Journal articles on the topic 'Internet des objets social (IoT social)'
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1
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.
Abstract:
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".
2
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.
Abstract:
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.
3
Shin, Taehwan, and Jinsung Byun. "Design and Implementation of a Vehicle Social Enabler Based on Social Internet of Things." Mobile Information Systems 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/4102163.
Abstract:
In recent years, the combination of novel context-aware systems with the Internet of Things (IoT) has received great attention with the advances in network and context-awareness technologies. Various context-aware consumer electronics based on IoT for intelligent and personalized user-centric services have been introduced. However, although the paradigm of the IoT has evolved from smart objects into social objects, the existing context-aware systems have not reflected the changes in these paradigms well. Therefore, this paper proposes a social enabler (S-Enabler) in order to overcome this limitation. The S-Enabler plays an important role in converting the existing objects into social objects. This paper presents the middleware architecture and cooperation processes for a social IoT-based smart system. In this paper, the S-Enabler is designed to be applied to a vehicle and an energy saving service is introduced by using the S-Enabler. The proposed energy saving service can reduce energy consumption and fuel consumption based on social behaviors such as sharing or competition. The performance of the S-Enabler is discussed through a simple vehicle service scenario. The experimental results show that the S-Enabler reduced fuel consumption by up to 31.7%.
4
Gao, Yunpeng, and Nan Zhang. "Social Security and Privacy for Social IoT Polymorphic Value Set: A Solution to Inference Attacks on Social Networks." Security and Communication Networks 2019 (August 28, 2019): 1–16. http://dx.doi.org/10.1155/2019/5498375.
Abstract:
Social Internet of Things (SIoT) integrates social network schemes into Internet of Things (IoT), which provides opportunities for IoT objects to form social communities. Existing social network models have been adopted by SIoT paradigm. The wide distribution of IoT objects and openness of social networks, however, make it more challenging to preserve privacy of IoT users. In this paper, we present a novel framework that preserves privacy against inference attacks on social network data through ranked retrieval models. We propose PVS, a privacy-preserving framework that involves the design of polymorphic value sets and ranking functions. PVS enables polymorphism of private attributes by allowing them to respond to different queries in different ways. We begin this work by identifying two classes of adversaries, authenticity-ignorant adversary, and authenticity-knowledgeable adversary, based on their knowledge of the distribution of private attributes. Next, we define the measurement functions of utility loss and propose PVSV and PVST that preserve privacy against authenticity-ignorant and authenticity-knowledgeable adversaries, respectively. We take into account the utility loss of query results in the design of PVSV and PVST. Finally, we show that PVSV and PVST meet the privacy guarantee with acceptable utility loss in extensive experiments over real-world datasets.
5
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.
Abstract:
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.
6
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.
Abstract:
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.
7
Muhammad, Shad, Muneer Umar, Shafiullah Khan, A. Alrajeh, and A. Mohammed. "Honesty-Based Social Technique to Enhance Cooperation in Social Internet of Things." Applied Sciences 13, no. 5 (February 21, 2023): 2778. http://dx.doi.org/10.3390/app13052778.
Abstract:
The Social Internet of Things (SIoT) can be seen as integrating the social networking concept into the Internet of Things (IoT). Such networks enable different devices to form social relationships among themselves depending on pre-programmed rules and the preferences of their owners. When SIoT devices encounter one another on the spur of the moment, they seek out each other’s assistance. The connectivity of such smart objects reveals new horizons for innovative applications empowering objects with cognizance. This enables smart objects to socialize with each other based on mutual interests and social aspects. Trust building in social networks has provided a new perspective for providing services to providers based on relationships like human ones. However, the connected IoT nodes in the community may show a lack of interest in forwarding packets in the network communication to save their resources, such as battery, energy, bandwidth, and memory. This act of selfishness can highly degrade the performance of the network. To enhance the cooperation among nodes in the network a novel technique is needed to improve the performance of the network. In this article, we address the issue of the selfishness of the nodes through the formation of a credible community based on honesty. A social process is used to form communities and select heads in these communities. The selected community heads having social attributes prove effective in determining the social behavior of the nodes as honest or selfish. Unlike other schemes, the dishonest nodes are isolated in a separate domain, and they are given several chances to rejoin the community after increasing their honesty levels. The proposed social technique was simulated using MATLAB and compared with existing schemes to show its effectiveness. Our proposed technique outperforms the existing techniques in terms of throughput, overhead, packet delivery ratio (PDR), and packet-delivery latency.
8
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.
Abstract:
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.
9
Kilani, Rim, Ahmed Zouinkhi, Eddy Bajic, and Mohamed Naceur Abdelkrim. "A Socio-Inspired Methodology and Model for Advanced and Opportunistic Interactions between Industrial IoT Objects." Electronics 11, no. 8 (April 18, 2022): 1281. http://dx.doi.org/10.3390/electronics11081281.
Abstract:
The concept of the Internet of Things (IoT) is widely discussed. IoT is one of the emerging technologies that have caught the attention of many researchers. The increase in the number of exchanges of services between heterogeneous or homogeneous connected objects with the integration of social networking concepts gives rise to the concept of the Social Internet of Things (SIoT). The SIoT concept contributes to the evolution of interactions between industrial objects by improving deterministic mechanisms towards intelligent interactions. The integration of the SIoT concept into the Industrial Internet of Things (IIoT) gives rise to the Social Internet of Industrial Things (SIoIT) and plays an important role in improving system performance in Industry 4.0. In this article, we propose an innovative methodology and a model of socio-inspired interaction between industrial communicating objects inspired by sociological approaches. Thanks to this model, socialized industrial communicating objects form a community of objects, autonomously and dynamically, by exchanging messages to know each other perfectly, and service requests between objects are executed adaptively according to the principles of social interaction governed by socio-inspired strategies and conditions. The model is implemented, tested and validated in a Netlogo multi-agent system simulation environment.
10
Chukhno, Olga, Nadezhda Chukhno, Giuseppe Araniti, Claudia Campolo, Antonio Iera, and Antonella Molinaro. "Optimal Placement of Social Digital Twins in Edge IoT Networks." Sensors 20, no. 21 (October 30, 2020): 6181. http://dx.doi.org/10.3390/s20216181.
Abstract:
In next-generation Internet of Things (IoT) deployments, every object such as a wearable device, a smartphone, a vehicle, and even a sensor or an actuator will be provided with a digital counterpart (twin) with the aim of augmenting the physical object’s capabilities and acting on its behalf when interacting with third parties. Moreover, such objects can be able to interact and autonomously establish social relationships according to the Social Internet of Things (SIoT) paradigm. In such a context, the goal of this work is to provide an optimal solution for the social-aware placement of IoT digital twins (DTs) at the network edge, with the twofold aim of reducing the latency (i) between physical devices and corresponding DTs for efficient data exchange, and (ii) among DTs of friend devices to speed-up the service discovery and chaining procedures across the SIoT network. To this aim, we formulate the problem as a mixed-integer linear programming model taking into account limited computing resources in the edge cloud and social relationships among IoT devices.
11
Amin, Farhan, Awais Ahmad, and Gyu Sang Choi. "Towards Trust and Friendliness Approaches in the Social Internet of Things." Applied Sciences 9, no. 1 (January 4, 2019): 166. http://dx.doi.org/10.3390/app9010166.
Abstract:
The Internet of Things (IoT) is an interconnected network of heterogeneous entities, such as sensors and embedded devices. During the current era, a new field of research has emerged, referred to as the social IoT, which mainly includes social networking features. The social IoT refers to devices that are capable of creating interactions with each other to independently achieve a common goal. Based on the structure, the support of numerous applications, and networking services, the social IoT is preferred over the traditional IoT. However, aspects like the roles of users and network navigability are major challenges that provoke users’ fears of data disclosure and privacy violations. Thus, it is important to provide reliable data analyses by using trust- and friendliness-based properties. This study was designed because of the limited availability of information in this area. It is a classified catalog of trust- and friendliness-based approaches in the social IoT with important highlights of important constraints, such as scalability, adaptability, and suitable network structures (for instance, human-to-human and human-to-object). In addition, typical concerns like communities of interest and social contacts are discussed in detail, with particular emphasis on friendliness- and trust-based properties, such as service composition, social similarity, and integrated cloud services.
12
Zia, Kashif, Muhammad Shafi, and Umar Farooq. "Improving Recommendation Accuracy Using Social Network of Owners in Social Internet of Vehicles." Future Internet 12, no. 4 (April 16, 2020): 69. http://dx.doi.org/10.3390/fi12040069.
Abstract:
The latest manifestation of “all connected world" is the Internet of Things (IoT), and Internet of Vehicles (IoV) is one of the key examples of IoT these days. In Social IoV (SIoV), each vehicle is treated as a social object where it establishes and manages its own Social Network (SN). Incidentally, most of the SIoV research in the literature is related to proximity-based connectivity and interactions. In this paper, we bring people in the loop by incorporating their SNs. While emphasizing a recommendation scenario, in which vehicles may require recommendations from SNs of their owners (in addition to their own SIoV), we proposed an agent-based model of information sharing (for context-based recommendations) on a hypothetical population of smart vehicles. Some important hypotheses were tested using a realistic simulation setting. The simulation results reveal that a recommendation using weak ties is more valuable than a recommendation using strong ties in pure SIoV. The simulation results also demonstrate that recommendations using the most-connected person in the social network are not more valuable than recommendation using a random person in the social network. The model presented in this paper can be used to design a multi-scale recommendation system, which uses SIoV and a typical SN in combination.
13
Sittón-Candanedo, Inés, Ricardo S. Alonso, Óscar García, Lilia Muñoz, and Sara Rodríguez-González. "Edge Computing, IoT and Social Computing in Smart Energy Scenarios." Sensors 19, no. 15 (July 31, 2019): 3353. http://dx.doi.org/10.3390/s19153353.
Abstract:
The Internet of Things (IoT) has become one of the most widely research paradigms, having received much attention from the research community in the last few years. IoT is the paradigm that creates an internet-connected world, where all the everyday objects capture data from our environment and adapt it to our needs. However, the implementation of IoT is a challenging task and all the implementation scenarios require the use of different technologies and the emergence of new ones, such as Edge Computing (EC). EC allows for more secure and efficient data processing in real time, achieving better performance and results. Energy efficiency is one of the most interesting IoT scenarios. In this scenario sensors, actuators and smart devices interact to generate a large volume of data associated with energy consumption. This work proposes the use of an Edge-IoT platform and a Social Computing framework to build a system aimed to smart energy efficiency in a public building scenario. The system has been evaluated in a public building and the results make evident the notable benefits that come from applying Edge Computing to both energy efficiency scenarios and the framework itself. Those benefits included reduced data transfer from the IoT-Edge to the Cloud and reduced Cloud, computing and network resource costs.
14
Kazia, Esmeralda. "Machine learning for False Information Detection in Social Internet of Things." Fusion: Practice and Applications 10, no. 1 (2023): 38–77. http://dx.doi.org/10.54216/fpa.100103.
Abstract:
By capitalizing on object relationships and local navigability, the Social Internet of Things (SIoT) is one of the burgeoning paradigms that could solve the technical challenges of conventional IoT. Because of this paradigm's capacity to combine conventional IoT with social media, it is possible to create smart objects and services with greater utility than those created using conventional IoT infrastructures. In recent years, scholars have become interested in SIoT, leading to a plethora of works examining various mechanisms for providing services and technologies within this context. In this vein, we present a comprehensive review of recent research covering important aspects of SIoT. In this research, we give a detailed justification for the function of several machine learning paradigms and provide a practical application of hitherto unexamined concerns relating to erroneous data and other social IoT. First, we give a classification of false news detection approaches and an analysis of these techniques. Second, the potential uses for detecting fake news are examined at length, including how it might be applied to the areas of fake profile detection, traffic management, bullying detection, etc. We also suggested a detailed review of the possibilities of machine learning algorithms for detecting bogus news and intervening in social networks. In our paper, we introduce categories of fake news detection methods providing a comparison between these methods. After that, the promising applications for false news detection is extensively discussed in terms of fake account detection, bot detection, bullying detection, and security and privacy of SIoT. Also, the paper contains a discussion of the potential of machine learning approaches for fake news detection and interventions in SIoT networks along with the state-of-the-art challenges, opportunities, and future search prospects. This article seeks for aiding the readers and researchers in explaining the motive and role of the different machine learning paradigms to offer them a comprehensive realization for so far unexplored issues related to false information and other scenarios of SIoT networks.
15
Ali, Sajjad, Muhammad Golam Kibria, Muhammad Aslam Jarwar, Hoon Ki Lee, and Ilyoung Chong. "A Model of Socially Connected Web Objects for IoT Applications." Wireless Communications and Mobile Computing 2018 (2018): 1–20. http://dx.doi.org/10.1155/2018/6309509.
Abstract:
The Internet of Things (IoT) is evolving with the connected objects at an unprecedented rate, bringing about enormous opportunities for the future IoT applications as well as challenges. One of the major challenges is to handle the complexity generated by the interconnection of billions of objects. However, Social Internet of Things (SIoT), emerging from the conglomeration of IoT and social networks, has realized an efficient way to facilitate the development of complex future IoT applications. Nevertheless, to fully utilize the benefits of SIoT, a platform that can provide efficient services using social relations among heterogeneous objects is highly required. The web objects enabled IoT environment promotes SIoT features by enabling virtualization using virtual objects and supporting the modularity with microservices. To realize SIoT services, this article proposes an architecture that provides a foundation for the development of lightweight microservices based on socially connected web objects. To efficiently discover web objects and reduce the complexity of service provisioning processes, a social relationship model is presented. To realize the interoperable service operations, a semantic ontology model has been developed. Finally, to evaluate the proposed design, a prototype has been implemented based on a use case scenario.
16
Komarov, Mikhail, Nikita Konovalov, and Nikolay Kazantsev. "How Internet of Things Influences Human Behavior Building Social Web of Services via Agent-Based Approach." Foundations of Computing and Decision Sciences 41, no. 3 (September 1, 2016): 197–210. http://dx.doi.org/10.1515/fcds-2016-0012.
Abstract:
AbstractThe paper discovers potential human interactions with growing amount of internet of things (IoT) via proposed concept of Social Web of Services (classical social web with smart things - daily life objects connected to the internet). To investigate the impact of IoT on user behaviour patterns we modelled human-thing interactions using agent-based simulation (ABM). We have proved that under certain conditions SmartThings, connected to the IoT, are able to change patterns of Human behaviour. Results of this work predict our way of living in the era of caused by viral effects of IoT application (HCI and M2M connections), and could be used to foster business process management in the IoT era.
17
H. Dutton, William. "Putting things to work: social and policy challenges for the Internet of things." info 16, no. 3 (May 6, 2014): 1–21. http://dx.doi.org/10.1108/info-09-2013-0047.
Abstract:
Purpose – This paper aims to provide a critical assessment of the Internet of things (IoT) and the social and policy issues raised by its development. While the Internet will continue to become ever more central to everyday life and work, there is a new but complementary vision for an IoT, which will connect billions of objects – “things” like sensors, monitors, and radio-frequency identification devices – to the Internet at a scale that far outstrips use of the Internet as we know it, and will have enormous social and economic implications. Design/methodology/approach – It is based on a review of literature and emerging developments, including synthesis of a workshop and discussions within a special interest group on the IoT. Findings – Nations can harvest the potential of this wave of innovation not only for manufacturing but also for everyday life and work and the development of new information and services that will change the way we do things in many walks of life. However, its success is not inevitable. Technical visions will not lead inexorably to successful public and private infrastructures that support the vitality of an IoT and the quality of everyday life and work. In fact, the IoT could undermine such core values as privacy, equality, trust and individual choice if not designed, implemented and governed in appropriate ways. Research limitations/implications – There is a need for more multi-disciplinary research on the IoT. Practical implications – Policymakers and opinion formers need to understand the IoT and its implications. Social implications – If the right policies and business models are developed, the IoT will stimulate major social, economic and service innovations in the next years and decades. Originality/value – This paper pulls together discussions and literature from a social science perspective, as one means to enable more multidisciplinary studies of emerging developments.
18
Simon Wewoliamo Kuseh, Henry Nunoo-Mensah, Griffith Selorm Klogo, and Eric Tutu Tchao. "A Survey of Trust Management Schemes for Social Internet of Things." Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi 7, no. 1 (June 9, 2022): 48–58. http://dx.doi.org/10.25139/inform.v7i1.4567.
Abstract:
Social Internet of Things (SIoT) involves integrating social networking concepts in the Internet of Things (IoT) to enhance social interactions among IoT objects and users. SIoT is envisaged to provide adequate service selection and discovery. Trust is an essential factor whenever social concepts are discussed in communication networks. Trust usually leads to a mutual relationship between two parties (i.e., the trustor and trustee) where they both enjoy mutual benefits. For secure social relationships, Trust management (TM) is a crucial feature of SIoT. The primary aim of this work is to provide a comprehensive review of trust management proposals/schemes available for SIoT. Four main trust calculation algorithms for trust management were selected for this review, and they were examined in detail. The IEEE Xplore, Scopus, ResearchGate, and Google Scholar databases were searched for articles containing the terms "Trust aggregation approaches in IoT", and "Trust computation in SIoT" with a particular emphasis on works published between 2018 and 2021. The paper also discussed the pros and cons of each TM technique, trust metrics/features, contributions, and limitations of the state-of-the-art SIoT TM proposals in the literature. The paper further provides open issues and possible research directions for entry-level researchers in the domain of SIoT.
19
Kuseh, Simon Wewoliamo, Henry Nunoo-Mensah, Griffith Selorm Klogo, and Eric Tutu Tchao. "A Survey of Trust Management Schemes for Social Internet of Things." Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi 7, no. 1 (January 23, 2022): 48–58. http://dx.doi.org/10.25139/inform.v7i1.4284.
Abstract:
Social Internet of Things (SIoT) involves integrating social networking concepts in the Internet of Things (IoT) to enhance social interactions among IoT objects and users. SIoT is envisaged to provide adequate service selection and discovery. Trust is an essential factor whenever social concepts are discussed in communication networks. Trust usually leads to a mutual relationship between two parties (i.e., the trustor and trustee) where they both enjoy mutual benefits. For secure social relationships, Trust management (TM) is a crucial feature of SIoT. The primary aim of this work is to provide a comprehensive review of trust management proposals/schemes available for SIoT. Four main trust calculation algorithms for trust management were selected for this review, and they were examined in detail. The IEEE Xplore, Scopus, ResearchGate, and Google Scholar databases were searched for articles containing the terms "Trust aggregation approaches in IoT", and "Trust computation in SIoT" with a particular emphasis on works published between 2018 and 2021. The paper also discussed the pros and cons of each TM technique, trust metrics/features, contributions, and limitations of the state-of-the-art SIoT TM proposals in the literature. The paper further provides open issues and possible research directions for entry-level researchers in the domain of SIoT.
20
Um, Lee, Lee, and Yoon. "Design and Implementation of a Trust Information Management Platform for Social Internet of Things Environments." Sensors 19, no. 21 (October 29, 2019): 4707. http://dx.doi.org/10.3390/s19214707.
Abstract:
As the vast amount of data in social Internet of Things (IoT) environments considering interactions between IoT and people is accumulated and processed through cloud and big data technologies, the services that utilize them are applied in various fields. The trust between IoT devices and their data is recognized as the core of IoT ecosystem creation and growth. Connection with suspicious IoT devices may pose a risk to services and system operation. Therefore, it is essential to analyze and manage trust information for devices, services, and people, as well as to provide the trust information to the other devices or users that need it. This paper presents a trust information management framework which contains a generic IoT reference model with trust capabilities to achieve the goal of converged trust information management. Additionally, a trust information management platform (TIMP) consisting of trust agents, trust information brokers, and trust information management systems has been proposed, which aims to provide trustworthy and safe interactions among people, virtual objects, and physical things. Implementing and deploying a TIMP enables a trustworthy ecosystem to be built while activating social IoT businesses by reducing transaction costs, as well as by eliminating the uncertainties in the use of social IoT services and data transactions.
21
Khan, Aysha, and Jana Shafi. "Graph Modelling of Social Internet of Things (S-IoT) centered home automation using medium domination approach." Boletim da Sociedade Paranaense de Matemática 41 (December 23, 2022): 1–6. http://dx.doi.org/10.5269/bspm.51446.
Abstract:
Preceding years predict IoT to be trend in technology domain as it possesses superior intelligence and methods to access data as well able to construct networks anywhere which we are witnessing today. Today IoT devices are well implemented and are a topic and product of interest for many. In midst of this S-IoT emerged which is understood as the added ingredient in IoT networks enables improvement in accessing data, its procession, real-time decisions, and many more new functions and all of this with an ideal price [1]. S-IoT led to the interesting development of enabling the Internet of things to be socially connected in a network with each other which permits them to socially interact with each other and have their respective profiles for their identification all similar to humans. This magical innovation-led internet networks to be more complicated. In this paper, we are modeling objects of S-Iot centered homes as network graphs with a medium domination number approach. The key notion here is to inspect the total number of objects connected that dominate every pair of objects in a network graph and the average value of this is defined as “the medium domination number”. We evaluated new results and relations along with further vulnerability methods and developed an algorithm of complexity O(n 2).
22
Chethan Raj C. "Implementation of Trust Model for Social Internet of Things Using Centrality Feed Forward Networks." Journal of Electrical Systems 20, no. 5s (April 27, 2024): 2791–800. http://dx.doi.org/10.52783/jes.2832.
Abstract:
Recent advances of Internet of Things (IoT) lead to the most promising paradigm called Social Internet of Things (SIoT). These techniques are considered the strong amalgamation of the social networking features with the IoT objects. These networks are characterized by facilitating the IoT objects to establish the social networking between each other. In SIoT, an interconnection of networks formed by considering the important features such a object-object interactions, social relationship, reliable recommendations and mandates the careful attention towards the strong trustworthy connections. Hence Intelligent Trust Model Identification Model System (ITMIS) is required for the SIoT networks to identify the misbehaving objects by selecting only the reliable, credible and trustworthy objects before relying on the services provided by them. However, existing frameworks truly relay on the conventional approaches that is based on linear relationship between the inputs and outputs. These methods may lead to the high misclassification ratio of selecting the untrusted devices that even may cause untrust process in an application. To overcome this problem, in the proposed research work the novel ITMIS which ensembles the non-linear centralities relationships with the architecture Extreme Feed Forward Neural Networks (EFFNN) with the combination of hybrid algorithm of Long Short Term Memory (LSTM) and Gated Recuurent Unit (GRU) for the better accuracy compare with the existing model. The proposed model captures the number of key trust metrics based on centralities measurements and envisages the EFNN to classify the trusty and non-trust objects. The extensive experimentations are conducted using the real world datasets and various trust metrics were evaluated and compared with the other state-of-the-art trust learning models. The results demonstrate that the proposed model has outperformed with the other existing models by maintaining the accuracy of 95% to 94% with the decreasing untrusted rates and It illustrates conclusively that the LSTM's use of enhancing ensemble characteristics has shown to be more advantageous. While other models, like E-LSTM (90%) to 80%, Stacked LSTM (85% to 80%), SVM (85% to 79%), KNN (75% to 68%), and RF (65% to 58%), exhibit decreasing efficiency, the proposed approach illustrates that it is more productive as well as efficient for building an intelligent trust classification system that is appropriate for establishing trusted SIoT network communication.
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Chethan Raj C. "Implementation of Trust Model for Social Internet of Things Using Centrality Feed Forward Networks." Journal of Electrical Systems 20, no. 6s (May 2, 2024): 2889–99. http://dx.doi.org/10.52783/jes.3294.
Abstract:
Recent advances of Internet of Things (IoT) lead to the most promising paradigm called Social Internet of Things (SIoT). These techniques are considered the strong amalgamation of the social networking features with the IoT objects. These networks are characterized by facilitating the IoT objects to establish the social networking between each other. In SIoT, an interconnection of networks formed by considering the important features such a object-object interactions, social relationship, reliable recommendations and mandates the careful attention towards the strong trustworthy connections. Hence Intelligent Trust Model Identification Model System (ITMIS) is required for the SIoT networks to identify the misbehaving objects by selecting only the reliable, credible and trustworthy objects before relying on the services provided by them. However, existing frameworks truly relay on the conventional approaches that is based on linear relationship between the inputs and outputs. These methods may lead to the high misclassification ratio of selecting the untrusted devices that even may cause untrust process in an application. To overcome this problem, in the proposed research work the novel ITMIS which ensembles the non-linear centralities relationships with the architecture Extreme Feed Forward Neural Networks (EFFNN) with the combination of hybrid algorithm of Long Short Term Memory (LSTM) and Gated Recuurent Unit (GRU) for the better accuracy compare with the existing model. The proposed model captures the number of key trust metrics based on centralities measurements and envisages the EFNN to classify the trusty and non-trust objects. The extensive experimentations are conducted using the real world datasets and various trust metrics were evaluated and compared with the other state-of-the-art trust learning models. The results demonstrate that the proposed model has outperformed with the other existing models by maintaining the accuracy of 95% to 94% with the decreasing untrusted rates and It illustrates conclusively that the LSTM's use of enhancing ensemble characteristics has shown to be more advantageous. While other models, like E-LSTM (90%) to 80%, Stacked LSTM (85% to 80%), SVM (85% to 79%), KNN (75% to 68%), and RF (65% to 58%), exhibit decreasing efficiency, the proposed approach illustrates that it is more productive as well as efficient for building an intelligent trust classification system that is appropriate for establishing trusted SIoT network communication.
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Amin, Farhan, Rashid Abbasi, Abdul Rehman, and Gyu Sang Choi. "An Advanced Algorithm for Higher Network Navigation in Social Internet of Things Using Small-World Networks." Sensors 19, no. 9 (April 29, 2019): 2007. http://dx.doi.org/10.3390/s19092007.
Abstract:
The Internet of Things (IoT) is a recent evolutionary technology that has been the primary focus of researchers for the last two decades. In the IoT, an enormous number of objects are connected together using diverse communications protocols. As a result of this massive object connectivity, a search for the exact service from an object is difficult, and hence the issue of scalability arises. In order to resolve this issue, the idea of integrating the social networking concept into the IoT, generally referred as the Social Internet of Things (SIoT) was introduced. The SIoT is gaining popularity and attracting the attention of the research community due to its flexible and spacious nature. In the SIoT, objects have the ability to find a desired service in a distributed manner by using their neighbors. Although the SIoT technique has been proven to be efficient, heterogeneous devices are growing so exponentially that problems can exist in the search for the right object or service from a huge number of devices. In order to better analyze the performance of services in an SIoT domain, there is a need to impose a certain set of rules on these objects. Our novel contribution in this study is to address the link selection problem in the SIoT by proposing an algorithm that follows the key properties of navigability in small-world networks, such as clustering coefficients, path lengths, and giant components. Our algorithm empowers object navigability in the SIoT by restricting the number of connections for objects, eliminating old links or having fewer connections. We performed an extensive series of experiments by using real network data sets from social networking sites like Brightkite and Facebook. The expected results demonstrate that our algorithm is efficient, especially in terms of reducing path length and increasing the average clustering coefficient. Finally, it reflects overall results in terms of achieving easier network navigation. Our algorithm can easily be applied to a single node or even an entire network.
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Rizwanullah, Mohammed, Sunil Singh, Rajeev Kumar, Fatma S. Alrayes, Abdullah Alharbi, Mrim M. Alnfiai, Pawan Kumar Chaurasia, and Alka Agrawal. "Development of a Model for Trust Management in the Social Internet of Things." Electronics 12, no. 1 (December 22, 2022): 41. http://dx.doi.org/10.3390/electronics12010041.
Abstract:
The Internet of Things (IoT) has evolved at a revolutionary pace in the last two decades of computer science. It is becoming increasingly fashionable for the IoT to be rebranded as the “Social Internet of Things” (SIoT), and this is drawing the attention of the scientific community. Smart items in the Internet of Things (IoT) ecosystem can locate relevant services based on the social ties between neighbors. As a result, SIoT displays the interplay between various items as a problem in the context of the social IoT ecosystem. Navigating a network can be difficult because of the number of friends and the complexity of social ties. By identifying difficulties with standard SIoT devices’ interaction with social objects, truthful friend computing (TFC) is a new paradigm for tracing such difficulties by utilising a relationship management component to improve network navigability. The concept of trust management can be useful as a strategy during collaborations among social IoT nodes. As a result, the trustor can use a variety of measures to evaluate a smart object’s trustworthiness. Hence, this article demonstrates the need for the trustor to evaluate the extent to which a given metric has contributed to the overall trust score and illustrates profitability when engaging in a transaction with other nodes. With the help of the SIoT, this paper used a unified fuzzy-based computational technique and a multiple-criteria decision-making approach to evaluate the trust weights. The statistical findings show that the computing of “truthful friends” is the biggest challenge for successful SIoT implementation at the initial level.
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Vadlamudi, Siddhartha. "The Internet of Things (IoT) and Social Interaction: Influence of Source Attribution and Human Specialization." Engineering International 9, no. 1 (April 20, 2021): 17–28. http://dx.doi.org/10.18034/ei.v9i1.526.
Abstract:
The evolvement of IT has open new doors in connecting many devices to the worldwide web that successively produce data around the physical setting using the IoT. However, the system of message turns out to be slightly intricate in human specialization-internet of things communication for the reason that the IoT is a system including diverse objects transferring data This study examines the hypothetical pathway by which the changes in source attribution that is multiple against single and specialization that is multi-functionality against single functionality of IoT devices affect the quality of human- internet of things interaction. The result from the study obtained from 80 participants that took part in the experiment shows that multiple source attribution improves the condition of information basically for the low-involvement people supports further probes the multiple source effects. However, this study recommends improvement of attribution source and human specialization-IoT.
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Tzafestas, Spyros. "Ethics and Law in the Internet of Things World." Smart Cities 1, no. 1 (October 12, 2018): 98–120. http://dx.doi.org/10.3390/smartcities1010006.
Abstract:
The aim of the law is to maintain social order, peace, and justice in society, whereas the aim of ethics is to provide codes of ethics and conduct that help people to decide what is wrong, and how to act and behave. Laws provide a minimum set of standards for obtaining good human behavior. Ethics often provides standards that exceed the legal minimum. Therefore, for the best behavior, both law and ethics should be respected. The Internet of Things (IoT) involves a large number of objects and humans that are connected via the Internet ‘anytime’ and ‘anyplace’ to provide homogeneous communication and contextual services. Thus, it creates a new social, economic, political, and ethical landscape that needs new enhanced legal and ethical measures for privacy protection, data security, ownership protection, trust improvement, and the development of proper standards. This survey and opinion article is concerned with the ethics and legislation of the IoT and provides an overview of the following: definition and history of the IoT; general ethical principles and theories that are available for application in the IoT; the role of governments in the IoT; regulations in the European Union (EU) and United States for the IoT’ IoT characteristics that have the potential to create ethical problems; IoT ethical questions and principles; IoT security, privacy, and trust aspects; and the ethical culture of IoT-related companies.
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Cano, Sandra, Victor Peñeñory, César A. Collazos, and Sergio Albiol-Pérez. "Designing Internet of Tangible Things for Children with Hearing Impairment." Information 11, no. 2 (January 28, 2020): 70. http://dx.doi.org/10.3390/info11020070.
Abstract:
Tangible User Interfaces (TUIs) are a new, non-traditional way to interact with digital information using a physical environment. Therefore, TUIs connect a physical set of objects that can be explored and manipulated. TUI can be interconnected over the Internet, using Internet of Things (IoT) technology to monitor a child’s activities in real-time. Internet of Tangible Things (IoTT) is defined as a tangible interaction applied to IoT. This article describes four case studies that apply IoTT to children with cochlear implants and children whose communication is sign language. For each case study, a discussion is presented, discussing how IoTT can help the child development in skills such as: social, emotional, psychomotor, cognitive, and visual. It was found that IoTT works best when it includes the social component in children with hearing impairment, because it helps them to communicate with each other and build social-emotional skills.
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Messina, Fabrizio, Domenico Rosaci, and Giuseppe M. L. Sarnè. "Applying Trust Patterns to Model Complex Trustworthiness in the Internet of Things." Electronics 13, no. 11 (May 29, 2024): 2107. http://dx.doi.org/10.3390/electronics13112107.
Abstract:
Key aspects of communities of the Internet of Things (IoT) smart objects presenting social aspects are represented by trust and reputation relationships between the objects. Several trustworthiness models have been presented in the literature in the context of multi-smart object community that could be adopted in the IoT scenario; however, most of these approaches represent the different dimensions of trust using scalar measures, then integrating these measures in a global trustworthiness value. In this paper, we discuss the limitation of this approach in the IoT context, highlighting the necessity of modeling complex trust relationships that cannot be captured by a vector-based model, and we propose a new trust model in which the trust perceived by an object with respect to another object is modeled by a directed, weighted graph whose vertices are trust dimensions and whose arcs represent relationships between trust dimensions. By using this new model, we provide the IoT community with the possibility of representing also situations in which an object does not know a trust dimension, e.g., reliability, but it is able to derive it from another one, e.g., honesty. The introduced model can represent any trust structure of the type illustrated above, in which several trust dimensions are mutually dependent.
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Cirillo, Flavio, Fang-Jing Wu, Gürkan Solmaz, and Ernö Kovacs. "Embracing the Future Internet of Things." Sensors 19, no. 2 (January 16, 2019): 351. http://dx.doi.org/10.3390/s19020351.
Abstract:
All of the objects in the real world are envisioned to be connected and/or represented, through an infrastructure layer, in the virtual world of the Internet, becoming Things with status information. Services are then using the available data from this Internet-of-Things (IoT) for various social and economical benefits which explain its extreme broad usage in very heterogeneous fields. Domain administrations of diverse areas of application developed and deployed their own IoT systems and services following disparate standards and architecture approaches that created a fragmentation of things, infrastructures and services in vertical IoT silos. Coordination and cooperation among IoT systems are the keys to build “smarter” IoT services boosting the benefits magnitude. This article analyses the technical trends of the future IoT world based on the current limitations of the IoT systems and the capability requirements. We propose a hyper-connected IoT framework in which “things” are connected to multiple interdependent services and describe how this framework enables the development of future applications. Moreover, we discuss the major limitations in today’s IoT and highlight the required capabilities in the future. We illustrate this global vision with the help of two concrete instances of the hyper-connected IoT in smart cities and autonomous driving scenarios. Finally, we analyse the trends in the number of connected “things” and point out open issues and future challenges. The proposed hyper-connected IoT framework is meant to scale the benefits of IoT from local to global.
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Abdul, Rehman, Anand Paul, Junaid Gul M., Won-Hwa Hong, and Hyuncheol Seo. "Exploiting Small World Problems in a SIoT Environment." Energies 11, no. 8 (August 10, 2018): 2089. http://dx.doi.org/10.3390/en11082089.
Abstract:
Internet of Things (IoT) has been at the center of attention among researchers for the last two decades. Their aim was to convert each real-world object into a virtual object. Recently, a new idea of integrating the Social Networking concept into the Internet of Things has merged and is gaining popularity and attention in the research society due to its vast and flexible nature. It comprises of the potential to provide a platform for innovative applications and network services with efficient and effective manners. In this paper, we provide the sustenance for the Social Internet of Things (SIoT) paradigm to jump to the next level. Currently, the SIoT technique has been proven to be efficient, but heterogeneous smart devices are growing exponentially. This can develop a problematic scenario while searching for the right objects or services from billions of devices. Small world phenomena have revealed some interesting facts and motivated many researchers to find the hidden links between acquaintances in order to reach someone across the world. The contribution of this research is to integrate the SIoT paradigm with the small world concept. By integrating the small world properties in SIoT smart devices, we empower the Smart Social Agent (SSA). The Smart Social Agent ensures the finding of appropriate friends (i.e., the IoT devices used by our friend circle) and services that are required by the user, without human intervention. The Smart Social Agent can be any smart device in SIoTs, e.g., mobile phones.
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Singh, Sunil, Pawan K. Chaurasia, and Manohar Lal. "A Review on Trust Management in the Social Internet of Things: Issues and Challenges." Technix International Journal for Engineering Research 9, no. 6 (June 21, 2022): 1–8. http://dx.doi.org/10.56975/tijer.v9i6.152.
Abstract:
In today's era, every electrical and electronic device is connected very intelligently. These electronic devices like sensors, RFIDs, actuators are becoming an important part of the structure. It is required to connect to the internet. Internet is used in every aspect of daily life. There are drastic changes in the usage of the most demanding and useful technology known as the Internet of Things (IoT). In this field, IoT has been shown one of the important which connect various physical objects with the internet with unique identification. Billions of objects are enabled with the internet and interconnected with each other to interface with Human-to-Machine or Machine-to-Machine to take decisions of data transaction without human involvement. This internet enables devices connected to our social life which is terme as Social Internet of Things (SIoT). Hence we can say SIoT is an expansion IoT. People and things are connected with social networks which are known as Human to Things (H2T) interactions. Some of the devices are authentic and some are suspicious. The essential utilization of services within SIoT makes a secured network closely rely on origin of services (Service provider) and services accesed by end terminal (Service requester). Due to a lack of trust technologies, trust SIoT is still not so much popular in the market as demanding technology for the researcher and developer. Device owners are worried about sharing the data or receiving any information. Therefore, trust devices are required to identify in the connected network..Hence minimization of risk and uncertaintity within the system are analyse by the degree of trust for Particular Trust Management System(TMS).Trust and Trustworthiness are novel fields in social networking environment clearlify by investigating the research article under SIoT. In present paper, our contribution starts with the introduction and then is further fragmented in three phases.The first phase represent the basic of trust and SIoT. Second phase categorizes the trust management solutions from the literature review. The third phase identifies and discuses issues, challenges and requirement in current scenario of SIoT and also depicts how developing trust and trustworthiness among social devices interaction as challenging task.
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Wei, Lijun, Yuhan Yang, Jing Wu, Chengnian Long, and Yi-Bing Lin. "A Bidirectional Trust Model for Service Delegation in Social Internet of Things." Future Internet 14, no. 5 (April 29, 2022): 135. http://dx.doi.org/10.3390/fi14050135.
Abstract:
As an emerging paradigm of service infrastructure, social internet of things (SIoT) applies the social networking aspects to the internet of things (IoT). Each object in SIoT can establish the social relationship without human intervention, which will enhance the efficiency of interaction among objects, thus boosting the service efficiency. The issue of trust is regarded as an important issue in the development of SIoT. It will influence the object to make decisions about the service delegation. In the current literature, the solutions for the trust issue are always unidirectional, that is, only consider the needs of the service requester to evaluate the trust of service providers. Moreover, the relationship between the service delegation and trust model is still ambiguous. In this paper, we present a bidirectional trust model and construct an explicit approach to address the issue of service delegation based on the trust model. We comprehensively consider the context of the SIoT services or tasks for enhancing the feasibility of our model. The subjective logic is used for trust quantification and we design two optimized operators for opinion convergence. Finally, the proposed trust model and trust-based service delegation method are validated through a series of numerical tests.
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Alqahtani, Abdullah Saad. "The Challenges of the Internet of Things (IoT): Systematic Literature Review." Journal of Computational and Theoretical Nanoscience 16, no. 9 (September 1, 2019): 3643–55. http://dx.doi.org/10.1166/jctn.2019.8365.
Abstract:
The Internet of things market grew rapidly in recent years. The increased number of connected objects and the diversity of IoT services caused many challenges. The IoT links heterogeneity sensors from different networks in order to address users’ needs. A systematic review study was accomplished to identify and clarify the challenges of the IoT with an initial result set of 811 articles, covering studies published from 2013 to 2019. 50 studies were selected and classified according to the study criteria. The results include highlighting the 10 main challenges with the IoT and introducing data security and privacy as major concerns. The lack of standardization and interoperability is also considered a critical challenge with the IoT. In addition, the descriptive results reported that most of the investigated papers are related either to industrial or technical aspect. A lack of other areas with the IoT, such as educational, social, and cloud, were reported as well.
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Kalakumari, Dr T., and Dr Jehan Murugadhas. "Internet of Things (IoT) in Industry and Other Applications." YMER Digital 21, no. 03 (March 9, 2022): 159–64. http://dx.doi.org/10.37896/ymer21.03/18.
Abstract:
Internet connects people along through enterprise and social verbal exchange like Mobile banking and electronic commerce. In the recent technology world, the growing Internet of Things (IoT) is all concerning connecting equipment and organizations through sensors, actuators and other electronic components. So, critical data from those systems can be accumulated and moves taken to enhance human productiveness and potency. IoT takes the object of inter-communication to a full high-level architecture. While IoT guarantees the manner to scale back wastes, fees and inconvenience while growing efficiency, the maximum vital elegance of this on coming years. Also, it enhances smart world to persuade environmentally cleaner, effective and a stronger high-quality of life
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Akeel Awadh, Wid, Ali Salah Hashim, and Alaa Khalaf Hamoud. "A REVIEW ON INTERNET OF THINGS ARCHITECTURE FOR BIG DATA PROCESSING." Iraqi Journal for Computers and Informatics 46, no. 1 (June 30, 2020): 11–19. http://dx.doi.org/10.25195/ijci.v46i1.245.
Abstract:
The importance of big data implementations is increased due to large amount of gathered data via the online gates. The businesses and organizations would benefit from the big data analysis i.e. analyze the political, market, and social interests of the people. The Internet of Things (IoT) presents many facilities that support the big data transfer between various Internet objects. The integration between the big data and IoT offer a lot of implementations in the daily life like GPS, Satellites, and airplanes tracking. There are many challenges face the integration between big data transfer and IoT technology. The main challenges are the transfer architecture, transfer protocols, and the transfer security. The main aim of this paper is to review the useful architecture of IoT for the purpose of big data processing with the consideration of the various requirements such as the transfer protocol. This paper also reviews other important issues such as the security requirements and the multiple IoT applications. In addition, the future directions of the IoT-Big data are explained in this paper.
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Kovalenko, O. Ye. "Security models of the Internet of Things." Mathematical machines and systems 4 (2023): 43–50. http://dx.doi.org/10.34121/1028-9763-2023-4-43-50.
Abstract:
The IoT is a cyber-convergent system that includes things, means of communication, target ap-plications, and data analysis tools that support the unique identification of each object. IoT technologies play a vital role in the creation of cyber-convergent systems due to their wide us-age in various spheres of life such as industry, social sphere, health care, and creating a com-fortable environment. The IoT security model method ensures the confidentiality, integrity, and availability of data that is transferred between devices and also guarantees the privacy and secu-rity of end users. The creation and use of IoT systems directly affect the security and privacy of the involved and connected components. The presented study introduces an analysis of IoT ar-chitecture models with end-to-end security support. The conducted literature review reveals the challenges of various aspects of security faced by the IoT environment. Some models imple-menting different security strategies at different layers of the IoT are described. These include the perception layer which provides the authentication process for identifying IoT entities, the network layer which focuses on the security processes of cloud platforms, and the application layer which provides authentication and authorization for end users. The results of the analysis show that building secure IoT systems is based on three main strategies: proper configuring and ensuring the protection of all IoT devices; using secure wireless networks to connect IoT devic-es to corporate or global networks; constant situational awareness of security threats to IoT de-vices; and implementing appropriate security solutions to protect them from attacks. The ma-turity model of the IoT security system based on the ISA/IEC 62443 document package is also described.
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Lye, Guang Xing, Wai Khuen Cheng, Teik Boon Tan, Chen Wei Hung, and Yen-Lin Chen. "Creating Personalized Recommendations in a Smart Community by Performing User Trajectory Analysis through Social Internet of Things Deployment." Sensors 20, no. 7 (April 8, 2020): 2098. http://dx.doi.org/10.3390/s20072098.
Abstract:
Despite advancements in the Internet of Things (IoT) and social networks, developing an intelligent service discovery and composition framework in the Social IoT (SIoT) domain remains a challenge. In the IoT, a large number of things are connected together according to the different objectives of their owners. Due to this extensive connection of heterogeneous objects, generating a suitable recommendation for users becomes very difficult. The complexity of this problem exponentially increases when additional issues, such as user preferences, autonomous settings, and a chaotic IoT environment, must be considered. For the aforementioned reasons, this paper presents an SIoT architecture with a personalized recommendation framework to enhance service discovery and composition. The novel contribution of this study is the development of a unique personalized recommender engine that is based on the knowledge–desire–intention model and is suitable for service discovery in a smart community. Our algorithm provides service recommendations with high satisfaction by analyzing data concerning users’ beliefs and surroundings. Moreover, the algorithm eliminates the prevalent cold start problem in the early stage of recommendation generation. Several experiments and benchmarking on different datasets are conducted to investigate the performance of the proposed personalized recommender engine. The experimental precision and recall results indicate that the proposed approach can achieve up to an approximately 28% higher F-score than conventional approaches. In general, the proposed hybrid approach outperforms other methods.
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Raja, Piyush, Dr Santosh Kumar, Digvijay Singh Yadav, and Dr Taresh Singh. "The Internet of Things (IOT): A Review of Concepts, Technologies, and Applications." International Journal of Information technology and Computer Engineering, no. 32 (March 22, 2023): 21–32. http://dx.doi.org/10.55529/ijitc.32.21.32.
Abstract:
The Internet of Things (IoT) is a system in which everyday objects such as gadgets, cars, and appliances are equipped with electronics, software, sensors, and network connectivity that allow them to connect to one another and share information and perform tasks. In this study, we examine the fundamentals of the IoT, including its sensors, actuators, and communication protocols. There are still a number of issues and challenges that must be fixed before IoT can live up to its full potential. Many angles on the Internet of Things, such as applications, challenges, enabling technologies, social and environmental repercussions, etc., need to be considered while tackling these issues. The primary purpose of this article is to provide a comprehensive explanation from a technical and societal perspective. The numerous challenges, important issues, architecture, and significant application domains associated with the IoT are all discussed in this article. Many IoT applications are covered, from healthcare to agriculture to transportation, and beyond.
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Kumar Yogi, Manas, Y. Himatej, and M. Mahesh reddy. "IOT Security Challenges and Measures to Mitigate: Novel Perspectives." International Journal of Engineering & Technology 7, no. 2.7 (March 18, 2018): 854. http://dx.doi.org/10.14419/ijet.v7i2.7.11081.
Abstract:
The Internet Of Things describes the ever-growing number of intelligent objects that are being connected to the internet and each other, smartphones, tablets, wearable technology and smart home devices are adopted into our everyday lives. The security of IOT is becoming more complex and may have a serious consequence. So, now we have many security challenges like privacy concerns, routine cryptography, passive data collection etc. Many people hide personal data in social media to eliminate these sort of privacy issues but common man nowadays is becoming a passive participant due to lack of security in these IOT devices that are surrounding us.
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Butkowski, Chelsea P., Ngai Keung Chan, and Lee Humphreys. "Community Internet of Things as Mobile Infrastructure: Methodological Challenges and Opportunities." Media and Communication 10, no. 3 (September 28, 2022): 303–14. http://dx.doi.org/10.17645/mac.v10i3.5372.
Abstract:
From smart devices to homes to cities, Internet of Things (IoT) technologies have become embedded within everyday objects on a global scale. We understand IoT technologies as a form of infrastructure that bridges the gaps between offline spaces and online networks as they track, transmit, and construct digital data from and of the physical world. We examine the social construction of IoT network technologies through their technological design and corporate discourses. In this article, we explore the methodological challenges and opportunities of studying IoT as an emerging network technology. We draw on a case study of a low-power wide-area network (LPWAN), a cost-effective radio frequency network that is designed to connect sensors across long distances. Reflecting on our semi-structured interviews with LPWAN users and advocates, participant observation at conferences about LPWAN, as well as a community-based LPWAN project, we examine the intersections of methods and practices as related to space, data, and infrastructures. We identify three key methodological obstacles involved in studying the social construction of networked technologies that straddle physical and digital environments. These include (a) transcending the invisibility and abstraction of network infrastructures, (b) managing practical and conceptual boundaries to sample key cases and participants, and (c) negotiating competing technospatial imaginaries between participants and researchers. Through our reflection, we demonstrate that these challenges also serve as generative methodological opportunities, extending existing tools to study the ways data connects online and offline spaces.
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Shammar, Elham Ali, and Ammar Thabit Zahary. "The Internet of Things (IoT): a survey of techniques, operating systems, and trends." Library Hi Tech 38, no. 1 (October 5, 2019): 5–66. http://dx.doi.org/10.1108/lht-12-2018-0200.
Abstract:
Purpose Internet has changed radically in the way people interact in the virtual world, in their careers or social relationships. IoT technology has added a new vision to this process by enabling connections between smart objects and humans, and also between smart objects themselves, which leads to anything, anytime, anywhere, and any media communications. IoT allows objects to physically see, hear, think, and perform tasks by making them talk to each other, share information and coordinate decisions. To enable the vision of IoT, it utilizes technologies such as ubiquitous computing, context awareness, RFID, WSN, embedded devices, CPS, communication technologies, and internet protocols. IoT is considered to be the future internet, which is significantly different from the Internet we use today. The purpose of this paper is to provide up-to-date literature on trends of IoT research which is driven by the need for convergence of several interdisciplinary technologies and new applications. Design/methodology/approach A comprehensive IoT literature review has been performed in this paper as a survey. The survey starts by providing an overview of IoT concepts, visions and evolutions. IoT architectures are also explored. Then, the most important components of IoT are discussed including a thorough discussion of IoT operating systems such as Tiny OS, Contiki OS, FreeRTOS, and RIOT. A review of IoT applications is also presented in this paper and finally, IoT challenges that can be recently encountered by researchers are introduced. Findings Studies of IoT literature and projects show the disproportionate importance of technology in IoT projects, which are often driven by technological interventions rather than innovation in the business model. There are a number of serious concerns about the dangers of IoT growth, particularly in the areas of privacy and security; hence, industry and government began addressing these concerns. At the end, what makes IoT exciting is that we do not yet know the exact use cases which would have the ability to significantly influence our lives. Originality/value This survey provides a comprehensive literature review on IoT techniques, operating systems and trends.
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Prashant, Gangapurwala Monika, and Gangapurwala Pratik P. "Internet of Things - Novel Application in Agriculture." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (May 31, 2024): 810–16. http://dx.doi.org/10.22214/ijraset.2024.61652.
Abstract:
Abstract: In the Present Era, the world is experiencing a strong rush towards modern technology, while specialized companies are living a terrible rush in the information and Communication technology towards the so-called Internet of things IoT or Internet of objects, which is the integration of things with the world of Internet, by adding hardware or/and software to be smart and so is able to communicate with each other and participate effectively in all aspects of daily life. By enabling new forms of communication between people and things, and between things themselves, that will change the traditional life into a high style of living. But it won’t be easy, because there are still many challenges and issues that need to be addressed and have to be viewed from various aspects to realize their full potential. The main objective of this paper is to provide the reader with a detailed discussion from a technological and social perspective. The various IoT aspects, definition and architecture, challenges and issues were discussed. Furthermore, a description of several sensors and actuators and their smart communication. Also, the most important application areas of IoT were presented with a case study. This work will help readers and researchers understand the IoT and its potential application in the real world
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Kirstein, Peter T. "Edge Networks & Devices for the Internet of Things." Daedalus 145, no. 1 (January 2016): 33–42. http://dx.doi.org/10.1162/daed_a_00363.
Abstract:
This paper considers how existing concepts underlying the development of the Internet are being strained in the emerging Internet of Things (IoT). It also explores how the well-known and tried Domain Name Service concepts, which map hierarchic names to addresses, can be extended for the IoT. The extension greatly broadens the concept of name/address mapping to digital objects with identifier/attribute database mapping for physical objects, applications, and data. Finally, this essay discusses the properties of the identifier management systems, showing how scalability, security, and flexibility can be supported in the IoT.
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Prabhu, R. Senthil, D. Sabitha Ananthi, S. Rajasoundarya, R. Janakan, and R. Priyanka. "INTERNET OF NANOTHINGS (IoNT) – A CONCISE REVIEW OF ITS HEALTHCARE APPLICATIONS AND FUTURE SCOPE IN PANDEMICS." International Journal of Pharmaceutical Sciences and Medicine 6, no. 10 (October 30, 2021): 1–15. http://dx.doi.org/10.47760/ijpsm.2021.v06i10.001.
Abstract:
Technologies that could allow literally billions of everyday objects to communicate with each other over the internet have enormous potential to change all our lives. The Internet of Things (IoT) is a transformative development, these technologies are a way of boosting productivity, keeping us healthier, making transport more efficient, reducing energy needs and making our homes more comfortable. In recent years, Internet of Things (IoT) and Internet of Nanothings (IoNT) have drawn significant research attention in numerous fields such as Healthcare, Defence, Environmental monitoring, Food and water quality control etc., There are various transformations such as Smart cities, Smart homes, Smart factories, Smart transportation, due to IoT and IoNT. Health care delivery requires the support of new technologies like IoT, IoNT to fight and look against the new pandemic diseases. For the past two years COVID-19 spreaded over worldwide including India, are fighting with pandemic disease and still looking for a practical and cost-effective solution to face the problems arising in several ways. To minimize the person to person, contact and to maintain social distancing various technologies are utilized, among them IoT and IoNT play a major role in healthcare system and allied fields. This review mainly discuss about the IoT, IoNT, its components and various applications in healthcare and allied fields.
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El-Haggar, Nahla, Lobna Amouri, Albandari Alsumayt, Fatemah H. Alghamedy, and Sumayh S. Aljameel. "The Effectiveness and Privacy Preservation of IoT on Ubiquitous Learning: Modern Learning Paradigm to Enhance Higher Education." Applied Sciences 13, no. 15 (August 6, 2023): 9003. http://dx.doi.org/10.3390/app13159003.
Abstract:
The progress made in Information and Communication Technologies (ICT) has played a crucial role in turning the Internet of Things (IoT) into a reality. IoT is an emerging technology that refers to networks of interconnected and Internet-enabled objects equipped with sensors, processors, and actuators that interact with each other to create significant collaboration and interaction environments. The field of education is one of the areas where IoT can be applied. However, the implementation of IoT poses security and privacy risks, such as unauthorized access, denial-of-service (DoS) attacks, and interference with wireless signals where IoT devices collect a significant amount of data, including user’s personal information like identity, location, and daily behavior. Therefore, it is crucial to protect users’ privacy in IoT applications. The innovative Ubiquitous Learning Environments (ULEs) have been created by ubiquitous computing technologies (mobile, wireless, network), which provide learners with learning experiences beyond the traditional classroom in both the real and virtual worlds. Ubiquitous learning (U-learning) is an emerging technology as a result of the tremendous technological revolution of ICT. U-learning is a novel learner-centered approach that aims to enhance learning, motivation, and creativity by utilizing innovative technology and IoT. U-learning enables learners to access the appropriate learning content, collaborate with the right learning partners, and engage in self-learning at the right time and place in a ubiquitous computing environment. To support learners in developing their social skills, in this study a framework for implementing the ULE based on the Internet of Things is designed, which consists of three main layers: perception, network, and application. The article explores the effects of IoT on education and how U-learning, which incorporates IoT to enhance learning experiences, has the potential to replace traditional classroom learning. Furthermore, the article addresses privacy preservation measures for different layers within the IoT environment and ULE. A framework for implementing the ULE model is in progress, which is a part of our future work.
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Mahmud, Syamsul H., Laromi Assan, and Rashidul Islam. "Potentials of Internet of Things (IoT) in Malaysian Construction Industry." Annals of Emerging Technologies in Computing 2, no. 4 (October 1, 2018): 44–52. http://dx.doi.org/10.33166/aetic.2018.04.004.
Abstract:
IoT is a man-made technology conceptualized by intelligent virtual objects, which capable of knowing all things and allows the devices around themselves to interact automatically without human control. Every year, the number of IoT devices usage is exponentially increasing and estimated as much as 75.44 billion devices will be connected in IoT network. In line with the expansion of the IoT network, the construction industry should take into consideration as otherwise the construction industry will be left behind by other industries. This is because the construction industry should utilize the applications offered by IoT to ensure the smoothness of the construction industry in the project. Therefore, the objective of this study is to identify the types of IoT applications used in the construction industry in Malaysia. The research method used to identify the types of IoT applications used is through the questionnaire method. The questionnaire was analysed using nominal analysis. A study was conducted on construction industry players which comprising of government agencies, developers, architects, engineers, quantity surveyors and class G7 contractors covering all states in Malaysia. The findings show that among the many types of IoT applications used by construction industry players are social media such as WhatsApp, Telegram and Facebook for discussion and communication purposes, the use of email for information and communication exchange and website usage as a source of reference to obtain data on company profiles, acts and policy, price quotes and so on.
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Javida Damirova, Javida Damirova, and Laman Musayeva Laman Musayeva. "INTERNET OF THINGS." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 13, no. 02 (March 1, 2022): 33–43. http://dx.doi.org/10.36962/pahtei13022022-33.
Abstract:
This article will discuss the Internet of things, which is a completely new technology. Currently, the world's most talked about new electronics use Internet of Things technology. This technology includes Google, Yandex, YouTube and all our social networks. The current benefits of Internet of Things technology will be discussed, as well as its future position. What is the role of smart technologies in the development of robotics, new electronics and the impetus for new inventions? The Internet of Things is a new paradigm that transforms traditional lifestyles into high-tech lifestyles. Many important studies and researches have been conducted to improve the technology through IoT. The Internet of Things, or IoT, refers to the billions of physical devices around the world that are now connected to the internet, all collecting and sharing data. The main purpose of this review article is to provide a detailed discussion, both technologically and socially. It is not just about the connected devices but also about the hardware, software, connectivity and communication protocols, middleware and so much more to create Internet of Things solutions as mentioned. And it’s also about many processes and technologies. So, this is most important theme in our world. The article discusses various problems and key issues in IoT, architecture and important applications. The Internet of Things is an emerging paradigm that enables the communication between electronic devices and sensors through the internet in order to facilitate our lives. IoT has also demonstrated its importance and potential for economic and industrial growth in the developing region. It is also seen as a revolutionary step in the trading and stock markets. However, data and information security is an important concern and is highly desirable, which is a major challenge that needs to be addressed. The Internet, the biggest source of security threats and cyber attacks, has opened various doors for hackers, thereby discrediting information and data. IoT is committed to providing the best possible solutions to deal with data and information security issues. IoT's most important concern in trade and the economy is security. The IoT system consists of a large number of devices and sensors that communicate with each other. They can range from a Wi-Fi pet camera on your bookshelf to a medical device implanted in your body, like a pacemaker. As long as the device is able to connect to the internet and has sensors that transmit data, it can be considered an IoT device. As the IoT network grows and expands, the number of these sensors and devices is growing rapidly. These devices communicate with each other and transmit large amounts of information over the Internet. This information is very large and flows every second, and therefore deserves to be called great information. The IoT was initially most interesting to business and manufacturing, where its application is sometimes known as machine-to-machine (mean - M2M), but the emphasis is now on filling our homes and offices with smart devices, transforming it into something. Today, these IoT projects are evolving and rapidly spreading to all platforms. It is possible to find IoT projects for each topic. As mentioned earlier, IoT projects are designed to make life easier. These projects, created to help as many people as possible, will be the most important part of our future lives. It will be impossible to imagine our lives without the Internet of Things and smart projects. A smart city with sensors covering all its regions using diverse tangible gadgets and objects all over the community and connected with the help of internet. The continuous expansion of IoT-based networks poses complex challenges such as data management and collection, storage and processing, and analytics. This article sheds light on the existing literature and describes their contributions to various aspects of IoT. This article will help readers and researchers understand IoT and its application to the real world Keywords: arduino, sensors, security systems, robotics, intelligent technology.
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Demyanov, Gleb, and Natalya Sadovnikova. "Network Interaction Monitoring System with IoT Devices Connected." NBI Technologies, no. 4 (March 2021): 12–17. http://dx.doi.org/10.15688/nbit.jvolsu.2020.4.2.
Abstract:
The Internet of Things is a concept of a computer network of physical objects equipped with built-in technologies for interacting with each other or with the external environment, considering the organization of such networks as a phenomenon that can restructure economic and social processes, eliminating the need for human participation from part of actions and operations. IoT technology has had a significant impact on the development of information technology and other industries. According to Forbes, the Internet of Things market is expected to reach $520 billion in 2021, up from $235 billion in 2017, indicating a continued growth in demand for such devices in the future. Gartner Research also estimates that the number of devices connected to the Internet will reach 25 billion by 2021, up from 8.4 billion in 2017. Network with IoT devices connected is an indispensable prey for intruders. There are many ways to attack IoT devices. In this article, the authors have identified several methods of protection. Among them, network interaction monitoring through the analysis is highlighted. The paper also describes how to apply this method in practice.
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Perumal, Sundresan. "Escalation of Security and Privacy in Internet of Things using Advanced IPv6 Based Security Mechanism." Wasit Journal of Computer and Mathematics Science 1, no. 1 (March 17, 2021): 43–51. http://dx.doi.org/10.31185/wjcm.vol1.iss1.7.
Abstract:
Kevin Ashton coined the phrase Internet of Things in 1999 with high performance implementation for corporate and social world. Thanks to the success of high-performing Internet of Things (IoT) whereby the tags and sensors are the foundation for IoT implementation of radio frequency identification with enormous implementation patterns. Real world objects and systems that are remotely managed using program- based tools may be outfitted with RFID tags. Radio frequency recognition devices may identify objects and sense information. Very thin micro-sized RFID chips that can attach remotely are built. The internet of things will cross over USD 267 billion in 2020. According to the report by Gartner, there would be $273 billion linked devices around the world in 2014. The quantity, which is equal to 8.4 billion goods, is 31% more than last year. This study examines security and productivity in the IoT. It is very popular to use Internet of Things (IoT) in robotics because of sensor sensors, advanced wireless technology and use of software programming. Both wireless IP-based systems come with built-in GPS modules. The utility of smart cities and home automation was increasingly accentuated by the appearance of vast databases of smart IP-based sensors. Within the scope of this study, one of the goals is to establish simulation trends that can cover protection weakness of the Internet of Things. In the novel, the simulation processes were implemented through Contiki Cooja and CupCarbon. The modern age is greatly being affected by impossibly sophisticated technical devices. It is treated under the umbrella of Internet of Things (IoT). Several applications are commonly using IoT linked technologies to a broad variety of purposes. IoT contains many other concepts such as universal computing, widespread computing, ambient computing, among several others. The work presents the implementation using high performance framework for the security in the IoT environment using security mechanism on IPv6.