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Journal articles on the topic 'Internet of Objects'
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1
Suryani, Vera, Selo Sulistyo, and Widyawan Widyawan. "Trust-Based Privacy for Internet of Things." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (October 1, 2016): 2396. http://dx.doi.org/10.11591/ijece.v6i5.9678.
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<p>Internet of Things or widely known as IOT makes smart objects become active participants in the communication process between objects and their environment. IoT services that utilize Internet connection require solutions to a new problem: security and privacy. Smart objects and machine-to-machine communications in IOT now become interesting research, including that related to security. Privacy, which is a safe condition in which object is free from interference from other objects, is one of the important aspects in IOT. Privacy can be implemented using various ways for examples by applying encryption algorithms, restrictions on access to data or users, as well as implementing rules or specific policy. Trustable object selection is one technique to improve privacy. The process of selecting a trustable object can be done based on past activities or trust history of the object, also by applying a threshold value to determine whether an object is "trusted" or not. Some researchers have studied this approach. In this study, the selection processes of trustable objects are calculated using Modified Ant Colony algorithm. The simulation was performed and resulted in declining graphic trend but stabilized in certain trust value.</p>
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Suryani, Vera, Selo Sulistyo, and Widyawan Widyawan. "Trust-Based Privacy for Internet of Things." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 5 (October 1, 2016): 2396. http://dx.doi.org/10.11591/ijece.v6i5.pp2396-2402.
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<p>Internet of Things or widely known as IOT makes smart objects become active participants in the communication process between objects and their environment. IoT services that utilize Internet connection require solutions to a new problem: security and privacy. Smart objects and machine-to-machine communications in IOT now become interesting research, including that related to security. Privacy, which is a safe condition in which object is free from interference from other objects, is one of the important aspects in IOT. Privacy can be implemented using various ways for examples by applying encryption algorithms, restrictions on access to data or users, as well as implementing rules or specific policy. Trustable object selection is one technique to improve privacy. The process of selecting a trustable object can be done based on past activities or trust history of the object, also by applying a threshold value to determine whether an object is "trusted" or not. Some researchers have studied this approach. In this study, the selection processes of trustable objects are calculated using Modified Ant Colony algorithm. The simulation was performed and resulted in declining graphic trend but stabilized in certain trust value.</p>
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Wei, Dawei, Huansheng Ning, Yuke Qian, and Tao Zhu. "Social relationship for physical objects." International Journal of Distributed Sensor Networks 14, no. 1 (January 2018): 155014771875496. http://dx.doi.org/10.1177/1550147718754968.
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To apply the algorithms in Internet of Things for physical world objects, the relationship between physical objects is becoming more and more complicated. As we know, social relationship is widely used in human world and social Internet of Things to solve the multiple object problems. Thus, a way via combining social relationship with physical object to solve the problem with a huge number of objects or complicated interactions among objects has been analyzed. This article proposes a new concept of “Physical Objects’ Social Relationship” for describing, managing, and predicting the relationships between physical objects in Internet of Things. The classification method for physical objects’ social relationships is proposed using the spatial-temporal attribute of social relationships. Moreover, the logical expression method for physical objects’ social relationships is discussed.
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Milivojević, Sanja, and Elizabeth Radulski. "The 'Future Internet' and crime: Towards a criminology of the Internet of Things." Crimen 11, no. 3 (2020): 255–71. http://dx.doi.org/10.5937/crimen2003255m.
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The Internet of Things (IoT) is poised to revolutionise the way we live and communicate, and the manner in which we engage with our social and natural world. In the IoT, objects such as household items, vending machines and cars have the ability to sense and share data with other things, via wireless, Bluetooth, or Radio Frequency IDentification (RFID) technology. "Smart things" have the capability to control their performance, as well as our experiences and decisions. In this exploratory paper, we overview recent developments in the IoT technology, and their relevance for criminology. Our aim is to partially fill the gap in the literature, by flagging emerging issues criminologists and social scientists ought to engage with in the future. The focus is exclusively on the IoT while other advances, such as facial recognition technology, are only lightly touched upon. This paper, thus, serves as a starting point in the conversation, as we invite scholars to join us in forecasting-if not preventing-the unwanted consequences of the "future Internet".
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Chen, Yuanyi, Yanyun Tao, Zengwei Zheng, and Dan Chen. "Graph-based service recommendation in Social Internet of Things." International Journal of Distributed Sensor Networks 17, no. 4 (April 2021): 155014772110090. http://dx.doi.org/10.1177/15501477211009047.
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While it is well understood that the emerging Social Internet of Things offers the capability of effectively integrating and managing massive heterogeneous IoT objects, it also presents new challenges for suggesting useful objects with certain service for users due to complex relationships in Social Internet of Things, such as user’s object usage pattern and various social relationships among Social Internet of Things objects. In this study, we focus on the problem of service recommendation in Social Internet of Things, which is very important for many applications such as urban computing, smart cities, and health care. We propose a graph-based service recommendation framework by jointly considering social relationships of heterogeneous objects in Social Internet of Things and user’s preferences. More exactly, we learn user’s preference from his or her object usage events with a latent variable model. Then, we model users, objects, and their relationships with a knowledge graph and regard Social Internet of Things service recommendation as a knowledge graph completion problem, where the “like” property that connects users to services needs to be predicted. To demonstrate the utility of the proposed model, we have built a Social Internet of Things testbed to validate our approach and the experimental results demonstrate its feasibility and effectiveness.
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Liu, Zhiting, and Zhiliang Xia. "A broken window escape device based on Internet of Things technology." Journal of Computing and Electronic Information Management 10, no. 1 (February 22, 2023): 64–67. http://dx.doi.org/10.54097/jceim.v10i1.5423.
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The window breaker used for escape consists of a tray used to secure the lower layer of the fragile surface of the glass, a supporting part used to knock the broken object to make it deformed and support the lifting of the object, and a part used to knock the broken object is set on the bottom tray. The outer packaging shell includes the outer packaging shell that protects the bottom tray from the contact of objects. The outer packaging shell is assembled with the bottom tray. The outer packaging shell has the parts that support the lifting and the parts that are used to knock the broken objects to separate the pressing part. When the pressing part is deformed, the parts that support the lifting and the parts that are used to knock the broken objects are compressed and separated from the parts that are used to knock the broken objects, and the elastic restoring force formed by the broken objects to break the glass, It is used to separate the parts supporting the lifting of objects from the parts used to knock broken objects. This product can be fixed with the broken window and the point where the glass is knocked in an emergency. It will not harm the human body and achieve the purpose of escape. This tool is simple in structure, strong in safety and practical.
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Prima, Wandynata, and Yo Ceng Giap. "Object Detection Radar Prototype with Ultrasonic Sensor Using Iot-Based Arduino." bit-Tech 3, no. 2 (April 18, 2021): 81–88. http://dx.doi.org/10.32877/bt.v3i2.187.
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Internet of Things (IoT) is a concept that aims to expand the benefits of connected internet connectivity. Internet of Things (IoT) refers to objects that are uniquely identified as virtual reservations in an internet-based structure. At this time, the limitation of surveillance control in observing objects as negligence of the limitation of view, light conditions or obstructions becomes a problem in application and monitoring. The use of radar is one solution to overcome this condition. Radar stands for radio detection and range is a device whose function is to determine the distance, direction, or speed of a moving and fixed object. Radar can be used in mapping applications and exploration of objects in unknown space. The use of radar can also help navigate moving objects. In this study, a radar prototype with ultrasonic sensors and a simcard module was made that can provide notification via SMS if an object is near the radar. It is hoped that this radar prototype can be used to identify the location of the presence of obstructive objects in rooms with limited access or in dangerous areas
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Aldelaimi, Monira N., M. Anwar Hossain, and Mohammed F. Alhamid. "Building Dynamic Communities of Interest for Internet of Things in Smart Cities." Sensors 20, no. 10 (May 25, 2020): 2986. http://dx.doi.org/10.3390/s20102986.
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The Internet of things (IoT) is a growing area of research in the context of smart cities. It links a city’s physical objects that are equipped with embedded sensing, communicating, and computing technology. These objects possess the capability to connect and share data with minimal human intervention, which creates the potential to establish social relationships among them. However, it is challenging for an object to discover, communicate, and collaborate dynamically with other objects, such as social entities, and provide services to humans. This is due to the increase in the number of objects and the complexity in defining social-like relationships among them. The current research aims to address this by introducing an object architecture and defining a Dynamic Community of Interest Model (DCIM) for IoT objects. The proposed model will help IoT objects to socialize and build communities amongst themselves based on different criteria. In this approach, objects belonging to a community will collaborate with each other to collect, manipulate, and share interesting content and provide services to enhance the quality of human interactions in smart cities.
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Smoliak, D. S., S. N. Petrov, and T. A. Pulko. "MONITORING OF INTERNET-FACING TECHNOGENIC OBJECTS." Doklady BGUIR, no. 6 (October 3, 2019): 80–86. http://dx.doi.org/10.35596/1729-7648-2019-124-6-80-86.
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The approach to detection and monitoring of Internet-facing technogenic objects has been described. The method of analysis of public services Shodan and Censys has been proposed. The automation monitoring software has been developed.
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Miller, Eric J. "Visualizing Spatial Relationships Between Internet Objects." Journal of Library Administration 34, no. 1-2 (December 2001): 171–77. http://dx.doi.org/10.1300/j111v34n01_26.
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S. D., Mohana, S. P. Shiva Prakash, and Kirill Krinkin. "Service Oriented R-ANN Knowledge Model for Social Internet of Things." Big Data and Cognitive Computing 6, no. 1 (March 18, 2022): 32. http://dx.doi.org/10.3390/bdcc6010032.
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Increase in technologies around the world requires adding intelligence to the objects, and making it a smart object in an environment leads to the Social Internet of Things (SIoT). These social objects are uniquely identifiable, transferable and share information from user-to-objects and objects-to objects through interactions in a smart environment such as smart homes, smart cities and many more applications. SIoT faces certain challenges such as handling of heterogeneous objects, selection of generated data in objects, missing values in data. Therefore, the discovery and communication of meaningful patterns in data are more important for every application. Thus, the analysis of data is essential in smarter decisions and qualifies performance of data for various applications. In a smart environment, social networks of intelligent objects are increasing services and decreasing the relationship in a reliable and efficient way of sharing resources and services. Hence, this work proposed the feature selection method based on proposed semantic rules and established the relationships to classify the services using relationship artificial neural networks (R-ANN). R-ANN is an inversely proportional relationship to the objects based on certain rules and conditions between the objects to objects and users to objects. It provides the service oriented knowledge model to make decisions in the proposed R-ANN model that produces service to the users. The proposed R-ANN provides an accuracy of 89.62% for various services namely weather, air quality, parking, light status, and people presence respectively in the SIoT environment compared to the existing model.
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Kumar, Malay, Dr Anant Kumar Sinha, and Dr Narendra Kumar. "Literature Review of Smart and Precision Agriculture by Applying IOT Module." International Journal for Research in Applied Science and Engineering Technology, no. 9 (September 30, 2022): 791–95. http://dx.doi.org/10.22214/ijraset.2022.46688.
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Abstract: The hottest topic in the internet industry is the Internet of Things. The IOT is a term used to describe a network of physical objects or things that may communicate with one another while still being connected to the Internet and are equipped with sensing, actuating, and computing capabilities. The concept of a smart object is made possible by embedded microcontrollers, actuators, and sensors. Wherein these intelligent objects gather data from the development environment, process it, and carry out the necessary actions. As a result, the Internet of Things will offer previously unthinkable advantages and assist people in living affluent, sophisticated lives.
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Hoffman, Donna L., and Thomas P. Novak. "Consumer and Object Experience in the Internet of Things: An Assemblage Theory Approach." Journal of Consumer Research 44, no. 6 (October 6, 2017): 1178–204. http://dx.doi.org/10.1093/jcr/ucx105.
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Abstract The consumer Internet of Things (IoT) has the potential to revolutionize consumer experience. Because consumers can actively interact with smart objects, the traditional, human-centric conceptualization of consumer experience as consumers’ internal subjective responses to branded objects may not be sufficient to conceptualize consumer experience in the IoT. Smart objects possess their own unique capacities and their own kinds of experiences in interaction with the consumer and each other. A conceptual framework based on assemblage theory and object-oriented ontology details how consumer experience and object experience emerge in the IoT. This conceptualization is anchored in the context of consumer-object assemblages, and defines consumer experience by its emergent properties, capacities, and agentic and communal roles expressed in interaction. Four specific consumer experience assemblages emerge: enabling experiences, comprising agentic self-extension and communal self-expansion, and constraining experiences, comprising agentic self-restriction and communal self-reduction. A parallel conceptualization of the construct of object experience argues that it can be accessed by consumers through object-oriented anthropomorphism, a nonhuman-centric approach to evaluating the expressive roles objects play in interaction. Directions for future research are derived, and consumer researchers are invited to join a dialogue about the important themes underlying our framework.
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Dinh, Ngoc-Thanh, and Young-Han Kim. "An Efficient Correlation-Based Cache Retrieval Scheme at the Edge for Internet of Things." Sensors 20, no. 23 (November 30, 2020): 6846. http://dx.doi.org/10.3390/s20236846.
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Existing caching mechanisms considers content objects individually without considering the semantic correlation among content objects. We argue that this approach can be inefficient in Internet of Things due to the highly redundant nature of IoT device deployments and the data accuracy tolerance of IoT applications. In many IoT applications, an approximate answer is acceptable. Therefore, a cache of an information object having a high semantic correlation with the requested information object can be used instead of a cache of the exact requested information object. In this case, caching both of the information objects can be inefficient and redundant. This paper proposes a caching retrieval scheme which considers the semantic information correlation of information objects of nodes for cache retrieval. We illustrate the benefits of considering the semantic information correlation in caching by studying IoT data caching at the edge. Our experiments and analysis show that semantic correlated caching can significantly improve the efficiency, cache hit, and reduce the resource consumption of IoT devices.
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Elhaloui, Loubna, Sanaa El Filali, El Habib Benlahmer, Mohamed Tabaa, Youness Tace, and Nouha Rida. "Machine learning for internet of things classification using network traffic parameters." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 3 (June 1, 2023): 3449. http://dx.doi.org/10.11591/ijece.v13i3.pp3449-3463.
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With the growth of the internet of things (IoT) smart objects, managing these objects becomes a very important challenge, to know the total number of interconnected objects on a heterogeneous network, and if they are functioning correctly; the use of IoT objects can have advantages in terms of comfort, efficiency, and cost. In this context, the identification of IoT objects is the first step to help owners manage them and ensure the security of their IoT environments such as smart homes, smart buildings, or smart cities. In this paper, to meet the need for IoT object identification, we have deployed an intelligent environment to collect all network traffic traces based on a diverse list of IoT in real-time conditions. In the exploratory phase of this traffic, we have developed learning models capable of identifying and classifying connected IoT objects in our environment. We have applied the six supervised machine learning algorithms: support vector machine, decision tree (DT), random forest (RF), k-nearest neighbors, naive Bayes, and stochastic gradient descent classifier. Finally, the experimental results indicate that the DT and RF models proved to be the most effective and demonstrate an accuracy of 97.72% on the analysis of network traffic data and more particularly information contained in network protocols. Most IoT objects are identified and classified with an accuracy of 99.21%.
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Pascual Espada, Jordán, Oscar Sanjuán Martínez, B. Cristina Pelayo G-Bustelo, and Juan Manuel Cueva Lovelle. "Virtual Objects on the Internet of Things." International Journal of Interactive Multimedia and Artificial Intelligence 1, no. 4 (2011): 23. http://dx.doi.org/10.9781/ijimai.2011.144.
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Blagov, A. A. "COMMERCIALIZATION OF COPYRIGHT OBJECTS ON THE INTERNET." Международный студенческий научный вестник (International Student Scientific Herald), no. 6 2022 (2022): 13. http://dx.doi.org/10.17513/msnv.21018.
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Stanescu, Aurelian, Mihnea Alexandru Moisescu, and Ioan Stefan Sacala. "Towards the Development of Internet of Things Oriented Robot to Object Interaction Framework." Advanced Materials Research 463-464 (February 2012): 1321–23. http://dx.doi.org/10.4028/www.scientific.net/amr.463-464.1321.
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The main objectives of this paper are to provide an overview of the current progress of Internet of Things oriented technologies and to propose a framework which will enable the transformation of real world objects into intelligent virtual objects and allow for a simplified robot to object interaction.
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Chalasani Srinivas, Dr, Dr Srinivas Malladi, and . "A Light Protocol for Tracking Secure Stuff for the Internet of Things." International Journal of Engineering & Technology 7, no. 2.32 (May 31, 2018): 121. http://dx.doi.org/10.14419/ijet.v7i2.32.15384.
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The Internet of Things (IoT) is growing in the web of an age-old IPv6 address for Internet connections and messages that arise between these and other devices and systems that work with the Internet. It is equipped with the unique ID and data transfer capability through the network. Among other things, tracking and tracking online travel is a major issue. Although there are many tracking techniques for moving objects, many are at risk. So there is a need for tracking the safety of an object Safety protocols should provide visibility and tracking of street objects in support of the Internet (IoT). This protocol is based on the RFID Identity System for IoT Objects. Existing ones do not provide authentication of sites that lead to fakes. Great use of energy. The proposed protocol improves road safety tracking using the base protocol light and SPDL. The requested protocol is intended to ensure accuracy, accuracy, confidentiality and encryption. To ensure safe monitoring of objects, the requested protocols use cryptic primitives that use HMAC concepts that are used to authenticate an object. This protocol introduction relies on code authentication code (CMC), which is used to reduce power consumption at low cost. The testing of a test network evaluates protocol implementation and is found to be safer and requires less calculation than existing protocols.
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Chalasani Srinivas, Dr, and Dr Srinivas Malladi. "A light protocol for tracking secure stuff for the internet of things." International Journal of Engineering & Technology 7, no. 3 (July 11, 2018): 1491. http://dx.doi.org/10.14419/ijet.v7i3.11254.
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The Internet of Things (IoT) is growing in the web of an age-old IPv6 address for Internet connections and messages that arise between these and other devices and systems that work with the Internet. It is equipped with the unique ID and data transfer capability through the network. Among other things, tracking and tracking online travel is a major issue. Although there are many tracking techniques for moving objects, many are at risk. So there is a need for tracking the safety of an object Safety protocols should provide visibility and tracking of street objects in support of the Internet (IoT). This protocol is based on the RFID Identity System for IoT Objects. Existing ones do not provide authentication of sites that lead to fakes. Great use of energy. The proposed protocol improves road safety tracking using the base protocol light and SPDL. The requested protocol is intended to ensure accuracy, accuracy, confidentiality and encryption. To ensure safe monitoring of objects, the requested protocols use cryptic primitives that use HMAC concepts that are used to authenticate an object. This protocol introduction relies on code authentication code (CMC), which is used to reduce power consumption at low cost. The testing of a test network evaluates protocol implementation and is found to be safer and requires less calculation than existing protocols.
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SEHNALOVÁ, Vladimíra. "LEARNING OBJECTS AND THEIR RESOURCES ON THE INTERNET." Journal of Technology and Information 1, no. 3 (December 1, 2009): 126–30. http://dx.doi.org/10.5507/jtie.2009.072.
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MA, JIANHUA, RUNHE HUANG, and RYOUHEI NAKATANI. "TOWARDS A NATURAL INTERNET-BASED COLLABORATIVE ENVIRONMENT WITH SUPPORT OF OBJECT PHYSICAL AND SOCIAL CHARACTERISTICS." International Journal of Software Engineering and Knowledge Engineering 11, no. 01 (February 2001): 37–53. http://dx.doi.org/10.1142/s0218194001000402.
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Objects in this article refer to sharable applications, such as a whiteboard and a video player, used by multi-users who are in different sites and have computers connected to networks. The objects are important elements in our Internet-based desktop collaborative system, called virtual collaboration room (VCR). We argue that a natural collaborative environment should be developed in a framework of using both a room metaphor and an object metaphor, i.e., emulating the fundamental characteristics of real rooms and real objects, respectively. This article gives the first systematic specifications of object physical and social characteristics, and discusses how to exploit and implement the object characteristics in VCR. A preliminary prototype of platform independent real-time audio/video communications among multiple users is also described. It can be used together with VCR.
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Wang, Hong Xiang, and H. B. Xu. "A Reliability Research on Internet of Objects Monitoring System of Facility Agriculture." Key Engineering Materials 693 (May 2016): 1486–91. http://dx.doi.org/10.4028/www.scientific.net/kem.693.1486.
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To solve the low transmission reliability in Internet of Objects monitoring system of facility agriculture, this study discussed the influences of transmission reliability in Internet of Objects. Meanwhile, the factors influencing transmission reliability of Internet of Objects were analyzed. Then, based on the results obtained, corresponding solutions were proposed. This research plays a guidance role in further improvement of reliability and function management level in Internet of Objects monitoring system.
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Băjenescu, Titu-Marius I. "INTERNET OF THINGS (IOT) CONQUERS THE WHOLE GLOBE." Journal of Social Sciences IV, no. 2 (May 2021): 107–16. http://dx.doi.org/10.52326/jss.utm.2021.4(2).11.
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The article examines the market for connected objects, which is gradually taking its place in the global economy. Autonomous cars, smartphones, video surveillance, connected objects are already present in our daily lives. However, it is in industry that the Internet of Things has developed the most. The Internet of Things, or IoT, is a concept defining the extension of the Internet to physical objects. This includes not only the connected objects, but also the sensors, software and network through which these objects operate. All connected objects are powered by software, which collects data - that are then processed in the cloud. They are, therefore, programmed and programmable objects that can interact via a WiFi, Bluetooth or 4G connection. Connected objects can be found in two main applications: an industrial application and an everyday application. In the industrial sector, connected objects are very well established in various sectors of activity: automotive, aeronautics, agriculture, health, commerce, public sector, logistics, etc. Everyday applications, known as consumer applications, are struggling to develop despite the announced Eldorado. Even though many connected everyday objects exist (toothbrushes, hoovers, watches, home automation, etc.), the business model is having trouble being set up and connected objects are having trouble proving their usefulness in everyday life. There needs to be consistency and logic in the range of connected products on offer and not just a range of independent products.
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Susanto, Fredy, Ni Komang Prasiani, and Putu Darmawan. "IMPLEMENTASI INTERNET OF THINGS DALAM KEHIDUPAN SEHARI-HARI." Jurnal Imagine 2, no. 1 (April 21, 2022): 35–40. http://dx.doi.org/10.35886/imagine.v2i1.329.
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ABSTRACT
Internet of Things or abbreviated as IoT is a technology that innovates surrounding objects with the internet so that daily activities become easier and more efficient. The Internet of Things is a technology that allows objects around us to be connected to the Internet. The importance of the Internet of Things can be seen with the increasing number of applications in various lines of life today. IoT gives us many ideas to participate in various aspects of development ranging from micro to macro around the world. The internet of things has made it a separate field of research since the development of internet technology (IT) and other communication media. The methodology used in the development of IoT is of various kinds. From the real time system to the use of the prototype flow. The more human needs about technology are developing, the more research will be present, the internet of things is one of the thoughts of researchers who optimize several tools such as sensor media, Radio Frequency Identification (RFID), Wireless Sensor Networks and other Smart Objects that allow humans easy to interact with all equipment connected to the internet network.
Keywords: IoT, RFID, Wireless Sensor Network, Smart Object
ABSTRAK
Internet of Things atau disingkat dengan istilah IoT merupakan teknologi yang menginovasi benda-benda sekitar dengan internet agar aktivitas sehari-hari menjadi lebih mudah dan efisien. Internet of Things adalah teknologi yang memungkinkan benda-benda di sekitar kita terhubung dengan Internet. Pentingnya Internet of Things dapat dilihat dengan semakin banyaknya diterapkan dalam berbagai lini kehidupan saat ini. IoT memberikan kita banyak gagasan untuk turut berperan serta dalam berbagai segi perkembangan mulai dari hal mikro hingga makro di seluruh dunia. Internet of things menjadikannya sebuah bidang penelitian tersendiri sejak berkembangnya teknologi internet (IT) dan media komunikasi lain. Metodology yang yang digunakan dalam pengembangan IoT ini adalah berbagai macam. Dari yang real time system hingga penggunaan alur prototype. Semakin berkembang keperluan manusia tentang teknologi, maka semakin banyak penelitian yang akan hadir, internet of things adalah salah satu hasil pemikiran para peneliti yang mengoptimasi beberapa alat seperti media sensor, Radio Frequency Identification (RFID), Wireless Sensor Network serta Smart Object lain yang memungkinkan manusia mudah berinteraksi dengan semua peralatan yang terhubung dengan jaringan internet.
Kata kunci : IoT, RFID, Wireless Sensor Network, Smart Object
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Nikishin, V. D. "OBJECTS OF FORENSIC LINGUISTIC EXAMINATION: NEW CHALLENGES OF CRIMINOGENIC INTERNET COMMUNICATION." Courier of Kutafin Moscow State Law University (MSAL)), no. 6 (July 31, 2020): 79–88. http://dx.doi.org/10.17803/2311-5998.2020.70.6.079-088.
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The article is devoted to the system of objects of forensic linguistic examination at the present stage of its development. The relevance of the study is tied with the activation of criminogenic Internet communication, which implements defamatory, extremist and other aggressive speech acts that create threats to the information and worldview security of Web users. The essence of the object of forensic linguistic examination is considered from the following points of view: the theory of confl ict, the criminalistic understanding of the object of forensic examination as a complex three-link dynamic system, the concept of speech traces, the language form of the speech products, the material storage mediums, etc. Defi nitions of the diagnosed and diagnosing objects of the forensic linguistic examination are proposed. The article focuses on creolized and multicode texts, their multimodal perception. The correlation of speech traces of criminogenic Internet communication and digital traces is considered.
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Aldabbas, Omar Subhi. "Sensing as a Service for the Internet of Things." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 4, no. 3 (October 26, 2016): 28. http://dx.doi.org/10.3991/ijes.v4i3.6087.
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Internet of Things (IoT) is a ubiquitous embedded ecosystem known for its capability to perform common application functions through coordinating resources, which are distributed on-object or on-network domains. As new applications evolve, the challenge is in the analysis and usage of multimodal data streamed by diverse kinds of sensors. This paper presents a new service-centric approach for data collection and retrieval. This approach considers objects as highly decentralized, composite and cost effective services. Such services can be constructed from objects located within close geographical proximity to retrieve spatio-temporal events from the gathered sensor data. To achieve this, we advocate Coordination languages and models to fuse multimodal, heterogeneous services through interfacing with every service to achieve the network objective according to the data they gather and analyze. In this paper we give an application scenario that illustrates the implementation of the coordination models to provision successful collaboration among IoT objects to retrieve information. The proposed solution reduced the communication delay before service composition by up to 43% and improved the target detection accuracy by up to 70%, while maintaining energy consumption 20% lower than its best rivals in the literature.
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Phupattanasilp, Pilaiwan, and Sheau-Ru Tong. "Augmented Reality in the Integrative Internet of Things (AR-IoT): Application for Precision Farming." Sustainability 11, no. 9 (May 9, 2019): 2658. http://dx.doi.org/10.3390/su11092658.
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Benefitted by the Internet of Things (IoT), visualization capabilities facilitate the improvement of precision farming, especially in dynamic indoor planting. However, conventional IoT data visualization is usually carried out in offsite and textual environments, i.e., text and number, which do not promote a user’s sensorial perception and interaction. This paper introduces the use of augmented reality (AR) as a support to IoT data visualization, called AR-IoT. The AR-IoT system superimposes IoT data directly onto real-world objects and enhances object interaction. As a case study, this system is applied to crop monitoring. Multi-camera, a non-destructive and low-cost imaging platform of the IoT, is connected to the internet and integrated into the system to measure the three-dimensional (3D) coordinates of objects. The relationships among accuracy, object coordinates, augmented information (e.g., virtual objects), and object interaction are investigated. The proposed system shows a great potential to integrate IoT data with AR resolution, which will effectively contribute to updating precision agricultural techniques in an environmentally sustainable manner.
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Ayoub, Amrani, Rafalia Najat, and Jaafar Abouchabaka. "An Overview on Security Schemes Based on Elliptic Curve for Cloud-Iot." JOURNAL OF ADVANCES IN NATURAL SCIENCES 5 (October 30, 2018): 352–61. http://dx.doi.org/10.24297/jns.v5i1.7861.
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The Internet of things appears as a solution in order to connect people around the world. With this concept of interconnection, sharing and dissemination of information between different physical objects. Many objects and services in different fields will be created, such as smart homes, e-health, transport and logistics that will make our everyday needs easier. The main characteristic of a connected object is that it must be identifiable, using technologies such as RFID (Radio-Frequency Identification), must interact with the environment by adding sensory techniques, and finally a connected object must be able to communicate with others. The evolution of Internet of things, increase the number of connected objects. Devices with sensors, generate a huge number of data. With this evolution, the big questions come! how can we control this big data? Cloud Computing a notion that is not newer than the IoT concept, but it's a revolution has steadily been gaining ground. It's a technology that offers to end users a great services in terms of storage, elasticity, analyzing data and other services . In this paper, we cite the benefits of integrating Cloud Computing and Internet of things to manage data provided by physical object and security difficulties that may have this convergence. We also present an overview of the security algorithms proposed in the literature, based on elliptic curves, in order to secure communication between smart objects and cloud computing.
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Jung, Jooik, Sejin Chun, Xiongnan Jin, and Kyong-Ho Lee. "Enabling smart objects discovery via constructing hypergraphs of heterogeneous IoT interactions." Journal of Information Science 44, no. 1 (October 1, 2016): 110–24. http://dx.doi.org/10.1177/0165551516674164.
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Recent advances in the Internet of Things (IoT) have led to the rise of a new paradigm: Social Internet of Things (SIoT). However, the new paradigm, as inspired by the idea that smart objects will soon have a certain degree of social consciousness, is still in its infant state for several reasons. Most of the related works are far from embracing the social aspects of smart objects and the dynamicity of inter-object social relations. Furthermore, there is yet to be a coherent structure for organising and managing IoT objects that elicit social-like features. To fully understand how and to what extent these objects mimic the behaviours of humans, we first model SIoT by scrutinising the distinct characteristics and structural facets of human-centric social networks. To elaborate, we describe the process of profiling the IoT objects that become social and classify various inter-object social relationships. Afterwards, a novel discovery mechanism, which utilises our hypergraph-based overlay network model, is proposed. To test the feasibility of the proposed approach, we have performed several experiments on our smart home automation demo box built with various sensors and actuators.
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Singh, Om Prakash, Ranjith Ranjith C. S, Karthik R., Sandeep Reddy, and Rashmi Soni. "Survey Report on Sending Data Securely using IOT Over Cloud." International Journal of Recent Technology and Applied Science 2, no. 1 (March 18, 2020): 75–80. http://dx.doi.org/10.36079/lamintang.ijortas-0201.76.
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Survey Report on Sending Data Securely using IOT Over Cloud
The Internet of Things (IOT) is the network of physical objects, computers, cars, houses, and other things embedded with electronics, software, sensors, and network connectivity, allowing these objects to collect and exchange data. In the new technology market, IOT innovations is the next major step, but with the big difference that it brings about massive changes in business usability. A flare in the number of connected devices as well as placed locations is anticipated over the next few years and the functions that they will perform. Due to recent developments in networking and sensor technology, the Internet of Things (IoT) has grown rapidly. It seems very difficult to link that object together through the internet, but within a time frame, the internet of things will change our lives dramatically.
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KAHKONEN, JAAKKO, LASSI LEHTO, TIINA KILPELAINEN, and TAPANI SARJAKOSKI. "Interactive visualisation of geographical objects on the Internet." International Journal of Geographical Information Science 13, no. 4 (June 1999): 429–38. http://dx.doi.org/10.1080/136588199241292.
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Skipper, Robert Boyd. "Objects in Space As Metaphor for the Internet." Philosophy in the Contemporary World 9, no. 1 (2002): 83–88. http://dx.doi.org/10.5840/pcw2002919.
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Salhi, Dhai Eddine, Abelkamel Tari, and Mohand Tahar Kechadi. "Using Clustering for Forensics Analysis on Internet of Things." International Journal of Software Science and Computational Intelligence 13, no. 1 (January 2021): 56–71. http://dx.doi.org/10.4018/ijssci.2021010104.
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In the world of the internet of things (IoT), many connected objects generate an enormous amount of data. This data is used to analyze and make decisions about specific phenomena. If an object generates wrong data, it will influence the analysis of this collected data and the decision later. A forensics analysis is necessary to detect IoT nodes that are failing. This paper deals with a problem: the detection of these nodes, which generate erroneous data. The study starts to collect in a cloud computing server temperature measurements (the case study); using temperature sensors, the communication of the nodes is based on the HIP (host identity protocol). The detection is made using a data mining classification technique, in order to group the connected objects according to the collected measurements. At the end of the study, very good results were found, which opens the door to further studies.
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M., Duraipandian, and Vinothkanna R. "CLOUD BASED INTERNET OF THINGS FOR SMART CONNECTED OBJECTS." Journal of ISMAC 01, no. 02 (September 20, 2019): 31–39. http://dx.doi.org/10.36548/jismac.2019.2.004.
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The paper proposing the cloud based internet of things for the smart connected objects, concentrates on developing a smart home utilizing the internet of things, by providing the embedded labeling for all the tangible things at home and enabling them to be connected through the internet. The smart home proposed in the paper concentrates on the steps in reducing the electricity consumption of the appliances at the home by converting them into the smart connected objects using the cloud based internet of things and also concentrates on protecting the house from the theft and the robbery. The proposed smart home by turning the ordinary tangible objects into the smart connected objects shows considerable improvement in the energy consumption and the security provision.
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Lumbantoruan, Jitu Halomoan. "Evaluation of Students' Difficulties in Learning Mathematics in Complex Variable Material." Journal of Education Research and Evaluation 7, no. 3 (August 27, 2023): 443–54. http://dx.doi.org/10.23887/jere.v7i3.60532.
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Prospective mathematics teachers are required to be able to master facts and be able to give examples that exist in everyday life. A prospective mathematics teacher is expected to be skilled and mature in using media when operating, explaining and demonstrating direct objects that exist in any complex variable material. The aim of this study is to analyze the obstacles and difficulties of students in Mathematics. Two indicators for assessing mathematics learning outcomes: 1) Direct objects (Facts, Concepts, Skills, and Principles), and 2) Indirect objects (Internet and friends). Mixed methods research method. The subject of the complex variable mathematics course and the student object. Qualitative data collection techniques by observation, interviews, documentation and quantitative survey method collection techniques by distributing instruments. Analysis with, presentation, reduction, presenting bar charts, data synchronization and drawing conclusions. The findings, students' difficulties lie in the direct object, namely mastery of mathematical facts 95.55% and concept difficulties 91.11%, principle (formula) difficulties 91.11% and algorithms 75.55%. Students who get good grades online are assisted by indirect objects, namely the internet and other student discussion partners. In conclusion, students' obstacles and difficulties lie in the direct objects of fact indicators (definitions) and concepts. Material design, facts and concepts with group discussion models are learning solutions.
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Zhang, Zhichao, Hui Chen, Xiaoqing Yin, and Jinsheng Deng. "EAWNet: An Edge Attention-Wise Objector for Real-Time Visual Internet of Things." Wireless Communications and Mobile Computing 2021 (July 10, 2021): 1–15. http://dx.doi.org/10.1155/2021/7258649.
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With the upgrading of the high-performance image processing platform and visual internet of things sensors, VIOT is widely used in intelligent transportation, autopilot, military reconnaissance, public safety, and other fields. However, the outdoor visual internet of things system is very sensitive to the weather and unbalanced scale of latent object. The performance of supervised learning is often limited by the disturbance of abnormal data. It is difficult to collect all classes from limited historical instances. Therefore, in terms of the anomaly detection images, fast and accurate artificial intelligence-based object detection technology has become a research hot spot in the field of intelligent vision internet of things. To this end, we propose an efficient and accurate deep learning framework for real-time and dense object detection in VIOT named the Edge Attention-wise Convolutional Neural Network (EAWNet) with three main features. First, it can identify remote aerial and daily scenery objects fast and accurately in terms of an unbalanced category. Second, edge prior and rotated anchor are adopted to enhance the efficiency of detection in edge computing internet. Third, our EAWNet network uses an edge sensing object structure, makes full use of an attention mechanism to dynamically screen different kinds of objects, and performs target recognition on multiple scales. The edge recovery effect and target detection performance for long-distance aerial objects were significantly improved. We explore the efficiency of various architectures and fine tune the training process using various backbone and data enhancement strategies to increase the variety of the training data and overcome the size limitation of input images. Extensive experiments and comprehensive evaluation on COCO and large-scale DOTA datasets proved the effectiveness of this framework that achieved the most advanced performance in real-time VIOT object detection.
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Busanelli, Stefano, Simone Cirani, Lorenzo Melegari, Marco Picone, Mirco Rosa, and Luca Veltri. "A Sidecar Object for the Optimized Communication Between Edge and Cloud in Internet of Things Applications." Future Internet 11, no. 7 (July 5, 2019): 145. http://dx.doi.org/10.3390/fi11070145.
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The internet of things (IoT) is one of the most disrupting revolutions that is characterizing the technology ecosystem. In the near future, the IoT will have a significant impact on people’s lives and on the design and developments of new paradigms and architectures coping with a completely new set of challenges and service categories. The IoT can be described as an ecosystem where a massive number of constrained devices (denoted as smart objects) will be deployed and connected to cooperate for multiple purposes, such a data collection, actuation, and interaction with people. In order to meet the specific requirements, IoT services may be deployed leveraging a hybrid architecture that will involve services deployed on the edge and the cloud. In this context, one of the challenges is to create an infrastructure of objects and microservices operating between both the edge and in the cloud that can be easily updated and extended with new features and functionalities without the need of updating or re-deploying smart objects. This work introduces a new concept for extending smart objects’ support for cloud services, denoted as a sidecar object. A sidecar object serves the purpose of being deployed as additional component of a preexisting object without interfering with the mechanisms and behaviors that have already been implemented. In particular, the sidecar object implementation developed in this work focuses on the communication with existing IoT cloud services (namely, AWS IoT and Google Cloud IoT) to provide a transparent and seamless synchronization of data, states, and commands between the object on the edge and the cloud. The proposed sidecar object implementation has been extensively evaluated through a detailed set of tests, in order to analyze the performances and behaviors in real- world scenarios.
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Fahrianto, Feri. "Attendance Recognation by Using Smart Meter Based On IoT Study Case : FST UIN Jakarta." JURNAL TEKNIK INFORMATIKA 12, no. 1 (June 20, 2019): 109–20. http://dx.doi.org/10.15408/jti.v12i1.11043.
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State Islamic University Syarif Hidayatullah Jakarta as rapidly growing university toward world-class research university placed in the edge of Jakarta has academic information centre running by Pustipanda (The Center of Information Technology and Database). The acadmic information system (AIS) has been used for recording an academic activity in university for almost a decade, this information system has a functionality for detecting the lecturer attandancity, but the attendance system needs to be input by admin. In this research, the system to detect attendancity from lecturer is build and synchronize to universisty academic information system. Internet of Things, based on ITU-T 2015, some objects are able to transmit data among object by using Internet connection. It means by this technology the Internet used has been widely changed, from human to machine communication now also become machine-to-machine communications. By using this technology a small object or device is able to implement into electrical system to detect an activity occured in the room. Things implemented in the room are able to monitor which electronic device is active and motion of moving objects, also the position of objects. The communication connection between smart phones and acces point in the class room is also monitored in order to identify the lecturer identity.
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Aydos, Murat, Yılmaz Vural, and Adem Tekerek. "Assessing risks and threats with layered approach to Internet of Things security." Measurement and Control 52, no. 5-6 (April 12, 2019): 338–53. http://dx.doi.org/10.1177/0020294019837991.
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Internet of Things is the next-generation Internet network created by intelligent objects with software and sensors, employed in a wide range of fields such as automotive, construction, health, textile, education and transportation. With the advent of Industry 4.0, Internet of Things has been started to be used and it has led to the emergence of innovative business models. The processing and production capabilities of Internet of Things objects in hidden and critical data provide great advantages for the next generation of Internet. However, the integrated features of Internet of Things objects cause vulnerabilities in terms of security, making them the target of cyber threats. In this study, a security model which offers an integrated risk-based Internet of Things security approach for the Internet of Things vulnerabilities while providing detailed information about Internet of Things and the types of attacks targeting Internet of Things is proposed. In addition, in this study, the vulnerabilities of Internet of Things were explained by classifying attack types threatening the physical layer, network layer, data processing layer and application layer. Moreover, the risk-based security model has been proposed by examining the vulnerabilities and threats of smart objects that generate the Internet of Things. The proposed Internet of Things model is a holistic security model that separately evaluates the Internet of Things layers against vulnerabilities and threats based on the risk-level approach.
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Jang, Seok-Woo, and Sang-Hong Lee. "Robust Blocking of Human Faces with Personal Information Using Artificial Deep Neural Computing." Sustainability 12, no. 6 (March 18, 2020): 2373. http://dx.doi.org/10.3390/su12062373.
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High-speed wired and wireless Internet are one of the useful ways to acquire various types of media data easily. In this circumstance, people also can easily get media data including objects with exposed personal information through the Internet. Exposure of personal information emerges as a social issue. This paper proposes an effective blocking technique that makes it possible to robustly detect target objects with exposed personal information from various types of input images with the use of deep neural computing and to effectively block the detected objects’ regions. The proposed technique first utilizes the neural computing-based learning algorithm to robustly detect the target object including personal information from an image. It next generates a grid-type mosaic and lets the mosaic overlap the target object region detected in the previous step so as to effectively block the object region that includes personal information. Experimental results reveal that the proposed algorithm robustly detects the target object region with exposed personal information from a variety of input images and effectively blocks the detected region through grid-type mosaic processing. The object blocking technique proposed in this paper is expected to be applied to various application fields such as image security, sustainable anticipatory computing, object tracking, and target blocking.
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Esmaeili, Mohammad. "The Goals of Data Storage According to the Needs of Different Smart Systems." Journal of IoT and Machine Learning 1, no. 2 (March 14, 2024): 8–12. http://dx.doi.org/10.48001/joitml.2024.128-12.
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In this century, with the significant growth and improvement of information technology and the emergence of the Internet of Things (IoT), Big Data, and Cloud Computing, the daily lives of people have taken on a different model. Considering that the role of the human agent has diminished and different objects communicate with each other by themselves in a planned and intelligent manner, and considering that every object can be considered a part of the Internet of Things and play its role in communication, and considering that communication at any time and in any place and by any object is one of the characteristics of the Internet of Things, so with the expansion of the Internet of Things, these communications will increase tremendously and as a result, a huge amount of data will be created. And it is exchanged between different objects. What will happen to this amount of data and what is the purpose of this data? Is not it better to save this data? In this article, we answer the above questions and address the goals of data storage according to the needs of different smart systems.
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Azevedo, Victor Antonio. "Geração internet das coisas." Diálogo com a Economia Criativa 1, no. 2 (October 11, 2016): 75. http://dx.doi.org/10.22398/2525-2828.1275-91.
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A Internet das Coisas visa conectar objetos aos indivíduos e aos outros objetos, unificando ainda mais os mundos físico e digital. Através dessa percepção esse estudo teve como objetivo conhecer os novos horizontes e desafios criados pela Internet das Coisas. Foram feitas pesquisas qualitativa e quantitativa para entender o comportamento de consumo e influências dos jovens brasileiros de 18 a 22 anos, denominados de Geração Internet das Coisas, em relação aos objetos inteligentes.Internet of Things GenerationAbstractThe Internet of Things aims to connect objects to individuals and to other objects, further unifying the physical and digital worlds. Using this concept, this study aimed to understand the new horizons and challenges created by the Internet of Things. A qualitative and quantitative research was conducted to understand the consumer behavior and influences of Brazilian youths aged 18 to 22 years, called the Internet of Things Generation, in relation to smart devices.
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Marinov, Val R. "Embedded Flexible Hybrid Electronics for the Internet of Things." International Symposium on Microelectronics 2015, no. 1 (October 1, 2015): 000006–13. http://dx.doi.org/10.4071/isom-2015-tp12.
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The Internet of Things (IoT) “things” are often times described as active or smart devices and objects augmented with sensing, processing, and network capabilities. These smart objects are in the heart of the IoT concept but they alone cannot realize the full potential of IoT. The most ubiquitous objects in the IoT ecosystem, those that reside at the lowest system level and interact with the higher-level smart object, are based on the passive RFID technology. In the form of wireless passive sensors these objects are found in smart packaging, they form the backbone of the structural health monitoring systems, they provide non-invasive and continuous monitoring of physiological parameters, etc. RFID capability is already added to everyday items in the physical form of adhesive “smart” labels, enabling them to become “citizens” of the IoT ecosystem, but this “add-on“ approach increases the implementation cost and oftentimes impacts negatively the host item's form factor and appearance. It also does very little in terms of security and counterfeit prevention. On the other hand, the key economic factor that drives the deployment of the IoT is the cost at the end points. Therefore, the future of the IoT depends on developing an ultra-low-cost technology solution that can mass-produce low cost, RFID-enabled IoT objects on flexible substrates, ready for integration into everyday items. In some cases, such as in intelligent packaging, these objects will be non-obstructive and seamlessly integrated in their hosts. This integration will minimize the cost of implementation and will provide an insurmountable barrier to counterfeiters as they will need access to sophisticated and capital-intensive technologies in order to be able to alter or replicate the product's embedded configuration. Presented are two disruptive processes for packaging of ultrathin flexible hybrid electronic systems with ICs as thin as 15–20 μm and as small as 250 μm per side. The first generation technology is a modification of the conventional pick-and-place technique and has been already demonstrated on a commercial-grade roll-to-roll assembly line with packaging rates exceeding 10,000 cph. The second generation technology uses a laser beam to scan and transfer ultrathin, ultra-small ICs for high-precision assembly onto various flexible and rigid substrates. It provides packaging rates significantly exceeding those of the conventional pick-and-place equipment. Reported are also results from integrating the resulting ultrathin flexible hybrid electronic devices into thin materials such as paper and plastics.
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Jiang, Linshan, Rui Tan, Xin Lou, and Guosheng Lin. "On Lightweight Privacy-preserving Collaborative Learning for Internet of Things by Independent Random Projections." ACM Transactions on Internet of Things 2, no. 2 (May 2021): 1–32. http://dx.doi.org/10.1145/3441303.
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The Internet of Things (IoT) will be a main data generation infrastructure for achieving better system intelligence. This article considers the design and implementation of a practical privacy-preserving collaborative learning scheme, in which a curious learning coordinator trains a better machine learning model based on the data samples contributed by a number of IoT objects, while the confidentiality of the raw forms of the training data is protected against the coordinator. Existing distributed machine learning and data encryption approaches incur significant computation and communication overhead, rendering them ill-suited for resource-constrained IoT objects. We study an approach that applies independent random projection at each IoT object to obfuscate data and trains a deep neural network at the coordinator based on the projected data from the IoT objects. This approach introduces light computation overhead to the IoT objects and moves most workload to the coordinator that can have sufficient computing resources. Although the independent projections performed by the IoT objects address the potential collusion between the curious coordinator and some compromised IoT objects, they significantly increase the complexity of the projected data. In this article, we leverage the superior learning capability of deep learning in capturing sophisticated patterns to maintain good learning performance. Extensive comparative evaluation shows that this approach outperforms other lightweight approaches that apply additive noisification for differential privacy and/or support vector machines for learning in the applications with light to moderate data pattern complexities.
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Rachita Sharma, Nikita Chaturvedi, Rajkumar Kaushik, Rohan Sharma,. "Application of Internet of Things." Tuijin Jishu/Journal of Propulsion Technology 44, no. 1 (November 24, 2023): 185–90. http://dx.doi.org/10.52783/tjjpt.v44.i1.2239.
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Today, there is a tremendous push towards modern technology throughout the world. Specialized companies, on the other hand, are experiencing a terrifying rush towards the Internet of objects, or the Internet of things, in information technology. This refers to the process of connecting objects to the Internet by installing hardware or software that gives them the intelligence to interact with one another and efficiently take part in all facets of daily life. To achieve their full potential, however, a number of obstacles and problems still need to be resolved, and they must be seen from a variety of angles. This review study's main objective is to give the reader a comprehensive analysis from a technological and sociological perspective.
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E, Umamaheswari, and Ajay Dm. "SCOPE OF INTERNET OF THINGS: A SURVEY." Asian Journal of Pharmaceutical and Clinical Research 10, no. 13 (April 1, 2017): 187. http://dx.doi.org/10.22159/ajpcr.2017.v10s1.19633.
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The advent of internet of things (IoT) has influenced and revolutionized the information systems and computing technologies. A computing conceptwhere physical objects used in daily life, will identify themselves by getting connected to the internet is called IoT. Physical objects embedded withelectronic, software, radio-frequency identification, sensors, actuators and smart objects converge with the internet to accumulate and share datain IoT. IoT is expected to bring in drastic changes and solutions to most of the daily problems in the real world. This paper explains in detail the keyconcepts of IoT, the applications of IoT, the challenges in establishing IoT. This work also explains in detail the future scope of IoT in different fields.
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Naderlou, Lida, Nigar Ismayilova, and Azar Feyziyev. "A REVIEW SIOT (SOCIAL INTERNET OF THINGS): TECHNIQUES, APPLICATIONS, CHALLENGES AND TRENDS." Azerbaijan Journal of High Performance Computing 5, no. 2 (December 31, 2022): 236–53. http://dx.doi.org/10.32010/26166127.2022.5.2.236.253.
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The social or human actions in the IoT platform derive the new paradigm in the IoT environment called the Social Internet of Things (SIoT). The Social Internet of Things is that part of an IoT capable of establishing social relationships with other objects concerning humans. SIoT attempts to moderate IoT challenges in scalability, trust, and resource discovery by taking a cue from social computing. In the IoT family, there is a subset of SIoT, a relatively recent concept. Moreover, a method of integrating IoT with social networking. SIoT is a simulation of human-to-human and object-to-object social networks where Humans are called intellectual and relational objects. They build their social network to accomplish shared objectives such as enhancing accessibility, success, and productivity and providing their needed services. This paper has extensively surveyed the SIoT (social Internet of things) for beginners involved in SIoT Studies. This paper gives you a clear view and ideas about SIoT's architecture, relationships, trust management, and applications and challenges implemented related to SIoT.
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Parsaei, Mohammad Reza, Ahmad Reza Parnian, Samaneh Miri Rostami, and Reza Javidan. "RPL LOAD BALANCING IN INTERNET OF THINGS." IIUM Engineering Journal 18, no. 2 (December 1, 2017): 137–50. http://dx.doi.org/10.31436/iiumej.v18i2.702.
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ABSTRACT:Â The wide address space provided by Internet Protocol version 6 (IPv6) lets any thing to be identified uniquely. consistency of the modified version of IPv6 protocol stack with smart objects, facilitated the Internet interconnection of the networks of smart objects and introduced Internet of things. A smart object is a small micro-electronic device that consists of a communication device, a small microprocessor and a sensor or an actuator. A network made of such devices is called low-power and lossy network. RPL routing protocol that is consistent to IPv6, is designed to be used in these kinds of networks. Load balancing is not considered in the RPL design process. Whenever RPL is used in large scale low-power and lossy networks some nodes will suffer from congestion and this problem severely degrades network performance. In this paper, we consider solutions provided to tackle RPL load balancing problems. Load balancing algorithms and protoclos are evaluated through simulation. We evaluate IETF RPL implementation and LB-RPL method with Contiki OS Java (COOJA) simulator. They are assessed comprehensively through metrics such as Packet delivery Ratio, Average End to End delay, and Gateway Throughput. LB-RPL improves RPL in terms of Packet delivery Ratio and throughput but increases Average End to End delay. Simulations results show that RPL load balancing needs extensive works to be performed yet.
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Chaturvedi, Rajnish Kumar, Dinesh Prasad Sahu, Manoj Kumar Tyagi, Manoj Diwakar, Prabhishek Singh, Achyut Shankar, and V. E. Sathishkumar. "Visual object detection using audio data." Journal of Physics: Conference Series 2664, no. 1 (December 1, 2023): 012006. http://dx.doi.org/10.1088/1742-6596/2664/1/012006.
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Abstract Nowadays Internet of Things (IoT) and Machine Learning (ML) are growing fields. One application of these two fields is object detection, which detects semantic objects using digital images and videos of classes like humans, vehicles, buildings, etc. Visual object detection systems are very effective and accurate due to the appearance information obtained from the cameras. But they face the problem of a limited Field of View. This paper aims to tackle this issue by using audio data to localize the object. A microphone is used to estimate the angular position of the object emitting the sound. Objects currently in the Field of View of a camera are detected and tracked using optical flow, but when they go out of the Field of View, the sound emitted by the object is used by the microphone to calculate the object‘s angular position. Once the angle is calculated, the camera is rotated in that direction. This thus ensures that the object can be located even if it goes out of frame. Once the object is located through IoT devices, we use ML to identify the person‘s face.