Smart Objects Research Articles

An ontology-based, general-purpose and Industry 4.0-ready architecture for supporting the smart operator (Part I – Mixed reality case)

The advent of novel industry 4.0-driven technologies is offering significant opportunities to manufacturing systems, but at the same time it is posing new great challenges. The growing number of connected and interconnected devices is enormously increasing the amount of data generated, which must be properly organized to give value to the business. Basically, the need for approaches that are able to guarantee compliance with FAIR data principles is significantly emerging. Recently, the KNOW4I platform has been proposed in the literature to support the smart operator through a suite of Smart Utilities and Objects (Longo et al., 2022). The main purpose of this paper is to extend such platform, in the form of an ontology-based, general-purpose and industry 4.0-ready architecture, capable of improving the capabilities of the smart operator, with a focus on mixed reality. The novel proposal is based on two fundamental aspects: (1) a new general ontology, developed through the ontology engineering methodology; (2) the adoption of FIWARE, an open-source infrastructure, capable of enabling interoperability between different systems. The proposed architecture is implemented and validated on two case studies belonging to the manufacturing sector, which respectively concern (1) scheduled maintenance and alarm management and (2) customer order management. The experimental phase shows that the architecture is able to effectively and efficiently support the smart operator.

Neural Network-Based Routing Energy-Saving Algorithm for Wireless Sensor Networks.

With the evolvement, standards have changed, mobile Internet technology has also been upgraded, and it has also driven the development of smart objects mobile. With the continuous development of smart objects mobile, the bottleneck of small node size and low battery energy storage has not been solved in the end, which makes the research of wireless sensor network energy-saving technology become the focus, and the improvement of routing technology is an effective way to improve energy-saving technology. From the data transmission energy consumption of smart objects mobile, the routing algorithm of smart objects mobile is discussed and analyzed and the classical representative LEACH is the object of in-depth research. Routing algorithms can easily and reliably process network data and make the network work well and are widely used in highly secure military systems and smaller commercial networks. Aiming at these deficiencies, a corresponding improved algorithm is proposed, and it is tested through simulation and specific experiments to verify the correctness and the system's reliability. The SMPSO-BP algorithm converges when the number of iterations is about 600, which is earlier than the LEACH algorithm and the improved LEACH algorithm, so the SMPSO-BP algorithm is due to the other two algorithms. In the wireless sensor network routing energy consumption experiment, in addition, the SMPSO-BP algorithm uses less energy than the other two methods. Therefore, the energy-saving algorithm under the neural network data fusion mechanism is still feasible.

Refined LSTM Based Intrusion Detection for Denial-of-Service Attack in Internet of Things

The Internet of Things (IoT) is a promising technology that allows numerous devices to be connected for ease of communication. The heterogeneity and ubiquity of the various connected devices, openness to devices in the network, and, importantly, the increasing number of connected smart objects (or devices) have exposed the IoT network to various security challenges and vulnerabilities which include manipulative data injection and cyberattacks such as a denial of service (DoS) attack. Any form of intrusive data injection or attacks on the IoT networks can create devastating consequences on the individual connected device or the entire network. Hence, there is a crucial need to employ modern security measures that can protect the network from various forms of attacks and other security challenges. Intrusion detection systems (IDS) and intrusion prevention systems have been identified globally as viable security solutions. Several traditional machine learning methods have been deployed as IoT IDS. However, the methods have been heavily criticized for poor performances in handling voluminous datasets, as they rely on domain expertise for feature extraction among other reasons. Thus, there is a need to devise better IDS models that can handle the IoT voluminous datasets efficiently, cater to feature extraction, and perform reasonably well in terms of overall performance. In this paper, an IDS based on redefined long short-term memory deep learning approach is proposed for detecting DoS attacks in IoT networks. The model was tested on benchmark datasets; CICIDS-2017 and NSL-KDS datasets. Three pre-processing procedures, which include encoding, dimensionality reduction, and normalization were deployed for the datasets. Using key classification metrics, experimental results obtained show that the proposed model can effectively detect DoS attacks in IoT networks as it performs better compared to other methods including models from related works.

Internet of Things (IoT), Applications, Open Issues, and Challenges: A Comprehensive Survey.

Abstract: One of the most well-known names has been the Internet of Things (IoT), which has risen to greater levels and become a world standard in the last few years. Things (items) in the physical world have been changed into smart objects. The Internet of Things (IoT) aims to connect all of the world's things under one common framework, allowing users to monitor and report on their present status on a regular and timely basis. IoT has become a standard for creating communication between devices. In light of the current state of IoT, a comprehensive survey of literature on many topics of IoT, such as technology and challenges, has been conducted. Existing challenges and issues in these fields are also mentioned. Future research directions in the field of IoT have also been highlighted in the study to allow new researchers in this subject with the tools they need to examine current IoT standings and improve them with innovative ideas

CREATION OF GENERALIZED MODEL OF EDUCATIONAL AND METHODOLOGICAL SUPPORT IN THE SYSTEM «REASONABLE ACT OF HIGHER EDUCATION» ON THE EXAMPLE OF SPECIALTY 193 «GEODESY AND LAND MANAGEMENT»

Now the trend of informatization and automation in various aspects of society is developing. Within the framework of this topic, an article was written highlighting the main ideas in the field of intellectual management of higher education institutions. Within the framework of this trend, models of system automation of constituent elements of management and functioning of higher education institutions in conceptual form are proposed. To do this, an analysis of the state of informatization of processes and phenomena in modern institutions of higher education. The main conceptual provisions of modeling of processes and phenomena of higher education institutions are offered in the work. Based on the analysis of the results of creating intelligent systems, which is called "smart objects", as well as the main trends in the construction and use of applied information technology in higher education, the idea of ​​creating a concept of modeling processes and phenomena in higher education. The main purpose of modeling is to combine the information technologies used in higher education and to create an intelligent information system "Smart Higher Education". Using the methods of aggregation and decomposition, the processes of functioning of a higher education institution are represented by a three-level system, in which information technologies of most types of support of the institution are distinguished. A generalized model of educational and methodological support has been developed. Using this model, an example of educational and methodological support of specialty 193 "Geodesy and Land Management" is presented. As a result, a semantic network was developed, built on the basis of models of disciplines of digital knowledge platforms of higher education. Such a network must meet the requirements of educational standards, in particular be isomorphic to the curriculum of the specialty and, ideally, have the property of transitive closure. And in the future the use of methods of decomposition and abstraction, as well as analysis of logical and heuristic models of knowledge representation led to the understanding that to formalize the functioning of higher education it is necessary to use topological formalities, including methods and representation of category theory. This mathematical apparatus will allow to abstract from insignificant and secondary elements of simulated objects and processes. Methods of system analysis, mathematical logic, heuristic methods were used to build models. The basis for formalizing the elements of the knowledge base of the intelligent system "Smart Institution of Higher Education" has been developed.

Things to Cloud : IOT

The Internet of Things is causing a big revolution, which is a new reality that has replaced traditional life with modernized life. Smart objects have made our lives easy. The IoT is virtually present in every aspect of life. Much research in IoT made this possible, along with technology and electronic devices such as chips, sensors, etc. which have greatly contributed to this new revolution and helped to recognize the full potential of IoT. This paper refers to the various domains in IoT and some of their examples, as well as the detailed architecture of IoT with examples. IoT generates huge amounts of data. Hence, the role of big data and cloud computing as tools in solving IoT problems and efficient working. Some issues and challenges related to the IoT have also been discussed, such as security and privacy.

Single-Antenna Device-to-Device Localization in Smart Environments With Backscatter

A long-standing vision of indoor localization is to eliminate infrastructure and deployment costs. Recent innovations make it possible to enable device-to-device (D2D) localization while requiring multiple antennas for the systems. We ask the following question: can we localize the more generally used single-antenna devices (e.g., IoT) using another single-antenna device (e.g., smartphone or smartwatch) in a smart environment where low-cost backscatter tags are widely deployed on walls or smart objects? In this article, we present TagLoc, a lightweight system that enables D2D localization without relying on large antenna arrays. Our observation is that the reflected signals from the ambient smart environment can be exploited to eliminate the requirement of bulky antenna arrays that are unachievable for the simple-designed IoT devices. Specifically, TagLoc creates multiple direction signatures using backscatter arrays in smart environments. Then, the receiver can accurately estimate the direction signatures from the transmitter to the arrays and then localize the target by cooperating all tag arrays. We prototype TagLoc using two single-antenna Intel NUCs with off-the-shelf Intel 5300 WiFi cards and customized backscatter tags. The results show TagLoc can achieve robust performance in a real indoor environment with a median localization error of 0.82 m.

A computational trust model for social IoT based on interval neutrosophic numbers

Nowadays, the trend of evolution of connected devices, communication networks, and cloud services towards the internet of things (IoT) has facilitated the interaction between smart objects with minimal human mediation. Considering IoT, where smart objects can be clients and providers of services for each other, trust between objects is a significant concern for selecting the most appropriate service providers. Trust is an uncertain concept, and its uncertainty originates from different sources, including context conditions, social relationships, and the accuracy of quantitative evaluations. Modeling and considering uncertainty in trust management for the IoT is the principal objective of this research. To this aim, several sources of uncertainty are modeled in trust calculations where interval neutrosophic numbers are used for modeling imprecision, indeterminacy, and inconsistency of the trustworthiness data. In the proposed model, trust in the quality of the provided services (QoS trust), as well as trust in the honesty of the socially related entities providing trust-related information (i.e. social trust), and trust in the suitability of context conditions (i.e. context-trust) are considered to calculate the overall trust used for the decision-making process. The impact of each of these dimensions on the final calculated trust has been evaluated in different scenarios.

CrowdLBM: A lightweight blockchain-based model for mobile crowdsensing in the Internet of Things

With the commercialization of fifth generation mobile networks (5G) and continuous innovation of the Internet of Things (IoT), crowdsensing, as a new emerging IoT application, has further deepened our knowledge, utilizing various smart objects distributed throughout the whole industrial system for data collection and processing. To avoid a single point of failure and ensure data integrity, blockchain technology was widely applied. However, due to the demand for computing power and resources, IoT devices with limited capabilities and resources are unsuitable for crowdsensing implementation in the blockchain network. Therefore, this paper proposes a lightweight blockchain-based crowdsensing model named CrowdLBM with a novel consensus mechanism based on global reputation to resolve the issues raised above. Furthermore, we propose a two-stage scheme and two types of smart contracts to support the crowdsensing process automatically without the intervention of any third party. Finally, we implement a blockchain prototype on Hyperledger Sawtooth, extensive experimental results show that the proposed CrowdLBM outperforms other crowdsensing systems in terms of both scalability and security.

Development and Hardware Implementation of IoT-Based Patrol Robot for Remote Gas Leak Inspection

The Internet of Things Robot (IoTR) is an emerging paradigm that brings together robotic systems with the Internet of Things (IoT) that connect sensors and smart objects pervasively embedded in everyday environments. With the recent developments in robotic system applications, it becomes apparent that the mobile robot has great importance in real-world applications such as navigation and surveillance. One of the most important applications of a mobile robot is patrolling and gas leak detection. This paper proposes a real-time IoT Robot (IoTR) that can be used indoors or outdoors for gas leak detection purposes. The proposed mobile robot is equipped with microphones, speakers, the hub of smart sensors that are necessary for patrolling and gas leak detection, a high-resolution IP video camera for live video streaming, Bluetooth for indoor applications and tracking, and GPS/GPRS for outdoor applications and tracking. The experimental testing of the preliminary prototype confirms the design objectives. The robot has been tested for indoor and outdoor modes; the robot can detect gas leakage and provides a live video streaming of the surrounding area, which can be tracked on Google maps. At the same time, the robot can be controlled remotely through a mobile app or website, the robot can move autonomously and avoid obstacles. The proposed work provides a low-cost IoT robot through the use of the available and cheap components and sensors, which featured a high quality at the same time. Our proposed system exhibits promising gas sensing performance in harsh environments, using intelligent gas sensors that have a fast response (>10s), low cost, high sensitivity, long life, robustness, and physical size.

A Survey on Attribute-Based Encryption Schemes Suitable for the Internet of Things

The Internet of Things (IoT) is an information service paradigm based on the integration of smart objects, mobile devices, and computers via the Internet. IoT technologies are key enablers for a multitude of applications in diverse fields, such as digital health, smart city, industrial automation, and supply chain. This raises new security and privacy challenges that can be addressed by advanced cryptographic methods. One of the most prominent is attribute-based encryption (ABE), which allows one to encrypt data while enforcing fine-grained access control on it. ABE is advantageous in many IoT applications since it allows data to be safely stored on untrusted storage, such as third-party cloud servers, hackable publish-subscribe brokers, physically accessible sensors, etc. This article surveys the ABE literature proposing schemes and solutions that are best suited for IoT applications. To do so, it first identifies three performance indicators that are key in IoT, namely, the data producer CPU efficiency, the data producer bandwidth efficiency, and the key authority bandwidth efficiency. Then, it analyzes only those schemes that are promising from the point of view of one or more indicators and, therefore, more applicable in typical IoT applications. As a further contribution, this article selects a subset of representative schemes and assesses their efficiency by thorough simulations. Such simulations show that no scheme excels in all three performance indicators at once, but some simultaneously perform well in two indicators.

Future IoT Software in Healthcare Also Exploring IoT Industry Application

There has been a great deal of investigation into medical services ability and specialized advancements during the most recent 10 years. To state the obvious, Internet of Things (IoT) has demonstrated insure associating different clinical hardware, sensors, and medical services experts to give top-notch clinical consideration at a distant area. This has upgraded patient security, diminished medical care costs, expanded admittance to medical services benefits, and expanded functional adequacy in the medical care industry. Emerging technologies such as IoT have the potential to transform our lives in many ways. A smart ubiquitous framework can only be built using smart objects in the IoT system, which is its ultimate building pieces. This research surrenders an audit of potential IoT-based innovation applications in medical services conducted to date. This paper records the development of the use of the Healthcare Internet of Things (HIoT) in tending to different medical care worries according to the viewpoints of empowering innovation, medical care administrations, and applications. Besides, potential HIoT framework issues and issues are explored. The current research closes by giving a wellspring of comprehension on the various uses of HIoT with expectations of empowering future scholastics that are quick to chip away at and kick off something new in the field to have a superior handle of the subject. IoT innovation has helped medical care experts in checking and diagnosing an assortment of well-being concerns, estimating an assortment of well-being factors, and giving demonstrative capacities at far-off areas using these standards. The structure and implementation of a specific framework are the subject of this paper. This has moved the medical services industry’s concentrate away from clinics and toward patients.

Dimensions of Internet of Things: Technological Taxonomy Architecture Applications and Open Challenges—A Systematic Review

We are traversing the growing emerging technology paradigms in today’s advanced technological world. In this present era, the Internet of Things (IoT) is extensively used in all sectors. IoT is the ecosystem of smart devices which contains sensors, smart objects, networking, and processing units. These integrated devices provide better services to the end user. IoT is impacting our environment and is becoming one of the most popular technologies. The leading use of IoT in human life is to track activities anywhere at any time. The utmost utilities achieved by IoT applications are decision-making and monitoring for efficient and effective management. In this paper, an extensive literature review on IoT has been done using the systematic literature review (SLR) technique. The main focus areas include commercial, environmental, healthcare, industrial, and smart cities. The issues related to the IoT are also discussed in detail. The purpose of this review is to identify the major areas of applications, different popular architectures, and their challenges. The various IoT applications are compared in accordance with technical features such as quality of service and environmental evaluation. This study can be utilized by the researchers to understand the concept of IoT and provides a roadmap to develop strategies for their future research work.

Smart object recommendation based on topic learning and joint features in the social internet of things

With the extensive integration of the Internet, social networks and the internet of things, the social internet of things has increasingly become a significant research issue. In the social internet of things application scenario, one of the greatest challenges is how to accurately recommend or match smart objects for users with massive resources. Although a variety of recommendation algorithms have been employed in this field, they ignore the massive text resources in the social internet of things, which can effectively improve the effect of recommendation. In this paper, a smart object recommendation approach named object recommendation based on topic learning and joint features is proposed. The proposed approach extracts and calculates topics and service relevant features of texts related to smart objects and introduces the “thing-thing” relationship information in the internet of things to improve the effect of recommendation. Experiments show that the proposed approach enables higher accuracy compared to the existing recommendation methods.

One smart object – three layers of smartphone use in discovering an encapsulated patient’s inner world*

ABSTRACT This paper explores the use of a smartphone within a therapy. It describes its use as a screen object in the service of survival-oriented infantile omnipotence, towards its use as a bridge that facilitated the structuring of internal space and the emergence of nascent capacities for relatedness and introspection. Clinical material from a ten year-long therapy with an adopted girl illustrates the presence of the smartphone on three layers of the therapeutic relationship. First, on a sensory level, the smartphone was used as an almost autistic screening object, but also as an auditory-visual envelope where therapist and patient could be immersed together. Second, on the level of patient-therapist communication and transference relations, the use of the smartphone revived infantile trauma involving the internalisation of a parental gaze that established a distorted internal and external gaze experience, which I termed ‘psychic cross-eyes’. Third, the smartphone served as a ‘third’ object that helped establish our shared observation of reality, and of the patient’s own psyche. By dwelling together, and developing a private language of ‘being-with’ ‘inside’ the phone, while gradually interpreting primitive anxieties and defences in terms of withdrawal from relatedness, we were able to add greater flexibility to the patient’s notion of relatedness, establish her binocular vision, and promote the development of the inner witness function. The paper thus explores the smartphone’s transition from a sterile, screening object, to a communicative, ‘object-seeking’ presence.

Design Methods Review For Smart Product: Objectomy, a New Approach

AbstractDigital artefacts call for new design challenges: they enable services, technology-driven and multidisciplinary never ended processes, uncouple form-function, in a social relationship that must be ecosystem-framed. Then, the usual design mindset is not proper and expected vs unexpected outcomes must be equally studied. A framework of methods, in view of the usual design variables and the new ones called by design of smart objects, is here offered. From that the seeds for the future aid to the design process of smart objects result. Then, Objectomy and one real application case are described.

Smart Railway Traffic Monitoring Using Fiber Bragg Grating Strain Gauges.

There is today ample evidence that fiber Bragg gratings (FBGs) distributed along a railway track can provide robust axle counting and bring numerous assets compared to competing technologies in this practical environment. This work brings two relevant originalities with respect to the state-of-the-art solutions. First, a study of the strain distribution in the rail cross-section is performed to determine the sensitivity according to the charge and the position on the rail. Secondly, the technology is deployed along the rail track as a smart object where the sensor head is composed of four FBG wavelength-division-multiplexed in a single telecommunication-grade optical fiber and interrogated by a miniaturized read-out device. Two FBGs ensure the detection of the train direction and another two bring the required redundancy to reach a safety integrity level (SIL) 4. The read-out unit has been specifically developed for the application and contains a vertical-cavity surface-emitting laser (VCSEL) and a photodiode driven by a high-speed microprocessor unit that processes the data and communicates the useful information, i.e., the number of axles. On-field tests confirm that the proposed approach makes the installation process easier while it democratizes the technology.

Data Sharing with High Security on an Edge Server by Intelligent Internet of Things Users

Abstract: New needs are being created regularly as a result of technology improvements. The internet is one of these tools. To take it a step further, they created the Internet of Things (IoT), which is used to connect smart objects to the internet to facilitate communication. It is linked to the cloud, which stores all of the data created by it, allowing smart devices to operate more efficiently. This further enhances the advantages of the item. Smart devices communicate with edge servers, which are located close to them and capable of performing communication and security functions. With this thesis, an attempt is made to shorten the amount of time it takes to search in a secure cloud on an edge server. The discoveries that have been proposed allow for an extension of time without jeopardizing security issues. This creates a more user-friendly interface for securely engaging with and exchanging data, as well as searching for and downloading data from a secure server in less time, all while maintaining security. Keywords: IoT, Server, Edge, MySQL, Java

Object-centred automated compliance checking: a novel, bottom-up approach

Building Information Modelling (BIM) is changing how built assets are delivered and operated. A built asset is represented as a set of objects, each with an identity, attributes, and relations. This object-oriented nature enables new approaches for ensuring compliance with a range of requirements: e.g. industry guidelines; pro-ject and client-specific requirements; and building codes and standards. Furthermore, bottom-up design ap-proaches are known to be more suitable for quality control and design errors detection. Based on an adapted version of simulated annealing concept, this paper proposes an automated compliance checking classification and identifies a set of desired characteristics these methods should fulfil. It then demonstrates a bottom-up object-centred approach for automated model checking and the corresponding plugin prototype. The approach and the prototype enable four key processes and satisfy all desired characteristics of compliance checking methods including content validation, model completeness, smart object, and design option checking. To demonstrate the feasibility and accuracy of the approach, two case studies are processed using existing BIM objects libraries one of which is created by a major French manufacturer. All four steps were successfully completed, and the results show savings of around 125 minutes per object between the automated approach and traditional manual methods of working.

Automation Assemblages in the Internet of Things: Discovering Qualitative Practices at the Boundaries of Quantitative Change

Abstract We examine consumers’ interactions with smart objects using a novel mixed-method approach, guided by assemblage theory, to discover the emergence of automation practices. We use a unique text data set from the web service IFTTT, (“If This Then That”), representing hundreds of thousands of applets that represent “if–then” connections between pairs of Internet services. Consumers use these applets to automate events in their daily lives. We quantitatively identify and qualitatively interpret automation assemblages that emerge bottom-up as different consumers create similar applets within unique social contexts. Our data discovery approach combines word embeddings, density-based clustering, and nonlinear dimensionality reduction with an inductive approach to the thematic analysis. We uncover 127 nested automation assemblages that correspond to automation practices. Practices are interpreted in terms of four higher-order categories: social expression, social connectedness, extended mind, and relational AI. To investigate the future trajectories of automation practices, we use the concept of the possibility space, a fundamental theoretical idea from assemblage theory. Using our empirical approach, we translate this theoretical possibility space of automation assemblages into a data visualization to predict how existing practices can grow and new practices can emerge. Our new approach makes conceptual, methodological, and empirical contributions with implications for consumer research and marketing strategy.