Self-adaptive middleware framework for Internet of Things

To assess the impact of gender and orthodontic qualification length on the awareness, knowledge and usage of orthodontic diagnostic mobile applications, non-diagnostic mobile applications and social media platforms among orthodontic clinicians. Cross-sectional questionnaire-based study. The Republic of Croatia. A total of 92 orthodontic specialists, members of the Croatian Dental Chamber. This study was conducted using a questionnaire distributed via email to orthodontic clinicians between May and July 2022. In total, 92 respondents were divided into groups according to sex and median orthodontic qualification length: more recently qualified (MRQ) with ⩽12 years; and longer qualified (LQ) with >12 years. Nearly one-third of respondents did not have any prior knowledge of mobile applications used as an orthodontic diagnostic tool. MRQ respondents were more interested in using mobile apps as opposed to computer software for digital analysis (P < 0.05). This interest was in a negative correlation with orthodontic qualification length (P < 0.01) and was more prevalent among female respondents (P < 0.001). About one-third (32.6%) of respondents did not use non-diagnostic mobile applications and 44.6% did not use social media platforms. Nearly two-thirds (62%) of the respondents did not promote their work through social media. Male respondents and LQ promoted their work more frequently than others (P < 0.05). The usage of other mobile applications was in a positive correlation with the knowledge and awareness of orthodontic mobile applications (P < 0.05). Orthodontic clinicians lacked knowledge, awareness and the usage of orthodontic diagnostic mobile applications according to sex and orthodontic qualification length. One-third used non-diagnostic mobile applications and less than half used social platforms in daily clinical work.

Responding to rapid growth of Internet of Things (IoT) services and devices, many IoT platforms and frameworks are presented for successful IoT realization. Recently, Open Connectivity Foundation (OCF) which consists of a group of industry leaders emerges to create new standards for IoT platform and deliver an open source implementation and a certification program. IoTivity open-source software framework is one of the project sponsored by the OCF which has been developed to provide interoperability among heterogeneous IoT devices. It enables seamless Device-to-Device (D2D) connectivity and targets various application domains such as home and manufacturing automation, health care, and social networks. IoTivity uses, however, rather lots of memory in view of small devices which have limited hardware resources and runs Real-Time Operating System (RTOS). In this paper, we propose a light-weight IoT framework, RT-OCF that optimizes memory consumption and provides a memory tracer to prevent memory leaks. It has a layered architecture which consists of resource layer, messaging layer, and platform adaptation layer together with modules for security and utility. RT-OCF is able to run not only on Linux but also on TizenRT, an open source RTOS platform runnable on ARTIK053 board. The experiment performed on both Linux and TizenRT shows that more than 20% of peak memory is reduced when compared with IoTivity while preserving a packet latency for GET operations.

PurposeThe Internet of Things (IoT) provides exciting opportunities for the construction industry to solve its time and resource constraints and frequent defaults. This study seeks to identify and rank the perceived importance level of principal research areas associated with the IoT and the construction industry by utilising a scientific mapping tool (i.e. VOSviewer). Such knowledge would enable key drivers for successful adoption of the IoT and digitisation technologies to be outlined. An analysis of key drivers and research trends that facilitates the development of a roadmap for applying the IoT and digital technologies in the construction sector is therefore much needed.Design/methodology/approachAn interpretivist philosophical lens was adopted to analyse published work as secondary data, where each publication represented a unit of analysis. A total of 417 peer-reviewed journal review articles covering the IoT within the construction domain were systematically reviewed using a mixed-methods approach, utilising qualitative-scientometric analyses techniques.FindingsThe results revealed a field of study in a fledgling stage, with a limited number of experts operating somewhat in isolation and offering single-point solutions instead of taking an integrated “holistic” approach. Key publication outlets were identified and the main focus of research undertaken being in the technical areas of smart buildings, smart construction objects and environmental sustainability. The major effects of adopting the IoT within the construction industry were identified as high-speed reporting, complete process control, data explosion leading to deep data analytics, strict ethical and legal expectations. Key drivers of the IoT adoption were outlined: interoperability; data privacy and security; flexible governance structures; proper business planning and models.Practical implicationsThe study benefits researchers and industry practitioners alike. For researchers, the identified gaps reveal areas of high priority in future research. For construction companies, particularly small to medium-sized businesses, the study raises awareness of the latest developments and potential applicability of the IoT in the industry. For government agencies and policymakers, this study offers a point of reference in directing the adoption of the IoT smoothly in the construction sector and provides guidelines and standards for maximising the potential benefits.Originality/valueThe study is the first scientometric review of the existing body of knowledge in the context of application of the IoT in the construction industry. Findings expose knowledge gaps in contemporary research, specifically, a broader consideration of organisational adjustments needed to accommodate the IoT usage, economic analyses and impediments to wider acceptance.

Internet of things (IoT) paradigm is becoming ubiquitous in everyday life. IoT-based systems are increasingly getting deployed in generic household, healthcare, public utilities, etc., related application. The reason for such rapid acceptance is in majority due to the internet's feature of connect from anywhere. However, due to some weaknesses inherent with the internet itself, IoT deployments also face certain challenges. Though there is a growing number of IoT-related reference architectures, frameworks, guidelines, platforms and standards, majority of them are yet to address the concerns due to internet outage. Furthermore, such growing numbers of architectures, frameworks, etc., also means bountiful amounts of both opportunities and risks for IoT vendors and original equipment manufacturers (OEMs). Of course, the IoT-device consumers also run the risks if the purchased products frameworks incompatible. We present One IoT version 2 (v2), an IoT framework and protocol that addresses the internet outage scenario. Similar to version 1 (v1), One IoT v2 is also forward compatible.

The Internet of Things (IoT) enabled technologies to have proliferated due to their abilities to capture and exchange quality information. This empirical study aims to investigate the factors influencing the intention to use IoT services in healthcare by young physicians. An integrated model based on the theory of planned behaviour (TPB) and diffusion of innovations (DOI) theories are drawn upon and analyzed through a Structural Equation Modelling (SEM) with importance-performance map analysis (IPMA). Data were collected through a structured survey questionnaire. The results indicated that behavioural intention to use IoT in healthcare services vastly affected by the attitude and value co-creation. Attitude was found to be a principal determinant followed by the relative advantage towards behavioural intention to use IoT services. The novelty of this empirical study is that the proposed integrated model provides a meaningful application of the young physicians’ intention to use IoT in healthcare in developing countries.

Providing Internet of Things (IoT) environments with service level guarantee is a challenging task for improving IoT application usage experience. We specify in this paper an IoT architecture enabling an IoT Service Level Agreement (iSLA) achievement between an IoT Service Provider (IoT-SP) and an IoT Client (IoT-C). In order to guarantee the IoT applications’ requirements, Quality of Service (QoS) mechanisms should be implemented within all the layers of the IoT architecture. Thus, we propose a specific mechanism for the lowest layer of our service level based IoT architecture (i.e., sensing layer). It is an adaptation of the IEEE 802.15.4 slotted CSMA/CA mechanism enabling to take into consideration the requirements of real-time IoT services. Our access method called QBAIoT (QoS based Access for IoT) extends IEEE 802.15.4 systems by creating a new contention access period for each specified traffic class in the iSLA. Furthermore, due to the huge number of IoT connected devices, self-configuring capability provisioning is necessary for limiting human intervention and total cost of ownership (TCO). Thus, we integrate a self-configuring capability to the QBAIoT access method by implementing the MAPE-K closed control loop within the IoT High Level Gateway (HL-Gw) of our proposed QoS based IoT architecture.

Billions of devices in the Internet of Things (IoT) collect sensitive data about people, creating data privacy risks and breach vulnerabilities. Accordingly, data privacy preservation is vital for sustaining the proliferation of IoT services. In particular, privacy-preserving IoT connects devices embedded with sensors and maintains the data privacy of people. However, common misconceptions exist among IoT researchers, service providers, and users about privacy-preserving IoT. This article refutes five common misconceptions about privacy-preserving IoT concerning data sensing and innovation, regulations, and privacy safeguards. For example, IoT users have a common misconception that no data collection is permitted in data privacy regulations. On the other hand, IoT service providers often think data privacy impedes IoT sensing and innovation. Addressing these misconceptions is essential for making progress in privacy-preserving IoT. This article refutes such common misconceptions using real-world experiments and online survey research. First, the experiments indicate that data privacy should not be perceived as an impediment in IoT but as an opportunity to increase customer retention and trust. Second, privacy-preserving IoT is not exclusively a regulatory problem but also a functional necessity that must be incorporated in the early stages of any IoT design. Third, people do not trust services that lack sufficient privacy measures. Fourth, conventional data security principles do not guarantee data privacy protection, and data privacy can be exposed even if data is securely stored. Fifth, IoT decentralization does not attain absolute privacy preservation.

Since the deployment of the Internet of Things (IoT), it has transformed everyday life by enabling intelligent environments that improve efficiency and automate services in domains such as agriculture, healthcare, smart cities, and industry. However, the rapid proliferation of IoT devices has introduced significant security challenges, largely driven by the heterogeneity of devices, resource constraints, and the increasing exposure of network communications. This work proposes a lightweight security protection mechanism for IoT networks based on trust modelling. The proposed approach integrates machine learning techniques to evaluate IoT node behavior using network-layer (Layer 3) traffic features under different labeling granularities, including binary, categorical, and subcategorical classifications. By focusing on network-layer observations, the model remains applicable across heterogeneous IoT devices while preserving a low computational footprint. In addition, the Common Vulnerability Scoring System (CVSS) is incorporated as a standardized vulnerability severity metric, enabling the integration of probabilistic security evidence with contextual information about potential impact. This combination allows the estimation of trust to reflect not only the likelihood of anomalous behavior but also its associated severity. Experimental evaluation was conducted using a representative IoT traffic dataset, multiple preprocessing strategies, and several classical machine learning models. The results demonstrate that aggregating traffic-based intrusion detection outputs with vulnerability severity metrics enables a more robust, flexible, and interpretable trust estimation process. This approach supports the early identification of potentially compromised nodes while maintaining scalability and efficiency, making it suitable for deployment in heterogeneous IoT environments.

<title>Abstract</title> The Internet of Things (IoT) services have seen rapid growth in recent years. However, existing research has yet to propose a robust method for quantitatively evaluating IoT services, nor has it adequately addressed the impact of cooperation and competition among IoT service providers on pricing strategies. This paper develops a duopolistic Cournot competition model involving data providers, service providers, and consumers. IoT service providers leverage machine learning to train models that generate user-centric IoT services, which they can then market and monetize for profit. We introduce a Logistic-curved service-quality function, with the amount of data used for machine learning as the primary metric for IoT service quality. The competitive behavior between IoT service providers in a Cournot duopoly market is examined, and we derive the optimal IoT service pricing and data procurement strategies that maximize profits for both parties. Next, we explore the possibility of bundling IoT services at discounted prices, categorizing four distinct scenarios based on the relationship between service quality and pricing. We calculate the pricing of IoT service bundles and determine the optimal data purchase quantities for both providers to maximize their profits. Finally, we incorporate a price-fluctuation factor to account for market uncertainty, refining the profit-function model to better reflect real-world market dynamics. The research can provide decision-making references for IoT service pricing, and the pricing mechanism based on machine learning can effectively mitigate the biases caused by price fluctuations.

Internet of Things (IoT) services have grown substantially in recent years. Consequently, IoT service providers (SPs) are emerging in the market and competing to offer their services. Many IoT applications utilize these services in an integrated manner with different Quality-of-Service (QoS) requirements. Thus, the provisioning of end-to-end QoS is getting more indispensable for IoT platforms. However, provisioning the system by using only QoS metrics without considering user experiences is not sufficient. Recently, Quality of Experience (QoE) model has become a promising approach to quantify actual user experiences of services. A holistic design approach that considers constraints of various QoS/QoE metrics together is needed to satisfy requirements of these applications and services. Besides, IoT services may operate in environments with limited resources. Therefore, effective management of services and system resources is essential for QoS/QoE support. This paper provides a comprehensive survey for the state-of-the-art studies on IoT services with QoS/QoE perspective. Our contributions are threefold: (1) QoE-driven architecture is demonstrated by classifying vital components according to QoE-related functions in prior studies, (2) QoE metrics and QoE optimization objectives are classified by corresponding system and resource control problems in the architecture, and (3) QoE-aware resource management e.g., QoE-aware offloading, placement and data caching policies with recent Machine Learning approaches are extensively reviewed.

The Internet of things (IoT) ecosystem has grown exponentially with the convergence of various technologies such as deep learning, sensor systems, and advances in computing platforms. With such a highly pervasive nature of “smart” devices, the nature of data being collected and processed can be increasingly private and require safeguards to ensure the data’s integrity and security. Physically unclonable functions (PUFs) have emerged as a lightweight, viable security protocol in the Internet of Things (IoT) framework. Malicious modeling of PUF architectures has proven to be difficult due to the inherently stochastic nature of PUF architectures. In this work, we show that knowledge of the underlying PUF structure is unnecessary to clone a PUF. We tackle the problem of cloning PUF-based edge nodes in different settings such as unencrypted, encrypted, and obfuscated challenges in an IoT framework. We present a novel non-invasive, architecture-independent, machine learning attack for robust PUF designs and can handle encryption and obfuscation-based security measures on the transmitted challenge response pairs (CRPs). We show that the proposed framework can successfully clone different PUF architectures, including those encrypted using two (2) different encryption protocols in DES and AES and with varying degrees of obfuscation. We also show that the proposed approach outperforms a two-stage brute force attack model. Finally, we offer a machine learning-based countermeasure, a discriminator, which can distinguish cloned PUF devices and authentic PUFs with an average accuracy of 96%. The proposed discriminator can be used for rapidly authenticating millions of IoT nodes remotely from the cloud server.

Since the Internet of Things (IoT) will be entwined with everything we use in our daily life, the consequence of security flaws escalates. Smart objects will govern most of the home appliances and car engines yielding potential disaster scenarios. In this context, successful attacks could lead to chaos and scary scenarios (www.darkreading.com). Unprotected personal information may expose sensitive and embarrassing data to the public and attacks may threaten not only our computers and smart devices, but our intimacy and perhaps our lives too. Because persons and objects will be bonded with each other, user consent becomes critical. Therefore, thing, object, and user Identity will be the focus of future IoT security solutions, yielding a Trust, Security, and Privacy (TSP) paradigm, which may constitute the Achilles' heel of IoT. While security issues are quite straightforward, mainly from background knowledge, privacy issues are far more complex. Privacy constitutes a rather challenging task, even for the m...

This study intends to propose a system to maintain regular diet. The biggest hurdle that all are facing today is absence of health consciousness. Diet is one of the aspects of healthcare. Radio Frequency Identification (RFID) has become a trend in Internet of Things (IoT) healthcare in today’s world. It consists of RFID readers, which automatically reads food information. A web application is used, which allows the individual users to view the name of the food taken and other information like calories of food consumed, date and time of food. The Web Application (iotbeginer) is built with security, so that the user having username and password can only view the information with One Time Password (OTP) sent to their Mobile number or mail id. This system allows user to directly interact with their daily nutritional values. An integrated IoT project ensures that everyone has a healthy balanced diet.

Remote correspondence frameworks are exceedingly disposed to security perils. The critical usages of remote correspondence frameworks are in military, business, human administrations, retail, and transportations. These structures use wired, cell, or ad hoc frameworks. Remote sensor frameworks, actuator frameworks, and vehicular frameworks have gotten a fantastic thought in the open eye and industry. Of late, the Internet of things (IoT) has become broad research thought. The IoT is considered as possible destiny of the Web. In future, IoT will accept a vital activity and change our living styles, standards, similarly to game plans. The use of IoT in different applications is required to rise rapidly in the coming years. The IoT grants billions of devices, society, and organizations to connect with others and exchange information. Due to the extended usage of IoT contraptions, the IoT frameworks are slanted to various security strikes. The presence of successful security and assurance shows that IoT frameworks are incredibly expected to ensure protection, get the chance to control, and decency, among others. In this chapter, a complete assessment on security and insurance issues in IoT frameworks is provided.

Pricing Models for the Internet of Things (IoT): Game Perspectives