MQTT client. The researcher trying to simulate an Alexa-enabled device into their project can get some reference information from this work.</em> <strong>Design/Methodology/Approach</strong>: <em>We create a graphical user interface(GUI) to interact with the user or display the device's status. The GUI is connected with the C# AWS IoT Device Shadow client. We created IoT Things in the AWS cloud. Under the IoT Shadow, we created a Device shadow. The Alexa service triggers the lambda function. The Lambda function updates the Shadow register, which resides inside the cloud. The c# shadow client receives a notification when the device Shadow updates and updates the GUI element that represents the equipment. We can use any Alexa device to send voice commands, like the Alexa mobile app, Echo Dot, or Alexa PC app.</em> <strong>Findings/Result: </strong><em>Through this research work, we created and tested virtual devices that can be experiments or research work using Alexa voice commands. It has been tested for a long time. It performed well, and no issue was found. Using more code-level protection it can be robust for practical implementation.</em> <strong>Originality/Value: </strong><em>We found several fragmented documents over the web to implement Alexa-enabled virtual devices. After lots of study, we did practical and included the procedure in this research work. From voice input to load trigger, there are lots of steps involved. The complete guidance is not available easily. So through this research work, if someone follows, they can easily create a voice-operated device. This research work may add value to the researcher experimenting with the Alexa command-activated device.</em> <strong>Paper Type: </strong><em>Experimental-based Research.</em>
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Jung, Younchan, and Ronnel Agulto. "Virtual IP-Based Secure Gatekeeper System for Internet of Things." Sensors 21, no. 1 (2020): 38. http://dx.doi.org/10.3390/s21010038.
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The advantage of using the Network Address Translation device is that the internal IP address, which makes the IP address space of Internet of Things (IoT) devices expanded, is invisible from the outside and safe from external attacks. However, the use of these private IPv4 addresses poses traversal problems, especially for the mobile IoTs to operate peer-to-peer applications. An alternative solution is to use IPv6 technologies for future IoT devices. However, IPv6 package, including IPSec, is too complex to apply to the IoT device because it is a technology developed for the user terminal with enough computing power. This paper proposes a gatekeeper to enable the real IP addresses of IoTs inside the same subnetwork to be not explicitly addressable and visible from outside of the gatekeeper. Each IoT device publishes its virtual IP address via the Registrar Server or Domain Name System (DNS) with which the gatekeeper shares the address mapping information. While the gatekeeper maintains the mapping information for the local IoT devices, the registration server or DNS has global address mapping information so that any peer can reach the mapping information. All incoming and outgoing packets must pass through the gatekeeper responsible for the address conversion and security checks for them from the entrance. This paper aims to apply our gatekeeper system to a platform of self-driving cars that allows surrounding IoT cameras and autonomous vehicles to communicate with each other securely, safely, and rapidly. So, this paper finally analyzes improvement effects on latency to show that our gatekeeper system guarantees the latency goal of 20 ms under the environment of 5G links.
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Hong, Yoosung, and Geun-Hyung Kim. "Integrity Guarantee System in IoT Virtual Environment Platform: Through Hyperedfger Indy and MQTT." Korean Institute of Smart Media 13, no. 4 (2024): 76–85. http://dx.doi.org/10.30693/smj.2024.13.4.76.
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In this paper, we propose a system that improves the data integrity of IoT(Internet of Things) devices in the virtual environment by combining Hyperledger Indy and MQTT(Message Queuing Telemetry Transport). The system complements the limitations of the centralized system by realizing a DPKI(Decentralized Public Key Infrastructure) structure that utilizes a distributed network in publish-subscribe(pub/sub) pattern communication. Digital signature technology was applied to ensure the data integrity of IoT devices and communication scenarios between the four core components of the client, IoT device, broker, and blockchain, as well as a topic structure using a decentralized identifier to ensure safety in the virtual environment. We present a systematic method for transparent data exchange. To prove the performance of the proposed system, this paper conducted experiments on four scenarios and evaluated communication performance in a virtual environment. The experimental results confirmed that the proposed system provides a reliable IoT data communication structure in a virtual environment.
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Ren, Jie, and Lijuan Liu. "A Study on Information Classification and Storage in Cloud Computing Data Centers Based on Group Collaborative Intelligent Clustering." Journal of Electrical and Computer Engineering 2022 (March 25, 2022): 1–11. http://dx.doi.org/10.1155/2022/1476661.
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Internet of things (IoT) and cloud computing are combined to form a cloud computing data center, and cloud computing provides virtualization, storage, computing, and other support services for IoT applications. Data is the foundation and core of cloud IoT platform applications, and massive multisource heterogeneous IoT data aggregation and storage have basic requirements such as real-time, security, and scalability. This paper focuses on the aggregation and storage methods of massive heterogeneous cloud IoT data, solving the multisource data aggregation problem caused by inconsistent protocols and the heterogeneous data storage problem caused by inconsistent data types. A heterogeneous network protocol adaptation and data aggregation method is proposed for the multisource data aggregation problem caused by protocol inconsistency. A protocol adaptation layer is set up in the IoT virtual gateway to achieve compatibility with multiple types of data aggregation protocols, ensuring adaptive access to different types of IoT nodes, and on this basis, data is transmitted to the cloud IoT platform through a unified interface, shielding the variability of IoT sensing devices. Given the problems of device forgery and malicious tampering in the data aggregation process, we propose a fast authentication and data storage method for IoT devices based on “API key” and implant the device authentication API key into the protocol adaptation layer of the virtual gateway to realize the source authentication of IoT nodes and ensure the authenticity of data.
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Vairalkar, Manoj, Ratandeep Umak, Shivam Marwadi, and Janhvi Shende. "Virtual Button Using IOT." Journal of Telecommunication Study 8, no. 1 (2023): 7–12. http://dx.doi.org/10.46610/jts.2023.v08i01.002.
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Virtual buttons are a way to control the Internet of things (IoT) bone through a user interface that can be entered anywise. The buttons can be represented as symbols on a web runner or mobile app, and they can be used by the user to perform specific conduct analogous to turning on a light or conforming to the temperature. By using virtual buttons, stoners can interact with IoT bias without having to physically touch the device, making it more accessible. The buttons can also be programmed to perform multiple conducts with a single click, simplifying the user experience and making it easier to control IoT bias. Augment reality increases the associated control of the bias and appliances controlling them currently it's possible to control the appliances ever with the help of smart bias. Numerous styles are used to control the appliances ever but it becomes delicate for the stoner to use the smart bias because of the graphical stoner interface. For making this easier we use stoked reality technology for an easy way to control home appliances connected by the home network. Augmented reality technology can give virtual plates and apply fresh information to specific areas through a camera display.
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Lim, Jongbeom. "Scalable Fog Computing Orchestration for Reliable Cloud Task Scheduling." Applied Sciences 11, no. 22 (2021): 10996. http://dx.doi.org/10.3390/app112210996.
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As Internet of Things (IoT) and Industrial Internet of Things (IIoT) devices are becoming increasingly popular in the era of the Fourth Industrial Revolution, the orchestration and management of numerous fog devices encounter a scalability problem. In fog computing environments, to embrace various types of computation, cloud virtualization technology is widely used. With virtualization technology, IoT and IIoT tasks can be run on virtual machines or containers, which are able to migrate from one machine to another. However, efficient and scalable orchestration of migrations for mobile users and devices in fog computing environments is not an easy task. Naïve or unmanaged migrations may impinge on the reliability of cloud tasks. In this paper, we propose a scalable fog computing orchestration mechanism for reliable cloud task scheduling. The proposed scalable orchestration mechanism considers live migrations of virtual machines and containers for the edge servers to reduce both cloud task failures and suspended time when a device is disconnected due to mobility. The performance evaluation shows that our proposed fog computing orchestration is scalable while preserving the reliability of cloud tasks.
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Imran, Shabir Ahmad, and DoHyeun Kim. "Design and Implementation of Thermal Comfort System based on Tasks Allocation Mechanism in Smart Homes." Sustainability 11, no. 20 (2019): 5849. http://dx.doi.org/10.3390/su11205849.
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The recent trend in the Internet of Things (IoT) is bringing innovations in almost every field of science. IoT is mainly focused on the connectivity of things via the Internet. IoT’s integration tools are developed based on the Do It Yourself (DIY) approach, as the general public lacks technical skills. This paper presents a thermal comfort system based on tasks allocation mechanism in smart homes. This paper designs and implements the tasks allocation mechanism based on virtual objects composition for IoT applications. We provide user-friendly drag and drops panels for the new IoT users to visualize both task composition and device virtualization. This paper also designs tasks generation from microservices, tasks mapping, task scheduling, and tasks allocation for thermal comfort applications in smart home. Microservices are functional units of services in an IoT environment. Physical devices are registered, and their corresponding virtual objects are initialized. Tasks are generated from the microservices and connected with the relevant virtual objects. Afterward, they are scheduled and finally allocated on the physical IoT device. The task composition toolbox is deployed on the cloud for users to access the application remotely. The performance of the proposed architecture is evaluated using both real-time and simulated scenarios. Round trip time (RTT), response time, task dropping and latency are used as the performance metrics. Results indicate that even for worst-case scenarios, values of these metrics are negligible, which makes our architecture significant, better and ideal for task allocation in IoT network.
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Zouai, Meftah, Okba Kazar, Guadalupe Ortiz Bellot, Belgacem Haba, Nadia Kabachi, and M. Krishnamurhty. "Ambiance Intelligence Approach Using IoT and Multi-Agent System." International Journal of Distributed Systems and Technologies 10, no. 1 (2019): 37–55. http://dx.doi.org/10.4018/ijdst.2019010104.
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Internet of things is a network of objects mainly supported by electronic devices and electronic components such as sensors and electronic cards. These objects can be physical and virtual devices, sensors or actuators, are autonomous and have their own intelligence characteristics. On the other hand, smart environments are those in which sensors and actuators have been integrated, to react to events and to adapt to those present. The environment acquires intelligence through its intelligent components, or through the intelligence resulting from its interaction with other components. Our contribution is a proposal of Cognitive IoT (CIoT) devices structure by adding an agent layer to the device. Such layer provides the device with agent characteristics (intelligence, autonomy, cooperation and organization).
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Guy, Leshem, and Domb Menachem. "Strengthening IoT Network Protocols: A Model Resilient Against Cyber Attacks." IgMin Research 2, no. 2 (2024): 084–96. http://dx.doi.org/10.61927/igmin149.
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The pervasive Internet of Things (IoT) integration has revolutionized industries such as medicine, environmental care, and urban development. The synergy between IoT devices and 5G cellular networks has further accelerated this transformation, providing ultra-high data rates and ultra-low latency. This connectivity enables various applications, including remote surgery, autonomous driving, virtual reality gaming, and AI-driven smart manufacturing. However, IoT devices’ real-time and high-volume messaging nature exposes them to potential malicious attacks. The implementation of encryption in such networks is challenging due to the constraints of IoT devices, including limited memory, storage, and processing bandwidth. In a previous work [1], we proposed an ongoing key construction process, introducing a pivotal pool to enhance network security. The protocol is designed with a probability analysis to ensure the existence of a shared key between any pair of IoT devices, with the predefined probability set by the system designer. However, our earlier model faced vulnerabilities such as the “parking lot attack” and physical attacks on devices, as highlighted in the conclusion section. We present a complementary solution to address these issues, fortifying our previous protocol against cyber threats. Our approach involves the implementation of an internal Certification Authority (CA) that issues certificates for each IoT device before joining the network. Furthermore, all encryption keys are distributed by the primary IoT device using the Unix OS ‘passwd’ mechanism. If a device “disappears,” all encryption keys are promptly replaced, ensuring continuous resilience against potential security breaches. This enhanced protocol establishes a robust security framework for IoT networks, safeguarding against internal and external threats.
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Hardeep, Singh*. "SUBSET OF DOMAINS IMPACTED BY INTERNET OF THINGS." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 5, no. 2 (2018): 68–78. https://doi.org/10.5281/zenodo.1174135.
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Internet of Things; abbreviated as IoT; is a new trend in connectivity which is outside the realm of laptops and smartphones. <em>IoT is a recent communication paradigm in which the items of everyday life are embedded with micro-controllers, transceivers for digital communication, and with suitable protocol stacks that allow them to communicate with one another and also with the humans. These network connected items or devices use unique addressing schemes and</em> are smart enough to share information with human, with the cloud based applications and with each other as device to device communication; hence automating our tasks and lessening efforts to almost zero. The IoT, with the prospect of seamlessly integrating the real and the virtual worlds through the massive deployment of embedded devices, has opened up many new domains of its applications. This paper will introduce a subset of domains of applications of IoT including smart homes, smart wearables, smart cars, smart cities and smart industries.
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Lola, João, Carlos Serrão, and João Casal. "Towards Transparent and Secure IoT: Improving the Security and Privacy through a User-Centric Rules-Based System." Electronics 12, no. 12 (2023): 2589. http://dx.doi.org/10.3390/electronics12122589.
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In recent years, we have seen a growing wave in the integration of IoT (Internet of Things) technologies into society. This has created new opportunities, but at the same time given rise to several critical issues, creating new challenges that need to be addressed. One of the main challenges is the security and privacy of information that is processed by IoT devices in our daily lives. Users are, most of the time, unaware of IoT devices’ personal information collection and transmission activities that affect their security and privacy. In this work, we propose a solution that aims to increase the privacy and security of data in IoT devices, through a system that controls the IoT device’s communication on the network. This system is based on two basic and simple principles. First, the IoT device manufacturer declares their device’s data collection intentions. Second, the user declares their own preferences of what is permitted to the IoT device. The design of the system includes tools capable of analyzing packets sent by IoT devices and applying network traffic control rules. The objective is to allow the declaration and verification of communication intentions of IoT devices and control the communication of such devices to detect potential security and privacy violations. We have created a test-bed to validate the developed solution, based on virtual machines, and we concluded that our system has little impact on how the overall system performed.
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Seo, Hyeon-Ho, Jae-Woong Kim, Dong-Hyun Kim, and Seong-Hyun Park. "Internet of Things Simulation Learning Model Based on Virtual Remote Input Output." Journal of Computational and Theoretical Nanoscience 18, no. 5 (2021): 1423–28. http://dx.doi.org/10.1166/jctn.2021.9615.
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In our technology-driven world, various methods for teaching in an educational venue or in a simulated environment have been suggested especially for computer and coding education, among which virtual learning is a widely used teaching approach. In particular, IoT (Internet of Things)-related education has been made possible owing to the industrial developments that have occurred in various fields since the Fourth Industrial Revolution. Because it is mostly based on hardware and simple operations taught in a two-dimensional (2D) environment, conventional virtual learning of coding decreases the interest among learners. Therefore, there is a need for a three-dimensional (3D)-based educational approach that can arouse interest in learners. The proposed model allows various IoT systems to be indirectly built; it provides an inexpensive learning method by applying a simulation system in a 3D environment. The model is implemented on IoT devices, real IoT systems, and an IoT simulator based on the Arduino platform, thereby reducing the cost of building an education system while at the same time arousing the interest of learners with its 3D environment for learning. Various education-related content can be provided to learners through such an indirectly developed system. A header file type library is created by analyzing the prototype of the GPIO (general-purpose input/output) function suitable for the IoT device to be used in the virtual IoT simulator; a virtual remote IO module is also implemented. In addition, the physical and electrical characteristics of the peripheral devices to be applied were identified and implemented in a virtual space. Sensors and actuators with various characteristics were implemented to enhance the educational effect, and a test code was written to check the consistency of an operation between the real system and the virtual system. An experiment conducted to check the update cycle of the actual input and output showed that they differ by more than 5,000 fold on average. This is a physical limitation resulting from the difference between a method that directly controls an actual electrical signal with a register and a method of transmitting and receiving signals through a communication device. The actual system motion analysis showed no cases in which the automatic guided vehicle (AGV) deviated from the line and there was a slight difference in the responsiveness when returning to the original position from the deviation.
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Seo, Hyeon-Ho, Jae-Woong Kim, Dong-Hyun Kim, and Seong-Hyun Park. "Internet of Things Simulation Learning Model Based on Virtual Remote Input Output." Journal of Computational and Theoretical Nanoscience 18, no. 5 (2021): 1423–28. http://dx.doi.org/10.1166/jctn.2021.9615.
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In our technology-driven world, various methods for teaching in an educational venue or in a simulated environment have been suggested especially for computer and coding education, among which virtual learning is a widely used teaching approach. In particular, IoT (Internet of Things)-related education has been made possible owing to the industrial developments that have occurred in various fields since the Fourth Industrial Revolution. Because it is mostly based on hardware and simple operations taught in a two-dimensional (2D) environment, conventional virtual learning of coding decreases the interest among learners. Therefore, there is a need for a three-dimensional (3D)-based educational approach that can arouse interest in learners. The proposed model allows various IoT systems to be indirectly built; it provides an inexpensive learning method by applying a simulation system in a 3D environment. The model is implemented on IoT devices, real IoT systems, and an IoT simulator based on the Arduino platform, thereby reducing the cost of building an education system while at the same time arousing the interest of learners with its 3D environment for learning. Various education-related content can be provided to learners through such an indirectly developed system. A header file type library is created by analyzing the prototype of the GPIO (general-purpose input/output) function suitable for the IoT device to be used in the virtual IoT simulator; a virtual remote IO module is also implemented. In addition, the physical and electrical characteristics of the peripheral devices to be applied were identified and implemented in a virtual space. Sensors and actuators with various characteristics were implemented to enhance the educational effect, and a test code was written to check the consistency of an operation between the real system and the virtual system. An experiment conducted to check the update cycle of the actual input and output showed that they differ by more than 5,000 fold on average. This is a physical limitation resulting from the difference between a method that directly controls an actual electrical signal with a register and a method of transmitting and receiving signals through a communication device. The actual system motion analysis showed no cases in which the automatic guided vehicle (AGV) deviated from the line and there was a slight difference in the responsiveness when returning to the original position from the deviation.
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Baheti, Shrey, Shreyas Badiger, and Yogesh Simmhan. "VIoLET." ACM Transactions on Cyber-Physical Systems 5, no. 3 (2021): 1–39. http://dx.doi.org/10.1145/3446346.
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Internet of Things (IoT) deployments have been growing manifold, encompassing sensors, networks, edge, fog, and cloud resources. Despite the intense interest from researchers and practitioners, most do not have access to large-scale IoT testbeds for validation. Simulation environments that allow analytical modeling are a poor substitute for evaluating software platforms or application workloads in realistic computing environments. Here, we propose a virtual environment for validating Internet of Things at large scales (VIoLET), an emulator for defining and launching large-scale IoT deployments within cloud VMs. It allows users to declaratively specify container-based compute resources that match the performance of native IoT compute devices using Docker. These can be inter-connected by complex topologies on which bandwidth and latency rules are enforced. Users can configure synthetic sensors for data generation as well. We also incorporate models for CPU resource dynamism, and for failure and recovery of the underlying devices. We offer a detailed comparison of VIoLET’s compute and network performance between the virtual and physical deployments, evaluate its scaling with deployments with up to 1, 000 devices and 4, 000 device-cores, and validate its ability to model resource dynamism. Our extensive experiments show that the performance of the virtual IoT environment accurately matches the expected behavior, with deviations levels within what is seen in actual physical devices. It also scales to 1, 000s of devices and at a modest cloud computing costs of under 0.15% of the actual hardware cost, per hour of use, with minimal management effort. This IoT emulation environment fills an essential gap between IoT simulators and real deployments.
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Khan, Muhammad Sohail, and DoHyeun Kim. "DIY Interface for Enhanced Service Customization of Remote IoT Devices: A CoAP Based Prototype." International Journal of Distributed Sensor Networks 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/542319.
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DIY vision for the design of a smart and customizable world in the form of IoT demands the involvement of general public in its development process. General public lacks the technical depths for programming state-of-the-art prototyping and development kits. Latest IoT kits, for example, Intel Edison, are revolutionizing the DIY paradigm for IoT and more than ever a DIY intuitive programming interface is required to enable masses to interact with and customize the behavior of remote IoT devices on the Internet. This paper presents the novel implementation of such a system enabling general public to customize the behavior of remote IoT devices through a visual interface. The interface enables the visualization of the resources exposed by a remote CoAP device in the form of graphical virtual objects. The VOs are used to create service design through simple operations like drag-and-drop and properties settings. The design is maintained as an XML document, thus being easily distributable and recognizable. CoAP proxy acts as an operation client for the remote device and also provides communication link between the designer and the device. The paper presents the architecture, detailed design, and prototype implementation of the system using state-of-the-art technologies.
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Kanehisa, Rodrigo, Felipe Barbosa, and Alberico De Castro. "5G energy efficiency for Internet of Things." Academic Journal on Computing, Engineering and Applied Mathematics 1, no. 2 (2020): 14–23. http://dx.doi.org/10.20873/uft.2675-3588.2020.v1n2.p14-23.
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The Internet of Things (IoT) consists of devices capable of measuring the environment and executing tasks without human intervention. Due to its size, these devices have restrictions in processing, memory, and battery. These devices can reach a trillion nodes and, therefore, requires network connections that are capable of both handle a large number of nodes connected and low energy transmission. The fifth generation of telecommunications technology (5G) is a key concept to address those requirements as new applications and business models require new criteria such as security trustworthy, ultra-low latency, ultra-reliability, and energy efficiency. Although the next generation of connections is at its early stage, progress has been made to achieve 5G enabled IoT technologies. This paper describes a review of the main technologies such as Cloud, Software Defined Network, device-to-device communication, Evolved Package Core and Network Virtual Function Orchestration that are planned to be applied for both fields of 5G and IoT.
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Arman, Ala, Pierfrancesco Bellini, Daniele Bologna, Paolo Nesi, Gianni Pantaleo, and Michela Paolucci. "Automating IoT Data Ingestion Enabling Visual Representation." Sensors 21, no. 24 (2021): 8429. http://dx.doi.org/10.3390/s21248429.
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The Internet of things has produced several heterogeneous devices and data models for sensors/actuators, physical and virtual. Corresponding data must be aggregated and their models have to be put in relationships with the general knowledge to make them immediately usable by visual analytics tools, APIs, and other devices. In this paper, models and tools for data ingestion and regularization are presented to simplify and enable the automated visual representation of corresponding data. The addressed problems are related to the (i) regularization of the high heterogeneity of data that are available in the IoT devices (physical or virtual) and KPIs (key performance indicators), thus allowing such data in elements of hypercubes to be reported, and (ii) the possibility of providing final users with an index on views and data structures that can be directly exploited by graphical widgets of visual analytics tools, according to different operators. The solution analyzes the loaded data to extract and generate the IoT device model, as well as to create the instances of the device and generate eventual time series. The whole process allows data for visual analytics and dashboarding to be prepared in a few clicks. The proposed IoT device model is compliant with FIWARE NGSI and is supported by a formal definition of data characterization in terms of value type, value unit, and data type. The resulting data model has been enforced into the Snap4City dashboard wizard and tool, which is a GDPR-compliant multitenant architecture. The solution has been developed and validated by considering six different pilots in Europe for collecting big data to monitor and reason people flows and tourism with the aim of improving quality of service; it has been developed in the context of the HERIT-DATA Interreg project and on top of Snap4City infrastructure and tools. The model turned out to be capable of meeting all the requirements of HERIT-DATA, while some of the visual representation tools still need to be updated and furtherly developed to add a few features.
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Reenu Shukal and Dr. Gaurav Khandelwal. "An Analysis of Implementable Security Algorithms in the internet of things Envioronment." Journal of Advances in Science and Technology 20, no. 2 (2024): 109–15. http://dx.doi.org/10.29070/a1f2r165.
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In the scientific community, the Internet of Things (IoT) is the latest buzzword. We live in an age where Internet access is not only possible for the vast majority of the population, but also increasingly affordable. The number of gadgets with internet access and built-in sensors continues to rise. Indeed, the prevalence and prevalence of smart phones, and the use of such devices, are on the rise. With this idea, anybody can hook up any device to the web. However, a major security issue will arise from the practise of storing and communicating data with anyone and any device. It's also unclear how well data can be transferred, communicated, and shared in this setting. In this paper, we discuss concerns about IoT security, including those of privacy, reliability, and accessibility. The rapidly evolving applications made possible by the IoT have drastically altered daily life, making it feel more fantastical and akin to living in a virtual world. Due to its open nature, the Internet of Things (IoT) might pose significant security challenges. A variety of methods, including encryption, are employed to protect the information transmitted by IoT devices.
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Barbosa, Guilherme Nunes Nasseh, and Diogo Menezes Ferrazani Mattos. "A Practical Evaluation of a Federated Learning Application in IoT Device and Cloud Environment." Journal of the Brazilian Computer Society 31, no. 1 (2025): 1–10. https://doi.org/10.5753/jbcs.2025.4324.
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Internet of Things (IoT) devices have grown exponentially in recent years, resulting in valuable data for machine learning applications. Traditionally, machine learning models require centralized data collection and processing, which is not feasible in the IoT landscape due to high density and growing data privacy concerns. Federated Learning is a trend in this scenario, as it allows collaborative training of models on IoT devices, distributed and without the need to share data. This paper examines a federated learning framework for IoT devices, employing a parameter server topology in a benign node environment without considering strategies for optimizing model performance. The evaluation is conducted in two distinct scenarios: (i) a testbed of IoT devices equipped with ARM processors and limited to 2GB of RAM, and (ii) a virtualized cloud environment with a mixture of resource-constrained virtual machines. The experiments use non-identically distributed (non-IID) datasets—MNIST for the IoT testbed and CIFAR-10 for the cloud environment—evaluated under various client configurations and aggregation strategies. In the IoT device scenario, the framework achieved an accuracy of up to 0.6 after ten rounds of global aggregation, while the cloud environment attained a maximum accuracy of 0.4. These results demonstrate the feasibility of applying FL in resource-constrained IoT environments, with scalability and accuracy influenced by the number of clients and local training epochs.
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Ganesan, Elaiyasuriyan, I.-Shyan Hwang, Andrew Tanny Liem, and Mohammad Syuhaimi Ab-Rahman. "SDN-Enabled FiWi-IoT Smart Environment Network Traffic Classification Using Supervised ML Models." Photonics 8, no. 6 (2021): 201. http://dx.doi.org/10.3390/photonics8060201.
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Due to the rapid growth of the Internet of Things (IoT), applications such as the Augmented Reality (AR)/Virtual Reality (VR), higher resolution media stream, automatic vehicle driving, the smart environment and intelligent e-health applications, increasing demands for high data rates, high bandwidth, low latency, and the quality of services are increasing every day (QoS). The management of network resources for IoT service provisioning is a major issue in modern communication. A possible solution to this issue is the use of the integrated fiber-wireless (FiWi) access network. In addition, dynamic and efficient network configurations can be achieved through software-defined networking (SDN), an innovative and programmable networking architecture enabling machine learning (ML) to automate networks. This paper, we propose a machine learning supervised network traffic classification scheduling model in SDN enhanced-FiWi-IoT that can intelligently learn and guarantee traffic based on its QoS requirements (QoS-Mapping). We capture the different IoT and non-IoT device network traffic trace files based on the traffic flow and analyze the traffic traces to extract statistical attributes (port source and destination, IP address, etc.). We develop a robust IoT device classification process module framework, using these network-level attributes to classify IoT and non-IoT devices. We tested the proposed classification process module in 21 IoT/Non-IoT devices with different ML algorithms and the results showed that classification can achieve a Random Forest classifier with 99% accuracy as compared to other techniques.
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Lee, Hwi-Ho, Jung-Hyok Kwon, and Eui-Jik Kim. "Design and Implementation of Virtual Private Storage Framework Using Internet of Things Local Networks." Symmetry 12, no. 3 (2020): 489. http://dx.doi.org/10.3390/sym12030489.
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This paper presents a virtual private storage framework (VPSF) using Internet of Things (IoT) local networks. The VPSF uses the extra storage space of sensor devices in an IoT local network to store users’ private data, while guaranteeing expected network lifetime, by partitioning the storage space of a sensor device into data and system volumes and, if necessary, logically integrating the extra data volumes of the multiple sensor devices to virtually build a single storage space. When user data need to be stored, the VPSF gateway divides the original data into several blocks and selects the sensor devices in which the blocks will be stored based on their residual energy. The blocks are transmitted to the selected devices using the modified speedy block-wise transfer (BlockS) option of the constrained application protocol (CoAP), which reduces communication overhead by retransmitting lost blocks without a retransmission request message. To verify the feasibility of the VPSF, an experimental implementation was conducted using the open-source software libcoap. The results demonstrate that the VPSF is an energy-efficient solution for virtual private storage because it averages the residual energy amounts for sensor devices within an IoT local network and reduces their communication overhead.
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Nachiappan, V. Alagammai, Raj esh, and Rajalakshmi Devaraj. "Remote Diagnosis of the Patient through IOT and Virtual Reality, Classification of the Cloud Data Using ANN." Revista Gestão Inovação e Tecnologias 11, no. 1 (2021): 6025–34. http://dx.doi.org/10.47059/revistageintec.v11i1.1876.
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Telemedicine was an existing field, but the current situation its becoming a more important necessity in the health care industry.my major aim is To increase the reliability of the online diagnosis using IoT and virtual Reality for the future with help of advanced technologies. Bridge between the patients and doctors. Patients may have wearable devices with AR glass, the measured data will be send to the raspberry pi based router device which is having the Node Red Software for connecting N- no of patients easily and also control the devices remotely based on the self-learning algorithms. All the information can be classified based on type of diseases and classified based on artificial neural network-based algorithms, the information is passed to doctors. Doctor may also have device with wearable Glass, with patient information and details will be displayed on the AR glass. So, we can connect N- of Patients and N- doctors with this technology also sharing the information through the cloud and IOT devices, which will help for the current trend and future technology for the society.
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Goto, Ren, Taiki Yoshikawa, Hijiri Komura, Kazushige Matama, Chihiro Nishiwaki, and Katsuhiro Naito. "Design and Basic Evaluation of Virtual IPv4-based CYPHONIC adapter." Journal of Systemics, Cybernetics and Informatics 20, no. 3 (2022): 55–63. http://dx.doi.org/10.54808/jsci.20.03.55.
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The rapid spread of cloud services and the Internet of Things (IoT) leads to a request for secure communication between devices, called zero-trust security. However, security tends to be a low priority compared to the designated service because zero-trust security requires security knowledge. Therefore, a secure communication framework for developers’ service development process is essential as the security measures. The authors have developed CYber PHysical Overlay Network over Internet Communication (CYPHONIC) for secure end-to-end communication between devices. Since the CYPHONIC provides secure communication, it also performs as the secure communication framework. The current implementation requires installing the device program into the end devices to join our overlay network. However, it should support general devices such as embedded devices or dedicated service servers even if they refuse to install the additional program. This paper proposes a new technology to support these general devices without installing the device program into the devices. We developed a CYPHONIC adapter to provide secure communication to general devices. It shows that general devices can communicate over the overlay network through the proposed CYPHONIC adapter.
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Simiscuka, Anderson Augusto, Tejas Moreshwar Markande, and Gabriel-Miro Muntean. "Real-Virtual World Device Synchronization in a Cloud-Enabled Social Virtual Reality IoT Network." IEEE Access 7 (2019): 106588–99. http://dx.doi.org/10.1109/access.2019.2933014.
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Anantwal, Sumit. "J.A.R.V.I.S. AI: A Virtual Voice Assistant System." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem45133.
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JARVIS is a next-generation virtual assistant designed to overcome limitations in natural language understanding, contextual awareness, and device compatibility. By leveraging technologies like NLP, machine learning, and IoT integration, it offers personalized interactions, automates tasks, and enhances productivity across domains such as smart homes, healthcare, and finance. With robust home automation capabilities, JARVIS can control and optimize household appliances, lighting, and security systems, creating a smarter and more responsive living environment. Additionally, its object detection features enable real-time identification and analysis of visual inputs, making it valuable for applications like surveillance, accessibility support, and smart navigation. JARVIS adapts to user preferences over time, ensuring relevant and timely assistance while prioritizing privacy and data security through robust measures. Its scalable architecture supports future growth and seamless integration across devices, fostering intuitive, efficient technology experiences. JARVIS aspires to redefine virtual assistants, enriching daily life through smarter, user-centric, and secure interactions. Index Terms: Natural Language Processing (NLP), Machine Learning, Internet of Things (IoT), Voice & Speech Recognition, User Personalization, Home Automation, Object Detection
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Gupta, Richa. "Decision Support Systems for IoT Based Infrastructures." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 9, no. 3 (2018): 1074–81. http://dx.doi.org/10.17762/turcomat.v9i3.13896.
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Computation offloading divides enormous computational tasks across numerous computer resources, circumventing hardware limits. Edge computing can employ vast quantities of data, individual preferences, and clever algorithms by offloading smart models to high-performance cloud servers. We propose a getaway-centric IoT system to enable intelligent and autonomous IoT devices at the computer infrastructure's edge. Edge computing manages IoT devices by selecting and applying the best control factor from a pool of intelligent services. The cloud-based intelligent service engine provides intelligent services by offloading intelligence and optimisation algorithms. Thus, the gateway's decision-making model may choose the best alternative. Resource virtualization-based gateway-based device management facilitates user monitoring and visualisation in the proposed IoT system. The gateway evaluates context-based profiles to enable real-time connection with intelligent services and dynamic application of the appropriate control factor to the physical device using the virtual resource. We propose two smart models to learn characteristics of a user's home environment using deep learning and build inference models for the intelligent service engine to optimise energy usage with the recommended IoT system. Inference methods forecast heater energy usage. Heaters set the environment. The decision-making algorithm also lowers the heater setting based on the two use numbers, reducing energy consumption and producing a user-desired environment.
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Raja, S. P., T. Dhiliphan Rajkumar, and Vivek Pandiya Raj. "Internet of Things: Challenges, Issues and Applications." Journal of Circuits, Systems and Computers 27, no. 12 (2018): 1830007. http://dx.doi.org/10.1142/s0218126618300076.
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Internet of Things (IoT) can be defined as a thing or device, physical and virtual, connected and communicating together, and integrated to a network for a specific purpose. The IoT uses technologies and devices such as sensors, radio-frequency identification (RFID) and actuators to collect data. IoT is not only about collecting data generated from sensors, but also about analyzing it. IoT applications must, of necessity, keep out all attackers and intruders so as to thwart attacks. IoT must allow for information to be shared, with every assurance of confidentiality, and is about a connected environment where people and things interact to enhance the quality of life. IoT infrastructure must be an open source, without ownership, meaning that anyone can develop, deploy and use it. The objective of this paper is to discuss the various challenges, issues and applications confronting the Internet of Things.
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Naret, S., T. Annop, S. Supharoek, and J. Thanadon. "Visualizing electrical energy consumption with virtual augmented technology and the internet of things." IOP Conference Series: Earth and Environmental Science 1094, no. 1 (2022): 012010. http://dx.doi.org/10.1088/1755-1315/1094/1/012010.
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Abstract Power consumption was considered one of the major expenses in households and small offices in the COVID pandemic situation. The proposed method employs virtual augmented technology and the Internet of Things (IoT) to provide a visual solution for monitoring the power consumption of electrical equipment. The IoT sensors are linked via mobile phones or portable communication devices. For the proposed work, the energy sensor devices are installed on the 4 single-phase electrical devices in the office room equipment. That equipment’s electrical consumption was saved, processed through the ESP8266 board, and then transmitted through WiFi to collect data on the cloud server. The saved electrical energy data in the dashboard can be displayed as a visual comparison with AR technology by using the mobile phone camera to scan the marker of each electrical device. The experimental results show that the value of electrical energy is accurate, and the data values can be used to manage the power consumption of electrical equipment.
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Tiwari,, Arun. "Security and Privacy Analysis in Internet of Things." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31055.
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The concept of the Internet of Things (IoT) promises to make all electronic devices smart, connected and capable of functioning together seamlessly courtesy of a worldwide network that links virtual elements with physical ones. Every IoT item in this network has a unique identification number to indicate its position in this system. In addition, connectivity is important for effective coordination with some low-tech gadgets. In this chapter, we shall be discussing the relevant IoT systems and security issues related to them including privacy, security attacks, means of securing IoT environments as well as appropriate models for privacy and security in IoT. This paper looks at various privacy concerns as well as security problems that emanate from the internet of things like data breaches, identity thefts and unauthorized entries. Finally, it also discusses multiple approaches that can be adopted to minimize these risks such as using techniques like data protection, access control and encryption etc. Keywords Internet of Things (IoT), Data Privacy, Physical security, Device Access
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del Campo, Guillermo, Edgar Saavedra, Luca Piovano, Francisco Luque, and Asuncion Santamaria. "Virtual Reality and Internet of Things Based Digital Twin for Smart City Cross-Domain Interoperability." Applied Sciences 14, no. 7 (2024): 2747. http://dx.doi.org/10.3390/app14072747.
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The fusion of Internet of Things (IoT), Digital Twins, and Virtual Reality (VR) technologies marks a pivotal advancement in urban development, offering new services to citizens and municipalities in urban environments. This integration promises enhanced urban planning, management, and engagement by providing a comprehensive, real-time digital reflection of the city, enriched with immersive experiences and interactive capabilities. It enables smarter decision-making, efficient resource management, and personalized citizen services, transforming the urban landscape into a more sustainable, livable, and responsive environment. The research presented herein focuses on the practical implementation of a DT concept for managing cross-domain smart city services, leveraging VR technology to create a virtual replica of the urban environment and IoT devices. Imperative for cross-domain city services is interoperability, which is crucial not only for the seamless operation of these advanced tools but also for unlocking the potential of cross-service applications. Through the deployment of our model at the IoTMADLab facilities, we showcase the integration of IoT devices within varied urban infrastructures. The outcomes demonstrate the efficacy of VR interfaces in simplifying complex interactions, offering pivotal insights into device functionality, and enabling informed decision-making processes.
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Hayashi, Victor Takashi, and Wilson Vicente Ruggiero. "Hands-Free Authentication for Virtual Assistants with Trusted IoT Device and Machine Learning." Sensors 22, no. 4 (2022): 1325. http://dx.doi.org/10.3390/s22041325.
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Virtual assistants, deployed on smartphone and smart speaker devices, enable hands-free financial transactions by voice commands. Even though these voice transactions are frictionless for end users, they are susceptible to typical attacks to authentication protocols (e.g., replay). Using traditional knowledge-based or possession-based authentication with additional invasive interactions raises users concerns regarding security and usefulness. State-of-the-art schemes for trusted devices with physical unclonable functions (PUF) have complex enrollment processes. We propose a scheme based on a challenge response protocol with a trusted Internet of Things (IoT) autonomous device for hands-free scenarios (i.e., with no additional user interaction), integrated with smart home behavior for continuous authentication. The protocol was validated with automatic formal security analysis. A proof of concept with websockets presented an average response time of 383 ms for mutual authentication using a 6-message protocol with a simple enrollment process. We performed hands-free activity recognition of a specific user, based on smart home testbed data from a 2-month period, obtaining an accuracy of 97% and a recall of 81%. Given the data minimization privacy principle, we could reduce the total number of smart home events time series from 7 to 5. When compared with existing invasive solutions, our non-invasive mechanism contributes to the efforts to enhance the usability of financial institutions’ virtual assistants, while maintaining security and privacy.
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Pise, Prakash. "Mobile Cloud IoT for Resource Allocation with Scheduling in Device- Device Communication and Optimization based on 5G Networks." International Journal on Future Revolution in Computer Science & Communication Engineering 8, no. 3 (2022): 33–42. http://dx.doi.org/10.17762/ijfrcsce.v8i3.2094.
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Internet of Things (IoT) is revolutionising technical environment of traditional methods as well as has applications in smart cities, smart industries, etc. Additionally, IoT enabled models' application areas are resource-constrained as well as demand quick answers, low latencies, and high bandwidth, all of which are outside of their capabilities. The above-mentioned issues are addressed by cloud computing (CC), which is viewed as a resource-rich solution. However, excessive latency of CC prevents it from being practical. The performance of IoT-based smart systems suffers from longer delay. CC is an affordable, emergent dispersed computing pattern that features extensive assembly of diverse autonomous methods. This research propose novel technique resource allocation and task scheduling for device-device communication in mobile Cloud IoT environment based on 5G networks. Here the resource allocation has been carried out using virtual machine based markov model infused wavelength division multiplexing. Task scheduling is carried out using meta-heuristic moath flame optimization with chaotic maps. So, by scheduling tasks in a smaller search space, system resources are conserved. We run simulation tests on benchmark issues and real-world situations to confirm the effectiveness of our suggested approach. The parameters measured here are resource utilization of 95%, response time of 89%, computational cost of 35%, power consumption of 38%, QoS of 85%.
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Bhake, Sarthak, Sahil Parekh, Sakshi Kulkarni, Sejal Sayam, Shajjad Shaikh, and Prof Ashwini Barbadekar. "Smart Mirror using IoT and Raspberry Pi." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (2022): 382–85. http://dx.doi.org/10.22214/ijraset.2022.47880.
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Abstract: Smart mirrors as a concept are growing rapidly. These mirrors directly affect the day to day lives of the people as it provides customization and a luxurious lifestyle. With the help of devices like smart mirrors people are getting exposed to technology and are in turn contributing to a tech supported lifestyle. The smart mirror is one such device where a normal mirror acts as a smart device which consists of a user interface with which the user can interact. This paper proposes a model which is robust and can be utilized by individuals in their day to day lives. The proposed model in this paper is in the form of a mirror developed with a combination of hardware and software. The mirror incorporates Oracle VM Virtual Box which supports the Raspbian OS. The model uses the Magic Mirror Module on the software part to implement different features like Calendar, Music App, Weather Forecast, News etc. These features are implemented using their respective API’s. The proposed model can be scaled to add more and more features thus making it more robust, also the model is very cost effective. With the help of this people would be able to ease their lifestyle a bit and automate things as much as possible.
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Yang, Jinhong, Hyojin Park, Yongrok Kim, and Jun Kyun Choi. "A Virtual Object Hosting Technology for IoT Device Controlling on Wireless AP's." Journal of Korea Information and Communications Society 39C, no. 2 (2014): 164–72. http://dx.doi.org/10.7840/kics.2014.39c.2.164.
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Telagam, Nagarjuna, Nehru Kandasamy, and Somanaidu U. "Smart Device for Women's Safety Designed Using IoT and Virtual Instrumentation Browser." International Journal of Interactive Mobile Technologies (iJIM) 17, no. 02 (2023): 166–77. http://dx.doi.org/10.3991/ijim.v17i02.35227.
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In the present technological developments, the internet of things (IoT) technology connects all interconnected networks. The attacks on women are increasing daily in Indian countries. If the woman is not carrying a mobile phone or device, she cannot contact the police station or other family members. This proposed method will help the women identify the exact location and inform the police station in such a scenario. The Emergencies, the women, can press the button once the location information is tracked. The purpose of this project is to help women in emergencies. Location tracking and short service messages are also sent to the family members and nearby police stations.
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Lee, Seungwoon, Sijung Kim, and Byeong-hee Roh. "Mixed Reality Virtual Device (MRVD) for seamless MR-IoT-Digital Twin convergence." Internet of Things 26 (July 2024): 101155. http://dx.doi.org/10.1016/j.iot.2024.101155.
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Sajjad, Syed Muhammad, Muhammad Rafiq Mufti, Muhammad Yousaf, et al. "Detection and Blockchain-Based Collaborative Mitigation of Internet of Things Botnets." Wireless Communications and Mobile Computing 2022 (April 20, 2022): 1–26. http://dx.doi.org/10.1155/2022/1194899.
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DDoS (distributed denial of service) attacks have drastically effected the functioning of Internet-based services in recent years. Following the release of the Mirai botnet source code on GitHub, the scope of these exploitations has grown. The attackers have been able to construct and launch variations of the Mirai botnet thanks to the open-sourcing of the Mirai code. These variants make the signature-based detection of these attacks challenging. Moreover, DDoS attacks are typically detected and mitigated reactively, making DDoS mitigation solutions very expensive. This paper presents a proactive IoT botnet detection system that detects the anomalies in the behavior of the IoT device and mitigates the DDoS botnet exploitation at the source end, which makes our proposal a low-cost solution. Further, this paper uses a collaborative trust relationship-based threat intelligence-sharing mechanism to prevent other IoT devices from being compromised by the detected botnet. The researchers have evaluated the collaborative threat intelligence sharing mechanism using Ethereum Virtual Machine and Hyperledger. The performance of our proposed system can detect 97% of the Mirai botnet attack activities. Furthermore, our collaborative threat intelligence sharing mechanism based on the Ethereum Virtual Machine showed more scalability.
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Roselind, J. Deepika, H. M. Naveen, and S.Yuvaraj. "Artificial Intelligence enabled Dynamic Bandwidth Allocation Optimization in IoT for improved QoS." International Journal of Scientific Methods in Intelligence Engineering Networks 01, no. 02 (2023): 33–43. http://dx.doi.org/10.58599/ijsmien.2023.1204.
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The Internet of Things (IoT) is a collection of intelligently connected devices that are connect to the internet. Every day, as technology advances, an IoT device outnumbers humans on the world. The Internet of Things (IoT) systems would connect not only physical users and devices, but also virtual networks and devices that have already been implemented in various scenarios using new networking, computing, and integrated system technologies. With the rapid advancement of technology, the number of devices involved grows rapidly. IoT systems have crucial issues in supplying sufficient bandwidth to IoT Devices for Improving Quality in Services provided in the form of QoS (Quality of Service) parameters, depending on the volume of devices and data. The proposed work is an artificial intelligence enabled dynamic bandwidth allocation optimization in IoT for improved QoS comprising of IoT devices, router, bandwidth data, KM-PSO clustering, Deep Alternative Neural Network (DANN), Dynamic Bandwidth Allocation Optimization, and QoS Estimation. It provides a scalable solution for allocating the bandwidth for the IoT enabled devices for improving QoS parameters. The work uses K-Means-Particle Swarm Optimization (KM-PSO) for generating the optimum number of clusters for improving the accuracy of the proposed work. Once the optimal number of clusters are generated, a Deep Alternative Neural Network (DANN) used in the present invention detects the traffic from the IoT devices, predicts the required bandwidth to be allocated. The Artificial Intelligence enabled Dynamic Bandwidth Allocation Optimization (AIEDBAO) uses Fuzzy Logic Controller (FLC) for allocating Bandwidth based on the traffic rules generated. The improved QoS parameters achieved with the present invention are Bandwidth Consumption of 34.5Mbps, Packet Delivery Delay (PDD) of 32ms, Packet Loss of 4% and Throughput of 99% at supply of 50Mbps
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Ahmed, Y. Nasir, S. Pakkir Mohideen, and Mohammad Pasha. "Task scheduling in cloud-fog computing using discrete binary particle swarm meta-heuristic with modified sigmoid function." Journal of Information and Optimization Sciences 44, no. 6 (2023): 1023–33. http://dx.doi.org/10.47974/jios-1226.
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Cloud-Fog IoT networking is a resourceful technology to aid the processing of IoT end device requests. These devices generate tasks that need optimized computing and reduced latency for applications that operate in real-time environments. This article sets forth a cloud-fog task scheduler that schedules diverse tasks on vertically scaled Cloud and Fog virtual machines. For the proposed Binary Particle Swarm Optimizer (BPSO) based scheduler, an apt choice identified is to employ a modified sigmoid function with the logarithm decreasing inertia weight policy to deliver an optimal scheduling scheme. Moreover, the parameters of the BPSO are tuned inferring the best practices prescribed in literature. The results show that proposed method caters better than existing heuristic techniques to improve makespan and load imbalance.
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C. Ramakrishna, Et al. "A Smart System for Future Generation based on the Internet of Things Employing Machine Learning, Deep Learning, and Artificial Intelligence : Comprehensive Survey." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 1798–815. http://dx.doi.org/10.17762/ijritcc.v11i9.9167.
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The Internet of Things (IoT) is a networked system including interconnected things, devices, and networks that utilize the internet for communication and data exchange. The entity engages in interactions with both its internal and external surroundings. The IoT is capable of seeing the surrounding environment and responding in a way that is appropriate and adaptive. The utilization of advanced technology in this context enhances the environment and thus enhances the overall well-being of humanity. The IoT facilitates inter-device communication, whether through physical or virtual means. The IoT facilitates the enhancement of environmental intelligence, enabling seamless connectivity across many devices at any given moment. The concepts centred on the IoT, such as augmented reality, high-resolution video streaming, autonomous vehicles, intelligent environments, and electronic healthcare, have become pervasive in contemporary society. These applications have requirements for faster data rates, larger bandwidths, enhanced capacities, decreased latencies, and increased throughputs. IoT and Machine learning (ML) are among the fields of research that have shown significant potential for advancement. ML and IoT are used to build intelligent systems. Those networks will modify the ways in which worldwide entities exchange information. This article gives a comprehensive survey of the upcoming 5G-IoT situation, as well as a study of IoT smart system applications and usages. In addition to covering the latest developments in ML and deep learning (DL) and their impact on 5G-IoT, this article describes a comprehensive study of these important enabling technologies and the developing use cases of 5G-IoT.
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Boeding, Matthew, Michael Hempel, and Hamid Sharif. "End-to-End Framework for Identifying Vulnerabilities of Operational Technology Protocols and Their Implementations in Industrial IoT." Future Internet 17, no. 1 (2025): 34. https://doi.org/10.3390/fi17010034.
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The convergence of IT and OT networks has gained significant attention in recent years, facilitated by the increase in distributed computing capabilities, the widespread deployment of Internet of Things devices, and the adoption of Industrial Internet of Things. This convergence has led to a drastic increase in external access capabilities to previously air-gapped industrial systems for process control and monitoring. To meet the need for remote access to system information, protocols designed for the OT space were extended to allow IT networked communications. However, OT protocols often lack the rigor of cybersecurity capabilities that have become a critical characteristic of IT protocols. Furthermore, OT protocol implementations on individual devices can vary in performance, requiring the comprehensive evaluation of a device’s reliability and capabilities before installation into a critical infrastructure production network. In this paper, the authors define a framework for identifying vulnerabilities within these protocols and their on-device implementations, utilizing formal modeling, hardware in the loop-driven network emulation, and fully virtual network scenario simulation. Initially, protocol specifications are modeled to identify any vulnerable states within the protocol, leveraging the Construction and Analysis of Distributed Processes (CADP) software (version 2022-d “Kista”, which was created by Inria, the French Institute for Research in Computer Science and Automation, in France). Device characteristics are then extracted through automated real-time network emulation tests built on the OMNET++ framework, and all measured device characteristics are then used as a virtual device representation for network simulation tests within the OMNET++ software (version 6.0.1., a public-soucre, open-architecture software, initially developed by OpenSim Limited in Budapest, Hungary), to verify the presence of any potential vulnerabilities identified in the formal modeling stage. With this framework, the authors have thus defined an end-to-end process to identify and verify the presence and impact of potential vulnerabilities within a protocol, as shown by the presented results. Furthermore, this framework can test protocol compliance, performance, and security in a controlled environment before deploying devices in live production networks and addressing cybersecurity concerns.
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Pesch, Alexander, and Peter Scavelli. "Condition Monitoring of Active Magnetic Bearings on the Internet of Things." Actuators 8, no. 1 (2019): 17. http://dx.doi.org/10.3390/act8010017.
Full textAbstract:
A magnetic bearing is an industrial device that supports a rotating shaft with a magnetic field. Magnetic bearings have advantages such as high efficiency, low maintenance, and no lubrication. Active magnetic bearings (AMBs) use electromagnets with actively controlled coil currents based on rotor position monitored by sensors integral to the AMB. AMBs are apt to the Internet of Things (IoT) due to their inherent sensors and actuators. The IoT is the interconnection of physical devices that enables them to send and receive data over the Internet. IoT technology has recently rapidly increased and is being applied to industrial devices. This study developed a method for the condition monitoring of AMB systems online using off-the-shelf IoT technology. Because off-the-shelf IoT solutions were utilized, the developed method is cost-effective and can be implemented on existing AMB systems. In this study, a MBC500 AMB test rig was outfitted with a Raspberry Pi single board computer. The Raspberry Pi monitors the AMB’s position sensors and current sensors via an analog-to-digital converter. Several loading cases were imposed on the experimental test rig and diagnosed remotely using virtual network computing. It was found that remote AMB condition monitoring is feasible for less than USD 100.
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Sandrine, Emvoutou Ndongo, Mbihi Jean, Thérèse Ngo Bissé Jacquie, and Nguemgne Malongte Célestine. "IoT Instrumentation Device for Digital Data Acquisition and Remote Virtual Monitoring of Ionizing Radiations in Radiology and Medical Imaging Media." European Journal of Advances in Engineering and Technology 10, no. 2 (2023): 1–8. https://doi.org/10.5281/zenodo.10634972.
Full textAbstract:
<strong>ABSTRACT </strong> This paper presents a new remote virtual instrumentation device for ionize ng radiations in IoT radiology and medical imaging media. The main parts used in the local medical medium consists of: an ionizing radiation sensor (GB51 component), an ESP32-Based core for DSP (Data Signal Acquisition) and WiFi server, and a 4G WiFi modem. In the remote side, a Labview virtual monitoring system is used for the visualization and analysis of received ionizing radiation data. A sample of experimental results obtained and visualized on the remote Labview monitor screen, show the feasibility and high quality of the proposed innovative instrumentation device, dedicated to radiology and medical imaging media.
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Hovakimyan, Anna, Siranush Sargsyan, Tatev Hovakimjan, and Vahagn Aleksanyan. "Remote Health Monitoring System for Patients." Information Theories and Applications 30, no. 1 (2023): 29–48. http://dx.doi.org/10.54521/ijita30-01-p06.
Full textAbstract:
In this paper, we introduce the Virtual Clinic, a hardware and software system that enables patients and doctors to communicate remotely. To utilize the system, patients must have a wearable medical device and a mobile phone, while doctors require access to a computer device. The Virtual Clinic allows for the quick exchange of vital data and messages between patients and doctors, and even employs machine learning techniques to diagnose diseases automatically. This system provides the opportunity to use telemedicine and telehealth concepts to remotely monitor a patient's health, offer personalized health services, manage drug treatments, handle chronic illnesses, provide psychological services, give second opinions, collaborate on treatments, and quickly respond to emergencies. Our Virtual Clinic system, which utilizes IoT, network, and cloud technologies, is a versatile tool suitable for individuals, medical clinics and trainers alike.