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Over the last few years, the microfluidics phenomenon coupled with the Internet of Things (IoT) using innovative nano-functional materials has been recognized as a sustainable and economical tool for point-of-care testing (POCT) of various pathogens influencing human health. The sensors based on these phenomena aim to be designed for cost-effectiveness, make it handy, environment-friendly, and get an accurate, easy, and rapid response. Considering the burgeoning importance of analytical devices in the healthcare domain, this review paper is based on the gist of sensing aspects of the microfabricated paper-based analytical devices (μPADs). The article discusses the various used design methodologies and fabrication approaches and elucidates the recently reported surface modification strategies, detection mechanisms viz., colorimetric, electrochemical, fluorescence, electrochemiluminescence, etc. In a nutshell, this article summarizes the state-of-the-art research work carried out over the nano functionalized paper-based analytical devices and associated challenges/solutions in the point of care testing domain., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Paper-based sensors can be exploited to develop low-cost, disposable, and rapid assays for the detection of a large variety of analytes. We report a paper-based sensor system for a point-of-care (POC) nucleic acid amplification test that can quantitatively detect multiple genes from different pathogens. The POC system combines a paper sensor chip and a portable instrument, which is built on an Internet of Things (IoT) platform. The paper-based sensor provides the functions of reagent storage, sample transportation, and nucleic acid amplification. The IoT instrument uses an Arduino microcontroller to control temperature, collect fluorescence images, and store the data in cloud storage via a WiFi network. A compact fluorescence reader was designed to measure fluorescence images of the amplicons during a loop-mediated isothermal amplification reaction in real-time. The real-time detection capability enables the quantitative analysis of target genes. The results show that the paper-based sensor cam distinguish multiple genes of the genomic DNA extracted from Escherichia coli and Campylobacter jejuni, with the concentration as low as 2 × 10 3 copies/μL. The affordable instrument, in conjunction with the disposable paper sensor chip, would have a great potential for POC detections of pathogens., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The electronic paper (E‐paper) has the advantages of low power consumption, flexibility, small form factor, and eye‐friendliness. However, most E‐paper substrates are made by indium tin oxide (ITO) glasses or plastic substrates, which are hard to degrade in the natural environment. Our previous work introduced a self‐powered E‐paper (SPEP) integrated with triboelectric nanogenerator (TENG). Here, a paper‐based SPEP was further demonstrated, driven by a TENG module without any other power module. By combining the self‐powered driving mode and paper substrates, this work showed novel possibilities for E‐paper devices, which provided great potential in future Internet of things (IoT) displays. [ABSTRACT FROM AUTHOR]

Electronic paper (e‐paper) is a reflective display technology with unique advantages, such as bistability, low‐power consumption, and high ambient contrast ratio. These features make e‐paper a promising candidate for future Internet of Things applications. Among different technologies of e‐paper, electrophoretic display (EPD) is the most successful one for commercialization. However, the edge ghosting (also known as the fringing effect) still limits the performance of EPD. Herein, we established a model of particle dynamics of electrophoresis, simulated the edge ghosting of microcapsule EPD, analyzed the edge ghosting effect, and revealed the relationship between thicknesses, dielectric constants of the back binder layer, and the edge ghosting. Two EPD panels with different thicknesses of back binder layer were demonstrated, which verifies the accuracy of this simulation model. With the proposed model, many device mechanisms and product issues can be analyzed and illustrated, which is supposed to guide the researchers in optimizing the device structure design of EPD. [ABSTRACT FROM AUTHOR]

The past decade has been marked by extensive research in the health services sector and their technological modernization. In particular, the Internet of Things (IoT) has shown potential applications in connecting medical devices, sensors and disparate healthcare professionals to provide quality medical services in faraway places. This has improved patient safety, reduced healthcare costs, improved access to healthcare services, and increased operational efficiency in the healthcare sector. An organization of human body wearable sensors, with each having a very precise identifier, could acquire healthiness statistics that are more detailed than what has previously been available for the regular observed data in scientific/clinical contexts. MIoT statistics when stored, analyzed, and evaluated by comparing with the records from extraordinary human beings, permits the customization and innovation of medical services with significant improvements in reduced costs and results. The current study updates the potential medical services of IoT technologies (MIoT). Here, the progression of the adoption of MIoT was reported in terms of latest technologies, medical care and services to solve various health problems. In summary, the present study serves as a comprehensive source of data on various application areas of MIoT with the aim of helping future researchers interested in this field.

The Internet of Things (IoT) has witnessed remarkable growth, leading to the emergence of numerous applications and services. However, energy efficiency remains a critical concern in IoT networks due to the resource-constrained nature of many IoT devices. Energy-efficient routing protocols play a pivotal role in mitigating this challenge, optimizing energy consumption, and extending the operational lifetime of IoT deployments. This survey paper aims to provide a holistic understanding of the state-of-the-art approaches, their characteristics, strengths, limitations, and performance metrics. The survey encompasses a wide range of energy-efficient routing protocols proposed in the literature, including traditional routing protocols adapted for IoT scenarios and protocols specifically tailored for energy optimization. We discuss the impact of different network characteristics on the performance of energy-efficient routing protocols, such as network size, node density, mobility, and heterogeneity. Through this systematic survey, we aim to provide researchers, engineers, and practitioners with a comprehensive overview of energy-efficient routing protocols for IoT networks. The survey findings can serve as a valuable reference for protocol selection, performance evaluation, and the development of novel energy-efficient routing strategies in future IoT deployments. [ABSTRACT FROM AUTHOR]

The world is undergoing a thoughtful revolution with the arrival of the intelligent information era. The central realms accompanying smart living such as transportation, entertainment, healthcare and smart cities are projected to improve service quality assuring a high-end user experience. Future mobile networks are projected to foster the future of ubiquitously connected data-intensive intelligent society powered with complete automation by seamless integrating of all sorts of wireless networks spread over the ground, underwater, air and space. This special issue aims to bring together foremost researchers in academia and engineering from various backgrounds to disseminate to the technical community an outline of emerging technologies, advanced architectures, challenges, open issues and future directions of modern networks in artificial intelligence, internet of things, and blockchain-based applications.

Paper-based sensors overcome the drawbacks of conventional sensors in terms of their flexibility, portability, and stability compared to conventional sensors. Moreover, as a noninvasive bodily fluid, saliva contains various biomarkers related to physical status, which makes it perfectly matched with to use of paper-based sensors to manufacture a convenient and inexpensive disposable sensing device. This review focuses on the recent advances and progress in the design of paper-based salivary sensors and their applications. The first part mainly discusses various paper-based sensors and their advanced compositions, including dipstick assay, lateral flow assay, and microfluidic analytical device. Different detection methods in salivary biomarker detection are specially introduced in the secondary section, then their multiple potential applications and prospects are summarized. The sensor has excellent advantages for saliva detection, provides a reliable platform for point-of-care tests and telemedicine, and epically promotes the development of the medical Internet of Things. [ABSTRACT FROM AUTHOR]

Categorizing Artificial Intelligence of Medical Things (AIoMT) devices within the realm of standard Internet of Things (IoT) and Internet of Medical Things (IoMT) devices, particularly at the server and computational layers, poses a formidable challenge. In this paper, we present a novel methodology for categorizing AIoMT devices through the application of decentralized processing, referred to as "Federated Learning" (FL). Our approach involves deploying a system on standard IoT devices and labeled IoMT devices for training purposes and attribute extraction. Through this process, we extract and map the interconnected attributes from a global federated cum aggression server. The aim of this terminology is to extract interdependent devices via federated learning, ensuring data privacy and adherence to operational policies. Consequently, a global training dataset repository is coordinated to establish a centralized indexing and synchronization knowledge repository. The categorization process employs generic labels for devices transmitting medical data through regular communication channels. We evaluate our proposed methodology across a variety of IoT, IoMT, and AIoMT devices, demonstrating effective classification and labeling. Our technique yields a reliable categorization index for facilitating efficient access and optimization of medical devices within global servers., (© 2024. The Author(s).)

In today's scenario of India most of the youth is preparing for some competitive exam. If we think behind 15–20 years the number of candidates appearing for competitive exams were in thousands but as the population is increasing exponentially in India day by day the number of candidates is increasing in lacks. We can observe by daily newspapers that most of the competitive exams are facing paper leak problems. Although online examination systems are more effective and secure as compared to offline examination systems because it's not easy to open the question paper before the time starts. On the other hand there are also various consequences where the examination process can be hacked online. But the main issue with online examination process is to lack of resources to conduct parallel examination of millions of candidates, lack of techno enabled exam centers in small cities etc. Our focus is to propose a system in which offline examination can be conducted at most of the govt. and private centers in metro cities as well as small techno backward cities with reduced possibility to leak the paper before commencement of examination. [ABSTRACT FROM AUTHOR]

Purpose -- Even if it is often accepted that smart hotels are built on networks of technological devices, there is currently no consensus among researchers as to what level of technology is required to define a smart hotel. Based on the above-mentioned assumption that smart hotels are built on a network of technological devices, this paper aims to understand how smart hotels can be conceptualised based on customer preferences. Methodology/Design/Approach -- To achieve this goal, the paper conceptualises smart hotels as a service network in which the customer comes into contact with a variety of technological and traditional touchpoints on site. This conceptualisation allows the researcher to observe customer preferences at different touchpoints and identify the technologies that are central to the development of the customer experience. Findings -- The results show that the ideal customer journey includes both traditional and technological touchpoints and that artificial intelligence is of central importance for the development of the smart hotel concept. Originality of the research -- The methodological approach taken in this paper enables researchers and practitioners to easily visualise and identify important patterns in the customer journey, facilitating the task of identifying the most relevant touchpoints in complex service networks, such as smart hotels. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) architectures generally focus on providing consistent performance and reliable communications. The convergence of IoT, edge, fog, and cloud aims to improve the quality of service of applications, which does not typically emphasize energy efficiency. Considering energy in IoT architectures would reduce the energy impact from billions of IoT devices. The research presented in this paper proposes an optimization framework that considers energy consumption of nodes when selecting a node for processing an IoT request in edge-fog-cloud layered architecture. The IoT use cases considered in this paper include smart grid, autonomous vehicles, and eHealth. The proposed framework is evaluated using CPLEX simulations. The results provide insights into mechanisms that can be used to select nodes energy-efficiently whilst meeting the application requirements and other network constraints in multi-layered IoT architectures. [ABSTRACT FROM AUTHOR]

In the past few years the use of IoT devices has grown exponentially. When it comes to working with them, we find a series of problems that are not easy to solve. On the one hand, the simple fact of communicating with those devices can be problematic since they can use different types of technologies regarding that communication. On the other hand, these types of devices usually aim to perform their function using the lowest possible energy, meaning they have certain constraints in terms of performance. Trying to work with these devices in high-availability environments becomes difficult because of those restraints. This paper introduces digital dice, a virtual representation of IoT devices and cyber-physical systems based on microservices that uses the standard established by the W3C, the Web of Things, as the underlying framework to declare its possible interactions. The article puts forward the different strategies that Digital Dice uses to mitigate the problems raised. Furthermore, we contrast the performance of Digital Dice with using the devices directly, demonstrating its advantages in a process that requires High Availability. [ABSTRACT FROM AUTHOR]

This work aims to explore the potentialities of an end-user personalisation platform in industrial settings. In such a context, stakeholders with different roles and competencies collaborate to manage and control an environment where legacy machines coexist and interact with newer ones. Our goal is to provide a rule-based tool that allows end-users to build personalised solutions to respond quickly to the dynamic needs of factories. We report on a case study in the paper factory domain, in which the industrial aspects identified with expert stakeholders through interviews have been simulated and addressed through an extension of a personalisation platform. A first user test of the resulting environment has been carried out with a representative set of users, and has provided useful and encouraging feedback in terms of the potentialities of the proposed approach in industrial contexts. [ABSTRACT FROM AUTHOR]

Abstract In the field of technology management, methods have been developed to detect technologies that are important in industry by analyzing massive numbers of documents. Such methods have been applied to the field of the Internet of Things as well to investigate technological trends. The Internet of Things consists of several conventional concepts, such as radio frequency identification, near field communication, and sensor networks. However, no research compares these technologies by analyzing massive quantities of papers and patents. Thus, in this study, we explored the research areas of technologies related to the Internet of Things, for which there are opportunities for commercialization in the near future. We also discuss potential applications of these technologies in diverse systems. Highlights • Extracting commercialization opportunities of the Internet of Things • Measuring text similarity between papers and patents • Results were good agreement with public government document contains IoT policy. • Extracted important technological options even experts did not discuss. [ABSTRACT FROM AUTHOR]

Centralized access control systems are unsuitable for IoT due to their resource-constrained, heterogeneous, and dynamic nature. Blockchain-assisted decentralized access control systems exist for IoT, but those approaches are tokenization-based. In some cases, IoT devices are not part of the blockchain network due to which they cannot interact with the access control system directly. Instead, they need a trusted admin, management hub, or a fog node for permissions verification and access to resources. This paper presents a smart contract and blockchain-assisted framework for the access control systems in the IoT enterprise environment, called ACS-IoT. In the proposed framework, resource-constrained IoT devices belong to the blockchain network. Therefore, these devices can directly access the permitted resources without any centrally administered authority and management hub's verification. We used smart contract and Ethereum blockchain for the new framework. Smart contract allows automated enforcement of access policies and serves as an autonomous agent running exactly as programmed. The proposed framework is validated through implementation of the proof of concept, and implemented prototype is deployed and tested on the Ethereum test network. The obtained results confirm that usage of blockchain and smart contract can be used as access management technology in the IoT enterprise environment. [ABSTRACT FROM AUTHOR]

Climate-change-induced unpredictable weather patterns are adversely affecting global agricultural productivity, posing a significant threat to sustainability and food security, particularly in developing regions. Wealthier nations can invest substantially in measures to mitigate climate change's impact on food production, but economically disadvantaged countries face challenges due to limited resources and heightened susceptibility to climate change. To enhance climate resilience in agriculture, technological solutions such as the Internet of Things (IoT) are being explored. This paper introduces a digital twin as a technological solution for monitoring and controlling temperatures in a greenhouse tunnel situated in Stellenbosch, South Africa. The study incorporates an aeroponics trial within the tunnel, analysing temperature variations caused by the fan and wet wall temperature regulatory systems. The research develops an analytical model and employs a support vector regression algorithm as an empirical model, successfully achieving accurate predictions. The analytical model demonstrated a root mean square error (RMSE) of 2.93 °C and an R 2 value of 0.8, while the empirical model outperformed it with an RMSE of 1.76 °C and an R 2 value of 0.9 for a one-hour-ahead simulation. Potential applications and future work using these modelling techniques are then discussed. [ABSTRACT FROM AUTHOR]

Baggage mishandling has received much attention by airport operators. Traditional baggage tracking methods (e.g., manual, barcode, and radio-frequency identification) have not been able to deal with the challenge of baggage mishandling due to their unreliable and inefficient performance. Baggage data comprises sensitive personal information, linking individuals to their personal details and travel history, with the potential to expose security vulnerabilities. This paper proposes a smart baggage tracking system based on surveillance and blockchain technology for mitigation of baggage mishandling at airports. Surveillance including a network of airport cameras is used to recognize and monitor locations of baggage and passengers. Blockchain technology is utilized to manage and process baggage and passenger databases, guaranteeing the security, privacy, and transparency of baggage information. Surveillance-captured images of baggage and passengers undergo processing through computer vision algorithms to determine the current whereabouts of baggage, subsequently synchronized and updated within the blockchain storage. Additionally, a user interface is developed to present real-time baggage tracking information. Preliminary experiments have demonstrated the applicability of the smart baggage tracking system for airports. [ABSTRACT FROM AUTHOR]

Over the last few years, the microfluidics phenomenon coupled with the Internet of Things (IoT) using innovative nano-functional materials has been recognized as a sustainable and economical tool for point-of-care testing (POCT) of various pathogens influencing human health. The sensors based on these phenomena aim to be designed for cost-effectiveness, make it handy, environment-friendly, and get an accurate, easy, and rapid response. Considering the burgeoning importance of analytical devices in the healthcare domain, this review paper is based on the gist of sensing aspects of the microfabricated paper-based analytical devices (μPADs). The article discusses the various used design methodologies and fabrication approaches and elucidates the recently reported surface modification strategies, detection mechanisms viz., colorimetric, electrochemical, fluorescence, electrochemiluminescence, etc. In a nutshell, this article summarizes the state-of-the-art research work carried out over the nano functionalized paper-based analytical devices and associated challenges/solutions in the point of care testing domain. [ABSTRACT FROM AUTHOR]

E-learning plays a key role in an individual's mental growth and a nation's future in today's competitive world. Traditional learning is teacher-centered, and teaching the same subject well every time is tough. Traditional teaching approaches can't be used everywhere. By mitigating this flaw in traditional learning, E-learning becomes a potent weapon for intellectual progress and contributes to intellectual society. Traditional learning's high prices, set hours, and limited classroom access may be avoided through e-learning. People are India's major strength as the world's first and biggest democracy. E-Learning benefits these countries and plays a crucial role in establishing intellectual think tanks that can be utilised by the entire world for constant growth and an aggressive reaction to other nations' logical cultures. In this regard, a more focused approach has been considered on introducing new e-learning methodologies, priorities set for each methodology for easy e-learning, and upcoming technological trends in the field of elearning such as Mobile learning, Microlearning, Beacon learning, Internet of Things(IoT), Cloud-based e-learning, Gamification, and others. [ABSTRACT FROM AUTHOR]

Preserving customers' expectations and understanding factors affecting their purchasing decisions are crucial in designing effective marketing and advertising strategies. However, constantly and swiftly changing the customers' interests and consumption behaviors make it inevitable to utilize sophisticated tools and approaches based on advanced technologies. Among them, by measuring the customers' physiological and neural signals, studying the customers' cognitive and affective responses to marketing stimuli, neuromarketing provides deep insight into the customers' motivations, preferences, and decisions. Recently, the internet of everything (IoE) has brought many new opportunities to the industry and has attracted the attention of many researchers in recent years. The main objective of this paper is to address how the IoE would empower neuromarketing techniques. Hence, an in-depth understanding of current research issues as well as emerging trends would help meet this goal. In this paper, a comprehensive review has been done by reviewing numerous journal and conference papers from various academic databases (sciencedirect.com, IEEE Xplore, Springer, Elsevier, Wiley, ACM digital library) based on applying various filtrations on specific keywords to identify and categorize the IoE devices in the neuromarketing field. In particular, we discussed the importance and the applications of IoE gadgets and devices, especially wearable medical technologies in eight neuromarketing techniques. Finally, we described critical existing challenges and limitations in neuromarketing and IoE gadgets that researchers have dealt with in this field of research. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT), projected to exceed 30 billion active device connections globally by 2025, presents an expansive attack surface. The frequent collection and dissemination of confidential data on these devices exposes them to significant security risks, including user information theft and denial-of-service attacks. This paper introduces a smart, network-based Intrusion Detection System (IDS) designed to protect IoT networks from distributed denial-of-service attacks. Our methodology involves generating synthetic images from flow-level traffic data of the Bot-IoT and the LATAM-DDoS-IoT datasets and conducting experiments within both supervised and self-supervised learning paradigms. Self-supervised learning is identified in the state of the art as a promising solution to replace the need for massive amounts of manually labeled data, as well as providing robust generalization. Our results showcase that self-supervised learning surpassed supervised learning in terms of classification performance for certain tests. Specifically, it exceeded the F1 score of supervised learning for attack detection by 4.83% and by 14.61% in accuracy for the multiclass task of protocol classification. Drawing from extensive ablation studies presented in our research, we recommend an optimal training framework for upcoming contrastive learning experiments that emphasize visual representations in the cybersecurity realm. This training approach has enabled us to highlight the broader applicability of self-supervised learning, which, in some instances, outperformed supervised learning transferability by over 5% in precision and nearly 1% in F1 score. [ABSTRACT FROM AUTHOR]

Nowadays, modern industries generate their energy by using renewable solar. The rapid increase in photovoltaic (PV) module installations provides a better energy conversion, but their life cycle is a major concern. This research paper focuses on the recycling process for solar PV modules using the Internet of Things in industries. The smart bin with the Internet of Things (IoT) utilizes a machine learning approach to collect solar waste. The proposed smart bin uses k-Nearest Neighbor's algorithm (k-NN) and Long Short-Term Memory (LSTM), a network-based learning algorithm. These algorithms are useful in updating the level of the bin via alert messages. It also helps in identifying the type of waste material. The k-NN algorithm provides 83% accuracy in predicting the bin level in a real-time testing environment. The smart dust bin classifies the waste materials, and notifies its level to the collection center through the IoT platform when the level reaches a prescribed threshold, the signal corresponding to the level is passed to the common waste collection unit. IoT is connected to Cloud Server. It helps to predict the level of the smart bin. Delay is introduced in the order of 3-8 s while the alert message is sent to the common waste collection unit. The system monitors the smart bin levels and sends the notifications to alert and initiate the collection unit. Real-time mobile app monitors the bin's level and location. The cloud IoT analytics analyze the solar e-waste in a different locations in industries.The proposed system works better and provides accurate results by using machine learning approach., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We propose a method for printing a radio frequency identification (RFID) tag on paper as a sensor for a wearable bracelet via the Internet of Things (IoT) to allow people to enter a secure area. The RFID paper tag is first printed out when entering the area and then can be torn up by hand when leaving. It can be easily destroyed and cannot be used again, thus preventing privacy violations. This paper tag technology has a low cost, high confidentiality, and low environmental impact. Before using RFID in this manner, it was first necessary to develop an appropriate antenna for use with the RFID tag. In this study, computer simulation software was used to select the best antenna from seven samples that matched the predetermined frequency requirements and obtain S-parameters that matched the desired frequency (924 MHz). This antenna can be used for a removable RFID tag printed directly on a wearable paper bracelet. Reliability experiments were conducted with printed antennas for RFID tags printed directly on paper. This wearable bracelet device can be easily removed to ensure personal security and has industrial applications combining RFID and the IoT. [ABSTRACT FROM AUTHOR]