IoT Entities Research Articles

Relativistic Digital Twin: Bringing the IoT to the future

Complex IoT ecosystems often require the usage of Digital Twins (DTs) of their physical assets in order to perform predictive analytics and simulate what-if scenarios. DTs are able to replicate IoT devices and adapt over time to their behavioral changes. However, DTs in IoT are typically tailored to a specific use case, without the possibility to seamlessly adapt to different scenarios. Further, the fragmentation of IoT poses additional challenges on how to deploy DTs in heterogeneous scenarios characterized by the usage of multiple data formats and IoT network protocols. In this paper, we propose the Relativistic Digital Twin (RDT) framework, through which we automatically generate general-purpose DTs of IoT entities and tune their behavioral models over time by constantly observing their real counterparts. The framework relies on the object representation via the Web of Things (WoT), to offer a standardized interface to each of the IoT devices as well as to their DTs. To this purpose, we extended the W3C WoT standard in order to encompass the concept of behavioral model and define it in the Thing Description (TD) through a new vocabulary. Finally, we evaluated the RDT framework over two disjoint use cases to assess its correctness and learning performance, i.e., the DT of a simulated smart home scenario with the capability of forecasting the indoor temperature, and the DT of a real-world drone with the capability of forecasting its trajectory in an outdoor scenario. Experiments show that the generated DT can estimate the behavior of its real counterpart after an observation stage, regardless of the considered scenario.

SUSIC: A Secure User Access Control Mechanism for SDN-Enabled IIoT and Cyber–Physical Systems

The integration of thriving Information and Communications Technology (ICT) and Cyber Physical Systems (CPS) has spawned several innovative applications such as remote healthcare, smart and intelligent transportation, smart logistics, smart grids, public safety etc. An emerging Software Defined Networks (SDN) technology further enabled to optimize the communication among industrial IoT (IIoT) and CPS entities. Nonetheless, the communication on public channel among different IIoT entities in an SDN-enabled environment may be exposed to various security threats due to wireless and insecure communication channels. To counter these security challenges in the way of wider CPS or IIoT adoption, we propose a novel three-factor authenticated key exchange mechanism (SUSIC) for SDN-enabled IIoT ecosystem. The SUSIC enables a registered user to access real-time data from physical IIoT environment directly after having mutual authentication performed through SDN-enabled controller node. The scheme is proved to be secure under rigorous formal and informal security analysis. Moreover, the simulation results and performance evaluation signifies towards achieving better trade-off between security functionalities and computational overheads comparatively.

Which country recorded the highest digital penetration in 2022-2023?

This paper explores country penetration levels of major Internet applications replacing physical activities. This exploration first aims to learn whether high penetration levels typify large or small countries. Second, it seeks to see whether wealthier countries, among the largest ones by population, lead penetration levels for major Internet applications. Previous data for 2010 showed that smaller countries led globally in their penetration levels, and it was not for wealthier countries to lead among the most prominent countries worldwide. The 2023 data for Internet penetration, for the adoption of smartphones, as well as for the penetration levels for the leading networking platforms (Facebook, Twitter (X), WhatsApp, Instagram, and TikTok) all reveal similar trends: high penetration levels typified both developing and developed countries and small, and usually wealthy, countries achieved the highest penetration scores worldwide. Thus, the trends studied in 2010 were not temporary. Thus, Digital networking is globally and freely available, possibly encouraging interaction and literacy. As far as e-mails are concerned, they are also automatically used by private, institutional, business, and IOT entities. Therefore, the list of leading countries for e-mail use for 2023 consists of developed countries. Online shopping levels depend on the economic status of individuals, so it was for developed countries to lead the 2023 list of online shopping levels.

An Edge Computing Environment for Early Wildfire Detection

Recently, an increasing demand is growing for installing a rapid response system in forest regions to enable an immediate and appropriate response to wildfires before they spread across vast areas. This paper introduces a multilevel system for early wildfire detection to support public authorities to immediately specify and attend to emergency demands. The presented work is designed and implemented within Edge Computing Infrastructure. At the first level; the dataset samples of wildfire represented by a set of video sequences are collected and labelled for training mode purposes. Then, YOLOv5 deep learning model is adopted in our framework to build a trained model for distinguishing the fire event against non-fire events in binary classification. The proposed system structure comprises IoT entities provided with camera sensor capabilities and NVIDIA Jetson Nano Developer kit as an edge computing environment. At the first level, a video camera is employed to assemble environment information received by the micro-controller middle level to handle and detect the possible fire event presenting in the interested area. The last level is characterized as making a decision by sending a text message and snapshot images to the cloud server. Meanwhile, a set of commands are sent to IoT nodes to operate the speakers and sprinklers, which are strategically assumed to place on the ground to give an alarm and prevent wildlife loss. The proposed system was tested and evaluated using a wildfire dataset constructed by our efforts. The experimental results exhibited 98% accurate detection of fire events in the video sequence. Further, a comparison study is performed in this research to confirm the results obtained from recent methods.

Facilitating Semantic Interoperability of Trustworthy IoT Entities in Cultural Spaces: The Smart Museum Ontology

Nowadays, cultural spaces (e.g., museums and archaeological sites) are interested in adding intelligence in their ecosystem by deploying different types of smart applications such as automated environmental monitoring, energy saving, and user experience optimization. Such an ecosystem is better realized through semantics in order to efficiently represent the required knowledge for facilitating interoperability among different application domains, integration of data, and inference of new knowledge as insights into what may have not been observed at first sight. This paper reports on our recent efforts for the engineering of a smart museum (SM) ontology that meets the following objectives: (a) represent knowledge related to trustworthy IoT entities that “live” and are deployed in a SM, i.e., things, sensors, actuators, people, data, and applications; (b) deal with the semantic interoperability and integration of heterogeneous SM applications and data; (c) represent knowledge related to museum visits and visitors toward enhancing their visiting experience; (d) represent knowledge related to smart energy saving; (e) represent knowledge related to the monitoring of environmental conditions in museums; and (f) represent knowledge related to the space and location of exhibits and collections. The paper not only contributes a novel SM ontology, but also presents the updated HCOME methodology for the agile, human-centered, collaborative and iterative engineering of living, reused, and modular ontologies.

Human modeling and interaction in cyber-physical systems: A reference framework

This study focuses on the question of how humans can be inherently integrated into cyber-physical systems (CPS) to reinforce their involvement in the increasingly automated industrial processes. After a use-case oriented review of the related research literature, a human-integration framework and associated data models are presented as part of a multi-agent IoT middleware called CHARIOT. The framework enables human actors to be semantically represented and registered, together with other IoT entities, in a common service directory, thereby facilitating their inclusion in complex service chains. To validate and evaluate the proposed framework, a user study is conducted on a setup where a human and a robot arm collaborate on a “pick-assemble-place” job on a conveyor belt. Based on the human skill set parameters obtained from the user study, online and offline variants of task assignment on the conveyor belt setup are implemented and analyzed over the presented framework. The results illustrate possible efficiency gains through the consolidated online monitoring and control of all cyber-physical system entities, including human actors.

A Pervasive Computational Intelligence based Cognitive Security Co-design Framework for Hype-connected Embedded Industrial IoT

The amplified connectivity of routine IoT entities can expose various security trajectories for cybercriminals to execute malevolent attacks. These dangers are even amplified by the source limitations and heterogeneity of low-budget IoT/IIoT nodes, which create existing multitude-centered and fixed perimeter-oriented security tools inappropriate for vibrant IoT settings. The offered emulation assessment exemplifies the remunerations of implementing context aware co-design oriented cognitive security method in assimilated IIoT settings and delivers exciting understandings in the strategy execution to drive forthcoming study. The innovative features of our system is in its capability to get by with irregular system connectivity as well as node limitations in terms of scares computational ability, limited buffer (at edge node), and finite energy. Based on real-time analytical data, projected scheme select the paramount probable end-to-end security system possibility that ties with an agreed set of node constraints. The paper achieves its goals by recognizing some gaps in the security explicit to node subclass that is vital to our system’s operations.

Data distribution and secure data transmission using IANFIS and MECC in IoT

IoT entities amass a massive quantity of sensing data and transmit it to the cloud for processing as well as reasoning. Such disparate networks raise numerous research questions, say processing, storage, and management of massive data. Though numerous prevailing methodologies are presented, it brings about restricted memory, battery-centered processes, privacy, safety, low processing ability, along with compatibility that directed them to be exposed to disparate attacks, particularly during the data transmission process. To surmount such disadvantages, ‘two’ methods are proposed aimed at IoT data distribution to the cloud utilizing IANFIS in addition to secure transmission of those distributed data utilizing MECC. Initially, the IoT device is authenticated by means of performing registration, login, as well as verification for preventing the device as of unauthorized utilization. Subsequently, the device is accessed to sense the information as of associated objects by utilizing smart sensors; in addition, the communication of disparate IoT sensors is performed by employing the MQTT protocol. Utilizing the IANFIS, this sensed information as of diverse IoT devices is distributed to the specific cloud server. Then by employing the MECC, the data is sent securely to the user. Lastly, the LC is executed by means of HFPGA. To corroborate the proposed system’s effectiveness and correctness, it is compared with existing methodologies and evaluated against relevant metrics.

Internet of Things Security using New Chaotic System and Lightweight AES

The Internet of Things (IoT)services and application were increasing during the last years in several life fields causes need to provide a secure identifier for protecting sensing data passing between IoT sensors/devices and embedded-subsystem connected by networks. This paper was proposed an algorithm for helping in IoT communication security can used in different IOT entities used in unofficial industrial machine to machine (M2M) communications, smart energy-grids, home or buildings and other computing devices. 
 This paper proposed a secure system using new proposed 4D chaotic system combined with the modified lightweight Advanced Encryption Standard (AES). The proposed 4-dimension (4D) chaos system Lyapunov was tested and pass for many initial periods and get a super chaos system (4 positive Lyapunov). Generated chaos keys (used JORN) were used in the lightweight AES and the Secure Hash Algorithm version 3 (SHA3-256). The Lightweight AES was design in case to reduce CPU computation cycles and complexity of AES. Results show that computation time for proposed system decreased (has 145% speedup more). The output of modified lightweight AES encryption System has the good statistical tests near to original AES that can avoid many attacks.

An IoT-Based Anonymous Function for Security and Privacy in Healthcare Sensor Networks.

In the age of the Internet of Things, connected devices are changing the delivery system in the healthcare communication environment. With the integration of IoT in healthcare, there is a huge potential for improvement of the quality, safety, and efficiency of health care in addition to promising technological, economical, and social prospects. Nevertheless, this integration comes with security risks such as data breach that might be caused by credential-stealing malware. In addition, the patient valuable data can be disclosed when the perspective devices are compromised since they are connected to the internet. Hence, security has become an essential part of today’s computing world regarding the ubiquitous nature of the IoT entities in general and IoT-based healthcare in particular. In this paper, research on the algorithm for anonymizing sensitive information about health data set exchanged in the IoT environment using a wireless communication system has been presented. To preserve the security and privacy, during the data session from the users interacting online, the algorithm defines records that cannot be revealed by providing protection to user’s privacy. Moreover, the proposed algorithm includes a secure encryption process that enables health data anonymity. Furthermore, we have provided an analysis using mathematical functions to valid the algorithm’s anonymity function. The results show that the anonymization algorithm guarantees safety features for the considered IoT system applied in context of the healthcare communication systems.

Semantically enabling IoT trust to ensure and secure deployment of IoT entities

Semantically enabling IoT trust to ensure and secure deployment of IoT entities

Semantically enabling IoT trust to ensure and secure deployment of IoT entities

Semantics for the IoT domain have been already introduced for the (semi-)automated deployment of heterogeneous entities. Depending on the level of interoperability and the ability of dynamic expansion of the IoT environment, an application may have to 'decide' (and then select) which devices in that environment are trustworthy for ensuring and securing effective deployment. In the open and distributed IoT, where a large number of heterogeneous entities will be registered, the need to ensure and secure their selection and deployment tasks is highly important. In this paper, an effective modelling approach towards supporting the selection and deployment of IoT entities is presented, based on the notion of trust semantics. Using fuzzy ontologies as an enabler of trust semantics in IoT, this work demonstrates that such semantics, when seamlessly integrated in IoT ontologies, serve as a secure selection key to an IoT application (or service) for selecting, among the available entities, the one(s) that the application should trust for its effective deployment in the specific environment/context.

A Cloud to the Ground: The New Frontier of Intelligent and Autonomous Networks of Things

The Internet of Things paradigm is supporting - and will support - an ever increasing number of services and applications impacting on almost every aspect of our everyday life. The current trend is forecasting IoT to connect tens of billions of objects by 2020 yielding a very high volume of data to be acquired, transmitted, and processed. IoT typically relies on cloud computing to process, analyze, and store the data acquired by IoT entities. Unfortunately, the need to transmit all data from the information producing objects to the cloud for a subsequent processing/analysis phase would require a large bandwidth and increase the latency in the decision making process whenever decisions/reactions must be promptly made by the IoT units. The fog computing paradigm aims to address these problems by extending cloud computing toward the edge of the network. In this direction, this article introduces a novel FC-IoT paradigm designed to move computing, storage, and applications/services close to IoT objects so as to reduce communication bandwidth and energy consumption as well as decision making latency. The proposed IoT-based solution has been designed to have intelligent and autonomous IoT objects that are integrated with an FC and fog networking approach. The distinguishing features of the intelligent FC-IoT platform are low latency, self-adaptation, low energy consumption, and spectrum efficiency.

Semantic Interoperability on the Internet of Things

Internet of Things should be able to integrate an extremely large amount of distributed and heterogeneous entities. To tackle heterogeneity, these entities will need to be consistently and formally represented and managed (registered, aligned, composed and queried) trough suitable abstraction technologies. Two distinct types of these entities are a) sensing/actuating devices that observe some features of interest or act on some other entities (call it ‘smart entities’), and b) applications that utilize the data sensed from or sent to the smart entities (call it ‘control entities’). The aim of this paper is to present the Semantic Smart Gateway Framework for supporting semantic interoperability between these types of heterogeneous IoT entities. More specifically, the paper describes an ontology as the key technology for the abstraction and semantic registration of these entities, towards supporting their automated deployment. The paper also described the alignment of IoT entities and of their exchanged messages. More important, the paper presents a use case scenario and a proof-of-concept implementation.