IoT-based Applications Research Articles

An Integrated Two-Factor Authentication Scheme for Smart Communications and Control Systems

Fast and reliable authentication is a crucial requirement of communications networks and has various research challenges in an Internet of Things (IoT) environment. In IoT-based applications, as fast and user-friendly access and high security are required simultaneously, biometric identification of the user, such as the face, iris, or fingerprint, is broadly employed as an authentication approach. Moreover, a so-called multi-factor authentication that combines user identification with other identification information, including token information and device identity, is usedto enhance the authentication security level. This paper proposes a novel twofactor authentication scheme for intelligent communication and control systems by utilizing the watermarking technique to incorporate the mobile device authentication component into the user’s facial recognition image. Our proposed scheme offers user-friendliness while improving user security and privacy and reducing authentication information exchange procedures to provide a secure and lightweight schema in real applications. The proposed scheme’s security advantages are validated using the widely accepted Burrows–Abadi–Needham (BAN) logic and experimentally assessed using the Automated Validation of Internet Security Protocols and Applications (AVISPA) simulator tool. Finally, our experimental results show that the proposed authentication scheme is an innovative solution for a smarthome control system, such as a smart lock door operation.

NGHIÊN CỨU XÂY DỰNG THIẾT BỊ HỖ TRỢ QUÁ TRÌNH LUYỆN TẬP PHỤC HỒI CHẤN THƯƠNG CỔ TAY

In this paper, we develop a supportive device to monitor the rehabilitation exercise process for people with disabilities to use their hands. The prototype is designed to include a resistance cable system to support the rehabilitation of the patient's hand motor function. During training, the patient pulls the resistance cable to exercise, and the resistance cable system applies force to the product's sensor block. The sensor block is capable of measuring parameters when force is applied, allowing the calculation of hand force during the patient's training. The hand force data obtained from the sensor block is then sent to a separate IoT-based application. This mobile-platform app is particularly developed for hosting data and providing a view for user to track his/her process of training. Additionally, the product is designed with angle measurement capabilities to track motion coordinates during the patient's hand training. The product is tailored to the physique of Vietnamese individuals. The patient's training results are stored on the Internet and displayed on a mobile application, facilitating the monitoring of training progress, comparing patient training results with standard data, and allowing remote monitoring by the patient's family members or healthcare professionals.

Context Caching for IoT-Based Applications: Opportunities and Challenges

Context Caching for IoT-Based Applications: Opportunities and Challenges

Hierarchical, Attribute and Hash-Based Naming and Forwarding Aided Smart Campus of Things

In order to provide universal ability to access information and communication among Internet-connected devices, the Sustainable Internet of Things (IoT) is on a mission to bring all objects or devices under one roof. Future Internet architecture, especially Information-Centric Networking (ICN), can easily handle the connectivity offered and information created by the massive amount of devices to make it as sustainable IoT applications. Named Data Networking (NDN), one of the several future Internet designs that employ ICN as its foundation, shows promise. NDN integration with IoT-based applications gives solutions to numerous problems. However, this fusion makes accessing the IoT content easier, provided that an effective naming scheme is created to execute this operation. In this work, we build an innovative NDN-based naming scheme (NDN–NS) and put it into practise for consumer, producer, and content routers using our own secure forwarding schemes (NDN–NFS). Due to its scalability, heterogeneity, and security needs, IoT-based Smart Campus (IoT-SC) scenarios are taken into consideration for design and evaluation. We give a complete activity list based on NDN–NS that is split into two communication models (PusH Type Communication (PHTC) and PulL Type Communication (PLTC)) that can be applied to any IoT application. In terms of interest satisfaction rate (ISR), delay, and number of transmissions, we compare the NDN–NFS to legacy NDN. The outcomes demonstrate that NDN–NFS outperforms classic NDN in terms of performance and efficiency.

Sistem Monitoring Nutrisi dan PH Air pada Tanaman Hidroponik Berbasis Internet of Things (IoT)


 
 
 
 Hydroponics is a soilless cultivation method that relies on water and the fulfillment of plant nutritional needs. Nutrient provision is usually done manually, which can be time-consuming. To improve efficiency, an automated system using sensors and an IoT-based application can be implemented. This system utilizes a TDS sensor, pH sensor, and NodeMCU ESP32 to monitor nutrient and pH levels in water. The values are displayed on an LCD screen and sent to the application. If the nutrient content falls below 700 ppm or the pH falls below 5 or above 8, indicating a nutrient deficiency, the nutrient pump can be remotely activated through the application. The pump stops when the nutrient level reaches 1000 ppm or the pH reaches 8. The system provides TDS and pH readings, which have an average error of 3.16% and 2.87%, respectively. This automated system can be used to reading TDS and pH values to assist in providing nutrients to hydroponic plants.
 
 
 

Sustainable Farm Care System Using IoT

Throughout history, the quest for sustenance has been a constant struggle. With the advent of agriculture, humankind has witnessed remarkable progress over the centuries. In the present era, the Internet of Things (IoT) has permeated every sphere of life. Inspired by this, We have embarkedon a project to develop an IoT-based application tailored specifically for the agricultural domain, with a focus on revolutionizing plant management. Plant management encompasses a range of agricultural activities, including seedbed preparation, seed sowing, and plant maintenance. Ourwork aims to automate crucial processes such as water irrigation, water storage management, artificial lighting, and plant security systems. To achieve this, We have devised a dedicated mobile application that interfaces withIoT devices. These interconnected devices form a network, enabling real-time data monitoring and seamless activation of various operations within the system. This ambitious work consists of four major modules. To handle each module effectively, an individual nodemcu device has been allocated. By combining the power of IoT technology and agriculture, this work strives to optimize plant management, enhance productivity, and ultimately contribute to the advancement of this vital field

Underpinning Quality Assurance: Identifying Core Testing Strategies for Multiple Layers of Internet-of-Things-Based Applications

The Internet of Things (IoT) constitutes a digitally integrated network of intelligent devices equipped with sensors, software, and communication capabilities, facilitating data exchange among a multitude of digital systems via the Internet. Despite its pivotal role in the software development life-cycle (SDLC) for ensuring software quality in terms of both functional and non-functional aspects, testing within this intricate software–hardware ecosystem has been somewhat overlooked. To address this, various testing techniques are applied for real-time minimization of failure rates in IoT applications. However, the execution of a comprehensive test suite for specific IoT software remains a complex undertaking. This paper proposes a holistic framework aimed at aiding quality assurance engineers in delineating essential testing methods across different testing levels within the IoT. This delineation is crucial for effective quality assurance, ultimately reducing failure rates in real-time scenarios. Furthermore, the paper offers a mapping of these identified tests to each layer within the layered framework of the IoT. This comprehensive approach seeks to enhance the reliability and performance of IoT-based applications.

Trusted Knowledge Infusion Model-based Recommender System for IoT based B2B applications

The exponential growth and usage of Internet, social sites, and e-commerce results extensive amount of information everywhere. It becomes very difficult for the people to search something, so they go for the offered suggestions which are pertinent for them rather than searching from a potentially overwhelming number of options. Recommender Systems are the solutions for such difficulties. There are many powerful Recommender Systems available for e-commerce, websites, books, tourism, and documents, but recommendations for IoT-based applications need of new discoveries. Traditional recommendations methods are not sufficient for big data based scalable and heterogeneous IoT environment. In this paper, we propose a knowledge infusion model-based hybrid recommendation model for IoT-based B2B applications. The proposed model is analyzed with a real dataset, and the evaluation represents that model performs well in terms execution time, RMSE, precision and F1-score as compared with the existing models.

Toplu Taşıma İçin Nesnelerin İnterneti Yazılımlarının Modellenmesi

The Internet of Things (IoT) is a very promising domain and it is one of the leading technologies used in the public transportation in recent years. However, in addition to the heterogeneity and high complexity problems which are usually observed in the development of IoT systems, the specific needs of public transportation domain make the construction of such systems even harder for the public transportation. This paper proposes the use of a domain-specific modelling language (DSML), called DSML4PT, to facilitate the design and implementation of IoT-based public transportation systems. A metamodel is introduced that enables modeling IoT-based applications according to the different viewpoints and leads to the model-driven engineering of such applications for different IoT-based public transportation platforms. Furthermore, originated from this metamodel, design and implementation of the DSML4PT language with including its syntax and semantics definitions are all discussed in this paper. Use of this DSML supports both the design of the IoT-based public transportation software graphically and the automatic generation of the code required for the implementation. Based on the conducted case study, it has been observed that 80% of a public transportation application can be generated only with using DSML4PT.

A Framework to Implement Data Mining Algorithms with IoT Data to Enable Safe and Rapid Decision-Making Process

Internet of Things (IoT) devices produce a significant amount of data in a real-time manner, it is crucial to make decisions and move forward using the information provided by the sensors that are a part of the IoT environment. In order to handle the analysis of enormous IoT data sets, this interdisciplinary methodology is used. Based on the tasks involving the data and the types of data we deal with during the process, data mining techniques are chosen for IoT data. Again, by choosing the appropriate methods, it is possible to reduce large data sets, clean up the data, and format it as needed. Therefore, the best algorithms for creating, controlling, and monitoring IoT-based applications in various fields are improving IoT process performance. The framework that is suggested will be used to build the appropriate algorithms for IoT Data in related applications, enabling safe and quick decision-making in real time..

Design of Multiplexers for IoT-Based Applications Using Stub-Loaded Coupled-Line Resonators.

This paper presents the design of microstrip-based multiplexers using stub-loaded coupled-line resonators. The proposed multiplexers consist of a diplexer and a triplexer, meticulously engineered to operate at specific frequency bands relevant to IoT systems: 2.55 GHz, 3.94 GHz, and 5.75 GHz. To enhance isolation and selectivity between the two passband regions, the diplexer incorporates five transmission poles (TPs) within its design. Similarly, the triplexer filter employs seven transmission poles to attain the desired performance across all three passbands. A comprehensive comparison was conducted against previously reported designs, considering crucial parameters such as size, insertion loss, return loss, and isolation between the two frequency bands. The fabrication of the diplexer and triplexer was carried out on a compact Rogers Duroid 5880 substrate. The experimental results demonstrate an exceptional performance, with the diplexer exhibiting a low insertion loss of 0.3 dB at 2.55 GHz and 0.4 dB at 3.94 GHz. The triplexer exhibits an insertion loss of 0.3 dB at 2.55 GHz, 0.37 dB at 3.94 GHz, and 0.2 dB at 5.75 GHz. The measured performance of the fabricated diplexer and triplexer aligns well with the simulated results, validating their effectiveness in meeting the desired specifications.

HPCLS-BC: A novel blockchain framework using heterogeneous peer-node and cloud-based ledger storage for Internet of Things applications

Internet of Things (IoT) has gained its widespread application in various fields. Integrating blockchain technology with IoT-based applications has been attracting more research enthusiasm. On the other hand, the number of peer nodes and distributed ledgers is one vital factor for the security of blockchain-based applications. Due to the enormous number of IoT terminal devices, IoT can potentially enhance the security of blockchain, supposing IoT terminal devices play the role of peer nodes. However, the combination of blockchain and IoT faces several challenges. The distributed ledger storage on peer node, which will consume too much storage space of IoT terminal devices, must be solved properly. With the increase of IoT terminal devices for use as peer nodes, especially full nodes, the performance of blockchain will face another challenge. The additional network traffic of IoT terminal devices must also be well-controlled. In this paper, a Heterogeneous Peer-node and Cloud-based Ledger Storage Blockchain (HPCLS-BC) is suggested, in which smart phone, tablet Personal Computer (PC) and conventional computer play the role of peer nodes. Cloud-based ledger storage is proposed to alleviate the pressure of ledger storage on peer nodes, and to make sure the number of peer nodes always equals that of the distributed ledgers. An anti-telecom-fraud scenario is presented to illustrate its application. Comparative experiment results show that HPCLS-BC is competent to blockchain application with lightweight and middleweight pressure, and does not lead to obvious additional network traffic for mobile peer nodes.

Development of smart energy monitoring using NB-IOT and cloud

IoT-based applications are growing in popularity nowadays because they offer effective answers to numerous current problems. In this research, With the aim of decreasing human efforts for monitoring the power units and increasing users' knowledge of excessive electricity usage, an IoT-based electric metre surveillance system utilising an Android platform has been developed. With the help of an Arduino Uno and an optical sensor, the electric analyser pulse is captured. To reduce human mistake and the expense of energy usage, a low-cost wireless network of sensors for digital energy metres is implemented alongside a smartphone application that can autonomously read the metre of the unit. In this research, an intelligent power monitoring system with effective communication modules has been developed to make wise use of the electricity. The controller, NB-IoT connection module, and cloud are the three main components of an IOT-based smart energy metre system. The controller is essential for maintaining the functionality of each component. This solution reduces the need for human involvement in electricity maintenance by connecting energy metres to the cloud using an NB-IoT communication module. The IoT-based metre reading system in the proposed work is created to monitor and analyse the metre reading, and the service provider can cut off the source of electricity whenever the customer fails to pay the monthly bill. It also eliminates the need for human intervention, provides accurate metre reading, and guards against billing errors. The proposed SPM improves the overall accuracy ranges of 7.42, 27.83, and 20% better than DR, OREM, and SLN respectively.

A Visual User Interfaces for Constant Checking of Non-Invasive Physiological Parameters

Objective: this study proposes the development of a wireless graphical interface with a monitoring system that allows for extensive integration with a variety of non-invasive devices. Method: an evaluation framework was created using ISO/IEC25012 parameters to evaluate each of the physiological parameters. Using an ISO standard as a framework to evaluate the quality of the results and analysis parameters such as consistency, accessibility, compressibility, and others, the Cayenne myDevices platform is used to develop a variety of IoT projects. Results: the successful prototype shows that the temperature sensor’s technical capabilities were found to be insufficient for accurately measuring a human’s body temperature, requiring a calibration algorithm. The Cayenne myDevices platform provides a web dashboard for continuous tracking and storage of physiological data. Blynk, an IoT-based application with a graphical user interface, enables real-time visualization and tracking of data from the server and the electronic prototype. Conclusion: findings concluded that free software tools such as Cayenne myDevices, the Blynk App, and Arduino enable integration and reduce the need for expensive applications. Electronic prototypes monitor parameters (e.g., temperature, heart rate, oxygen saturation) were used to monitor COVID-19, cardiovascular, and diabetic patients during exercise. Successful prototypes used Max30100, Mlx90614 sensors, and Esp8266 microcontroller. To avoid giving the patient inaccurate results, the instruments must be carefully selected, so they were assessed to ensure a 95% effectiveness level.

Effect of asymmetric proof mass and size-dependency in flexoelectric nanoharvester subjected to base and restraint forces

The piezoelectric and flexoelectric techniques are of great interest among the scientific fraternity, especially for the design of vibration-based micro/nano energy harvesters. The development of such energy harvesters in the micro/nanoscale has a huge potential, mostly in wireless networks and IoT-based applications. The present work thus formulates novel nanostructure-based analytical models of energy harvesters with asymmetric proof mass considering nonlocal flexoelectricity, geometrical nonlinearity, mid-plane stretching, harmonic base, and axially restraint forces. Using non-classical Euler-Bernoulli nanobeam and Hamilton’s principle, governing differential equation of motion has been derived. Analytical solutions have been obtained to compute the eigenfrequencies and subsequent modes of vibration concerning various systems’ physical and geometric variables. Nonlinear steady-state voltage and power characteristics thereafter have been investigated and studied their local stability and bifurcation for primary and sub-harmonic resonant conditions. The influences of performance factors associated with asymmetrically proof mass, nonlocal elasticity, and time-dependent base and restraint forces on the nonlinear voltage and power output using frequency characteristics criterion. These results have been validated with the findings using COMSOL-2D, and interestingly, mean voltage and power responses from linear models are found to be highly consistent with findings in COMSOL 2D. The present outcome shows how the asymmetric proof mass and nanoscale effect create disparities in harvesting energy performance and, simultaneously, how important their role is to avoid any undesirable structural instability. The present studies together can strengthen the significance of size-dependency and asymmetric proof mass while designing a nanoscale generator in the presence of harmonic excitation.

Joint Traffic Offloading and Aging Control in 5G IoT Networks

The widespread adoption of 5G cellular technology will evolve as one of the major drivers for the growth of IoT-based applications. In this paper, we consider a Service Provider (SP) that launches a smart city service based on IoT data readings: in order to serve IoT data collected across different locations, the SP dynamically negotiates and rescales bandwidth and service functions. 5G network slicing functions are key to lease appropriate amount of resources over heterogeneous access technologies and different site types. Also, different infrastructure providers will charge slicing service depending on specific access technology supported across sites and IoT data collection patterns. We introduce a pricing mechanism based on Age of Information (AoI) to reduce the cost of SPs. It provides incentives for devices to smooth traffic by shifting part of the traffic load from highly congested and more expensive locations to lesser charged ones, while meeting QoS requirements of the IoT service. The proposed optimal pricing scheme comprises a two-stage decision process, where the SP determines the pricing of each location and devices schedule uploads of collected data based on the optimal uploading policy. Simulations show that the SP attains consistent cost reductions tuning the trade-off between slicing costs and the AoI of uploaded IoT data.

DDoS Attack and Detection Methods in Internet-Enabled Networks: Concept, Research Perspectives, and Challenges

In recent times, distributed denial of service (DDoS) has been one of the most prevalent security threats in internet-enabled networks, with many internet of things (IoT) devices having been exploited to carry out attacks. Due to their inherent security flaws, the attacks seek to deplete the resources of the target network by flooding it with numerous spoofed requests from a distributed system. Research studies have demonstrated that a DDoS attack has a considerable impact on the target network resources and can result in an extended operational outage if not detected. The detection of DDoS attacks has been approached using a variety of methods. In this paper, a comprehensive survey of the methods used for DDoS attack detection on selected internet-enabled networks is presented. This survey aimed to provide a concise introductory reference for early researchers in the development and application of attack detection methodologies in IoT-based applications. Unlike other studies, a wide variety of methods, ranging from the traditional methods to machine and deep learning methods, were covered. These methods were classified based on their nature of operation, investigated as to their strengths and weaknesses, and then examined via several research studies which made use of each approach. In addition, attack scenarios and detection studies in emerging networks such as the internet of drones, routing protocol based IoT, and named data networking were also covered. Furthermore, technical challenges in each research study were identified. Finally, some remarks for enhancing the research studies were provided, and potential directions for future research were highlighted.

IoT Data Quality Assessment Framework Using Adaptive Weighted Estimation Fusion.

Timely data quality assessment has been shown to be crucial for the development of IoT-based applications. Different IoT applications' varying data quality requirements pose a challenge, as each application requires a unique data quality process. This creates scalability issues as the number of applications increases, and it also has financial implications, as it would require a separate data pipeline for each application. To address this challenge, this paper proposes a novel approach integrating fusion methods into end-to-end data quality assessment to cater to different applications within a single data pipeline. By using real-time and historical analytics, the study investigates the effects of each fusion method on the resulting data quality score and how this can be used to support different applications. The study results, based on two real-world datasets, indicate that Kalman fusion had a higher overall mean quality score than Adaptive weighted fusion and Naïve fusion. However, Kalman fusion also had a higher computational burden on the system. The proposed solution offers a flexible and efficient approach to addressing IoT applications' diverse data quality needs within a single data pipeline.

Time-efficient distributed virtual network embedding for round-trip delay minimization

Virtual Network Embedding (VNE) aims at determining the placement of virtual services both internally in the edge/cloud infrastructure (EC) and distributed, among distinct ECs, under several resource and network constraints. With regard to Network Function Virtualization technology, a virtual service is referred to as Virtual Network Function (VNF). Modern 5G applications related to the Internet of Things (IoT) are deployed as interconnected VNFs with specific execution sequence in the form of a Service Function Chain (SFC), composing a Virtual Network (VN), and the execution result has to be returned back to the original end-device. Thus, the minimization of the round-trip delay is of major importance to guarantee the performance requirements of IoT-based applications. Additionally, in such a dynamic environment, the re-optimization of VNE is often required to meet the network delay requirements due to end-device mobility, and other orchestration constraints related to the limited edge resources. In this paper, we propose a distributed VNE (DVNE) approach, which focuses on minimizing the round-trip delay. Initially, we introduce an algorithm, namely sV-VNM, that associates every VNF of the VN with a set of candidate ECs that can be hosted onto. Given this initial mapping, an efficient path-based algorithm, namely kSP-DVNE, is proposed to provide the DVNE solution, in polynomial time. Evaluation results show that the sV-VNM algorithm maps the VN onto the ECs, with decreased resource utilization within the infrastructure, while the kSP-DVNE achieves optimal or near optimal solutions regarding the round-trip delay minimization, with a significant reduction in the execution time, compared to existing relevant approaches in the literature.

A systematic review on performance evaluation metric selection method for IoT-based applications

Internet of Things (IoT) has evolved many day-to-day objects into smart objects, which humans can control when they are connected via Internet. Its practical implementation came into existence a few years back. Since the advent of IoT, it has tackled many challenges such as management, tracking, observation, etc. It has contributed to various fields such as Healthcare 4.0, smart grid, smart agriculture, Intelligent Transportation Systems (ITS), smart cities, smart homes, smart cars, and many more. It has applications through almost all domains, but the question arises: the performance evaluating parameters about specific IoT applications to consider to detect flaws in it. As per literature, there exist no such article helps beginners in selecting performance evaluation parameters for IoT-enabled applications. Motivated from the aforementioned facts, this paper presents a survey on performance evaluation metrics’ systematic study for various IoT applications. We then graphically present the comparison of multiple parameters of domains security, energy efficiency, data storage, and network performance. From the analysis, we can infer that, in the smart city, latency is the most usable parameter, i.e., 77%. In contrast, in Healthcare 4.0, equal importance is given to latency and network bandwidth, which is 50%. Also, in Industry 4.0, scalability is the most opted performance parameter by the researchers, which is 100%. The smart grid application uses latency and delay are the most valuable parameters, i.e., 60%.