IoT Applications Research Articles

Enhancing IoT data confidentiality and energy efficiency through decision tree-based self-management

Given the widespread deployment of IoT devices characterized by heterogeneity and energy limits, a greater emphasis on IoT data security within IoT environments has become required. This critical situation encouraged the deployment of lightweight encryption solutions to avoid additional attacks. These solutions, which are based on traditional encryption algorithms, are intended to fulfill the demands of resource-constrained devices while maintaining a high security level. In this research, we provide a novel IoT framework that uses lightweight cryptographic ciphers and the Autonomic Computing paradigm to self-manage the security of IoT devices. Our framework is based on a decision tree technique to guarantee the IoT data confidentiality by selecting and changing in an autonomic manner the most appropriate lightweight encryption algorithm to be used in order to improve energy efficiency by extending the lifespan of IoT devices and to provide an adapted security level according to IoT application type and IoT object state.

Latest Innovations in Internet of Things (IoT): Digital Transformation Across Industries

This research article explores recent advances in IoT technology and its huge impact on various sectors. This research method uses a qualitative research approach involving in-depth interviews and thematic analysis. This research explores key IoT innovations such as wearable devices, smart medical devices, predictive maintenance systems, and IoT-based transportation solutions. The research findings highlight how these innovations are driving digital transformation across industries, leading to improved healthcare delivery, increased manufacturing efficiency, optimized transportation operations, sustainable agricultural practices, and personalized retail experiences. This study also aligns these empirical findings with theoretical frameworks regarding IoT, digital transformation, and industry-specific applications, emphasizing the strategic importance of leveraging IoT as a catalyst for innovation, competitiveness, and value creation. This research provides valuable insights for businesses, policymakers and researchers looking to leverage IoT technology to drive digital transformation and achieve sustainable growth across industries.

Agricultural waste rice husk/poly(vinylidene fluoride) composite: a wearable triboelectric energy harvester for real-time smart IoT applications

Agricultural waste rice husk/poly(vinylidene fluoride) composite: a wearable triboelectric energy harvester for real-time smart IoT applications

Optimizing Requirements Prioritization for IoT Applications Using Extended Analytical Hierarchical Process and an Advanced Grouping Framework

Effective requirement collection and prioritization are paramount within the inherently distributed nature of the Internet of Things (IoT) application. Current methods typically categorize IoT application requirements subjectively into inessential, desirable, and mandatory groups. This often leads to prioritization challenges, especially when dealing with requirements of equal importance and when the number of requirements grows. This increases the complexity of the Analytical Hierarchical Process (AHP) to O(n2) dimensions. This research introduces a novel framework that integrates an enhanced AHP with an advanced grouping model to address these issues. This integrated approach mitigates the subjectivity found in traditional grouping methods and efficiently manages larger sets of requirements. The framework consists of two main modules: the Pre-processing Module and the Prioritization Module. The latter includes three units: the Grouping Processing Unit (GPU) for initial classification using a new grouping approach, the Review Processing Unit (RPU) for post-grouping assessment, and the AHP Processing Unit (APU) for final prioritization. This framework is evaluated through a detailed case study, demonstrating its ability to effectively streamline requirement prioritization in IoT applications, thereby enhancing design quality and operational efficiency.

Research on the Design Method of Rural Lodging Based on the Integration of Architecture and Environment

The concept of modern tourism intelligent application in China is to fully meet the information needs of tourists and customer experience, and the development of intelligent tourism relying on Internet of Things (IoT) is its most basic guarantee condition. With the rise of ethnic village tourism and the change of new consumer lifestyle, B&B shows an explosive development. Tourism consumers are also shifting from hotels to home stays in the process of tourism. Therefore, based on IOT application as the starting point, this paper firstly, gives a more detailed description of the development process and marketing status of home stays, and discusses its various problems. Then, based on the TP theory of ethnic villages, Porter's five forces analysis model and the SWOT analysis method of ethnic villages, the marketing environment of homestays is studied in depth to discover their advantages.The HTOE model develops a marketing mix strategy for B&Bs that meets the actual situation of ethnic village development

Realization of Authenticated One-Pass Key Establishment on RISC-V Micro-Controller for IoT Applications

Internet-of-things networks consist of multiple sensor devices spread over a wide area. In order to protect the data from unauthorized access and tampering, it is essential to ensure secure communication between the sensor devices and the central server. This security measure aims to guarantee authenticity, confidentiality, and data integrity. Unlike traditional computing systems, sensor node devices are often limited regarding memory and computing power. Lightweight communication protocols, such as LoRaWAN, were introduced to overcome these limitations. However, despite the lightweight feature, the protocol is vulnerable to different types of attacks. This proposal presents a highly secure key establishment protocol that combines two cryptography schemes: Elliptic Curve Qu–Vanstone and signcryption key encapsulation. The protocol provides a method to establish a secure channel that inherits the security properties of the two schemes. Also, it allows for fast rekeying with only one exchange message, significantly reducing the handshake complexity in low-bandwidth communication. In addition, the selected schemes complement each other and share the same mathematical operations in elliptic curve cryptography. Moreover, with the rise of a community-friendly platform like RISC-V, we implemented the protocol on a RISC-V system to evaluate its overheads regarding the cycle count and execution time.

Direct Electrodeposition of Electrically Conducting Ni3(HITP)2 MOF Nanostructures for Micro-Supercapacitor Integration.

Micro-supercapacitors emerge as an important electrical energy storage technology expected to play a critical role in the large-scale deployment of autonomous microdevices for health, sensing, monitoring, and other IoT applications. Electrochemical double-layer capacitive storage requires a combination of high surface area and high electronic conductivity, with these being attained only in porous or nanostructured carbons, and recently found also in conducting metal-organic frameworks (MOFs). However, techniques for conformal deposition at micro- and nanoscale of these materials are complex, costly, and hard to upscale. Herein, the study reports direct, one step non-sacrificial anodic electrochemical deposition of Ni3(2,3,6,7,10,11-hexaiminotriphenylene)2 - Ni3(HITP)2, a porous and electrically conducting MOF. Employing this strategy enables the growth of Ni3(HITP)2 films on a variety of 2D substrates as well as on 3D nanostructured substrates to form Ni3(HITP)2 nanotubes and Pt@ Ni3(HITP)2 core-shell nanowires. Based on the optimal electrodeposition protocols, Ni3(HITP)2 films interdigitated micro-supercapacitors are fabricated and tested as a proof of concept.

Enabling low-latency IoT communication for resource-constrained devices with the led cipher and decipher protocol

Block cipher algorithms are crucial for securing applications on resource-constrained devices. This paper introduces the modified light encryption device (MLED) cipher-decipher architecture, specifically designed to accommodate both 64-bit and 128-bit key sizes while maintaining a consistent 64-bit block and data size. MLED comprises 8-step and 12-step processes for MLED-64 and MLED-128 modules, respectively. Each stage involves a four-round operation followed by an add-round key operation. The add constant module (ACM) and mixed column modules (MCMs) within the round operation have been optimized for improved latency and throughput. Performance analysis reveals that MLED-64/128 requires less than 1% of the available slices and operates at 125 MHz on the Artix-7 FPGA. It achieves delays of 7.5 and 12.5 clock cycles for MLED-64 and MLED-128, respectively, translating to throughputs of 1366.5 Mbps and 819.89 Mbps. Additionally, MLED-64/128 exhibits hardware efficiencies of 2.373 and 0.986 Mbps/slice, respectively. Comparative evaluations with existing LED and other block ciphers (BCs) demonstrate that MLED-64/128 achieves significant improvements in latency, throughput, and efficiency, making it a compelling choice for securing resource-constrained IoT applications.

High-Efficiency Class-E Seamlessly Integrated Active-Integrated Antennas of Far-Field SWIPT Base Stations for Batteryless IoT Applications

High-Efficiency Class-E Seamlessly Integrated Active-Integrated Antennas of Far-Field SWIPT Base Stations for Batteryless IoT Applications

A Comprehensive Review: Advances in MIMO Antenna for IOT Application

A Comprehensive Review: Advances in MIMO Antenna for IOT Application

Enhanced authentication and device integrity protection for GDOI using blockchain

AbstractRecent device‐level cyber‐attacks have targeted IoT critical applications in power distribution systems integrated with the Internet communications infrastructure. These systems utilize group domain of interpretation (GDOI) as designated by International Electrotechnical Commission (IEC) power utility standards IEC 61850 and IEC 62351. However, GDOI cannot protect against novel threats, such as IoT device‐level attacks that can modify device firmware and configuration files to create command and control malicious communication. As a consequence, the attacks can compromise substations with potentially catastrophic consequences. With this in mind, this article proposes a permissioned/private blockchain‐based authentication framework that provides a solution to current security threats such as the IoT device‐level attacks. Our work improves the GDOI protocol applied in critical IoT applications by achieving decentralized and distributed device authentication. The security of our proposal is demonstrated against known attacks as well as through formal mechanisms via the joint use of the AVISPA and SPAN tools. The proposed approach adds negligible authentication latency, thus ensuring appropriate scalability as the number of nodes increases.

Energy and dynamics analysis of a single plucking energy harvester for transient-motion-powered IoT applications

This study focuses on a piezo-magneto-elastic structure comprising an economical piezoelectric cantilever and a magnet pair. It is designed for efficient mechanical energy harvesting to power a battery-free motion-sensing IoT system through plucking motions. We conduct a thorough analysis and parametric study to elucidate the energy and dynamic intricacies during operation, specifically under a single plucking excitation. Beginning with a magnetic dipole–dipole model, we present a potential energy profile to intuitively elucidate and quantitatively assess the energy progression throughout a single plucking transient. By meticulously adjusting the setup parameters, the input potential energy can be precisely tuned, ensuring that the energy harvested from a single plucking motion meets the demand of each round of wireless communication. Diverging from previous power-centric investigations of plucking energy harvesters, in which continuous plucking motions are investigated, our approach provides a new perspective on the energy-centric design and transient dynamics of a single plucking motion. The importance of the energy-matching concept considering the subsequent energy-driven electronic modules is emphasized. This insight offers valuable design principles for the effective energy-centric co-design of cyber-electromechanically coupled self-powered IoT systems.

Edge Computing Paradigms: Bridging the Gap between Software Engineering and IoT

This exploration presents a linked profound learning-based asset booking strategy to work on the general execution of edge-incorporated edge IoT networks. For an IoT network to complete a responsibility productively and inside the dispensed time, it should get the best assets from the edge layer. The choice and appropriation of ideal assets rely upon cautious asset booking. Previously, profound learning methods were made to coordinate edge networks with Internet of Things applications while bringing down information transmission inactivity. To further develop an IoT application's general viability and administration quality, it is important to think about a couple of extra measurements, for example, response time, holding up time, and data transmission necessities. A linked procedure using a gated recurrent unit and convolutional neural network is provided to accomplish this improved exhibition. To pick the best assets from the asset pool and disseminate them to the IoT networks, the proposed asset planning model thinks about the qualities and necessities of the assets. This work presents an intensive examination of the connected strategy and exploratory perceptions.

IoT Solutions for Smart Parking- Sigfox Technology

Sigfox technology has emerged as a competitive product in the communication service provider market for approximately a decade. Widely implemented for smart parking solutions across various European countries, it has now gained traction in Germany as well. The technology's successful track record and reputation in the market demonstrate its effectiveness and reliability in addressing the communication needs of IoT applications, particularly in the context of vehicle parking systems. This is noted in terms of a city like Berlin-Germany, for on which the study is conducted. The major challenge being on how to relate the parking techniques in a more user friendly, cost effective and less energy consumpmti0n mode where the questions had at the beginning of the paper, relatively at the end the answers are sought to it via Sigfox and its comparison with other related technologies like LoRA WAN and weightless. But more so future areas of research study is also pointed out on areas which are not clearly identified in this particular research area. This paper entails the pros, cons adaptive, emerging and existing technology study in terms of cloud, big data, Data analytics are all discussed in tandem to Sigfox.

L-shaped reconfigurable band decoupling assisted dual band four port MIMO antenna for 5G and IoT application

Reconfigurable MIMO antennas adapt dynamically to changing communication needs and environmental conditions by changing their emission patterns, polarization, and frequency characteristics. By adjusting the antenna configuration, reconfigurable MIMO systems can prevent interference and improve spectral efficiency, resulting in increased data rates and optimal utilization of available frequency ranges. Furthermore, the antenna parameters are optimized to obtain better results and help to enhance the overall efficiency of the model. In this study, an L-shaped reconfigurable band decoupling assisted dual band four port MIMO antenna is designed. The antenna reconfigurability has been obtained from a band stop filter with a pin diode in the proposed design, with four PIN diodes in each individual antenna for improved isolation. The mutual coupling between the antenna elements has been reduced by inserting a DGS to the antenna elements. The presented reconfigurable four-port L-shaped MIMO antenna is applied over 5G and IoT applications. The overall dimensions of the antenna is 40×40×0.508mm3, which resonates over a dual frequency range between 2.344 GHz for 5G applications and 1.433 GHz for IoT applications. Rogers RT Duroid 5880 substrate with a thickness of 0.508 mm, a dielectric constant of 2.2, a relative permeability of 1, and loss tangents of 0.009 in the proposed design and coplanar waveguide feed line are employed, and an I-shaped stub is used to increase isolation. Defected ground structure (DGS) is used in this work to minimize the antenna mutual coupling issue.

ECONOMIC THEORY AND PRACTICAL IMPACTS OF DIGITAL TRANSFORMATION IN SUPPLY CHAIN OPTIMIZATION

Digital transformation has emerged as a critical driver of innovation and efficiency in supply chain management, reshaping traditional economic paradigms and yielding profound practical implications. This paper delves into the economic theory underpinning digital transformation in supply chain optimization and explores its practical impacts on businesses and industries. In terms of economic theory, we examine the evolution from traditional supply chain models to digitally-enabled ecosystems. The integration of digital technologies such as big data analytics, artificial intelligence, and blockchain revolutionizes supply chain dynamics, enhancing efficiency, reducing costs, and mitigating risks. Drawing on game theory applications, we elucidate strategic interactions among supply chain stakeholders and the implications of digital transformation on their decision-making processes. Turning to practical impacts, we investigate how digital transformation enables enhanced visibility, real-time tracking, and predictive analytics, fostering agility and responsiveness in supply chain operations. Automation and AI-driven insights empower decision-makers to optimize resource allocation and mitigate disruptions effectively. Through case studies, we illustrate the tangible benefits and strategic advantages accrued by organizations embracing digital transformation. However, this transformation is not devoid of challenges. Cybersecurity threats, data privacy concerns, and the integration complexities of legacy systems pose significant hurdles. Addressing these challenges necessitates a holistic approach encompassing technological innovation, regulatory frameworks, and workforce development. Looking ahead, future trends such as blockchain integration, IoT applications, and sustainability initiatives promise further advancements in supply chain optimization. This paper underscores the imperative for ongoing research and adaptation to harness the full potential of digital transformation in reshaping the future of supply chain management. Keywords: Economic Theory, Practical Impacts, Digital Transformation, Supply Chain Optimization.

IoT Protocols: Connecting Devices in Smart Environments

The study delves into the implications of various IoT protocols on communication efficiency and energy consumption within smart environments. The RVRR (routing via respective reducer) protocol emerges as a standout performer, showcasing notable advantages over other conventional protocols. Specifically, the results demonstrate a substantial reduction in communication costs with RVRR, exhibiting improvements of 22.72%, 43.46%, and 49.04% when compared to ILP, SDN-Smart, and R-Drain, respectively. excels in data transmission, achieving commendable reductions in Round-Trip Time (RTT) and enhancing overall energy efficiency. It registers an 18.80% decrease in energy consumption compared to ILP, 28.65% compared to SDN-Smart, and a significant 37% reduction when compared to R-Drain. This suggests that RVRR is adept at optimizing resource usage (routing via respective reducer )and minimizing energy consumption, crucial aspects in the context of IoT applications. The study reveals that RVRR contributes to an extended network lifespan, outperforming other protocols by substantial margins. It showcases a 19.45% improvement over ILP, 39.16% over SDN-Smart, and an impressive 54.60% over R-Drain. This underscores the sustainability and longevity benefits offered by RVRR (routing via respective reducer), making it a promising protocol for efficient and enduring IoT applications within smart environments.

Joint computational and optimized resource allocation in edge computing networks

Fog computing has several undeniable benefits, such as enhancing near-real-time response, reducing transmission costs, and facilitating IoT analysis. This technology is poised to have a significant impact on businesses, organizations, and our daily lives. However, mobile user equipment struggles to handle the complex computing tasks associated with modern applications due to its limited processing power and battery life. Edge computing has emerged as a solution to this problem by relocating processing to nodes at the network’s periphery, which have more computational capacity. With the rapid evolution of wireless technologies and infrastructure, edge computing has become increasingly popular. Nevertheless, managing fog computing resources remains challenging due to resource constraints, heterogeneity, and distant nodes. For delay-sensitive intelligent IoT applications within the fog computing architecture, cooperation and communication processing resources in 6 G and future networks are essential. This study proposes a joint computational and optimized resource allocation (JCORA) technique to accelerate the processing of data from intelligent IoT sensors in a cell association environment. The proposed technique utilizes an uplink and downlink power allocation factor and the shortest job first (SJF) task scheduling system to optimize user fairness and decrease data processing time. This is a complex assignment due to several non-convex limitations. The suggested JCORA-SJF model simultaneously optimizes time partitioning, computing task processing mode selection, and target sensing location selection to maximize the weighted total of task processing and communication performance. The simulation results demonstrate the effectiveness of the proposed JCORA-SJF algorithms, and the system’s scalability is also examined.

A Novel Bootstrapped CMOS Switch with Minimized Sampling and Holding Error Using Sampling Window Error Analysis

This study proposes a novel 6-transistor bootstrapped switch with minimized sampling and holding error obtained through sampling window error analysis for SAR ADC design. The proposed switch design strategically mitigates channel charge injection and minimizes the input signal dependency of on-resistance by optimizing its sizing parameters. To counteract channel charge effects, dummy NMOS and PMOS components are judiciously employed, culminating in a substantial improvement in the effective number of bits (ENOB). The complete analysis of the proposed circuit is done using the Cadence Virtuoso SCL 0.18[Formula: see text][Formula: see text]m CMOS process. For a 51.514[Formula: see text]kHz sinusoidal 1[Formula: see text]V peak-to-peak differential input signal with a 1[Formula: see text]MSPs clock speed, the proposed circuit achieves 2.0141[Formula: see text]mV maximum sampling window error, 0.131[Formula: see text][Formula: see text]W power consumption, 84.67 dB signal-to-noise ratio (SNR), 84.67 signal-to-noise and distortion (SINAD) ratio and 86.02 dB spurious-free dynamic range (SFDR), which produces 13.77 bits ENOB. For the impacts of process variations and mismatch on switch performance, a comprehensive 500-point Monte Carlo (MC) simulation of the proposed bootstrap switch is conducted in this study. Post-layout results show that the proposed circuit is suitable for IoT applications.

Enhancing Smart Communication Security: A Novel Cost Function for Efficient S-Box Generation in Symmetric Key Cryptography

In the realm of smart communication systems, where the ubiquity of 5G/6G networks and IoT applications demands robust data confidentiality, the cryptographic integrity of block and stream cipher mechanisms plays a pivotal role. This paper focuses on the enhancement of cryptographic strength in these systems through an innovative approach to generating substitution boxes (S-boxes), which are integral in achieving confusion and diffusion properties in substitution–permutation networks. These properties are critical in thwarting statistical, differential, linear, and other forms of cryptanalysis, and are equally vital in pseudorandom number generation and cryptographic hashing algorithms. The paper addresses the challenge of rapidly producing random S-boxes with desired cryptographic attributes, a task notably arduous given the complexity of existing generation algorithms. We delve into the hill climbing algorithm, exploring various cost functions and their impact on computational complexity for generating S-boxes with a target nonlinearity of 104. Our contribution lies in proposing a new cost function that markedly reduces the generation complexity, bringing down the iteration count to under 50,000 for achieving the desired S-box. This advancement is particularly significant in the context of smart communication environments, where the balance between security and performance is paramount.