Internet of Things

Development and Application of IoT Monitoring Systems for Typical Large Amusement Facilities

The advent of internet of things (IoT) technology has ushered in a new dawn for the digital realm, offering innovative avenues for real-time surveillance and assessment of the operational conditions of intricate mechanical systems. Nowadays, mechanical system monitoring technologies are extensively utilized in various sectors, such as rotating and reciprocating machinery, expansive bridges, and intricate aircraft. Nevertheless, in comparison to standard mechanical frameworks, large amusement facilities, which constitute the primary manned electromechanical installations in amusement parks and scenic locales, showcase a myriad of structural designs and multiple failure patterns. The predominant method for fault diagnosis still relies on offline manual evaluations and intermittent testing of vital elements. This practice heavily depends on the inspectors' expertise and proficiency for effective detection. Moreover, periodic inspections cannot provide immediate feedback on the safety status of crucial components, they lack preemptive warnings for potential malfunctions, and fail to elevate safety measures during equipment operation. Hence, developing an equipment monitoring system grounded in IoT technology and sensor networks is paramount, especially considering the structural nuances and risk profiles of large amusement facilities. This study aims to develop customized operational status monitoring sensors and an IoT platform for large roller coasters, encompassing the design and fabrication of sensors and IoT platforms and data acquisition and processing. The ultimate objective is to enable timely warnings when monitoring signals deviate from normal ranges or violate relevant standards, thereby facilitating the prompt identification of potential safety hazards and equipment faults.

A Motivational Technology Perspective on the Use of Smart Wrist-Worn Wearables for Postpartum Exercise and Weight Management

Exercise and weight management is crucial in preventing postpartum depression and long-term obesity that carries the risk of chronic illness among postpartum women. Although communication devices, such as a smart wrist-worn wearable (SWW), can help users be more physically active, the extent to which postpartum women might benefit from this technology is unknown. We examined how SWWs promoted exercise and helped postpartum women return to pre-pregnancy weight. We tested a model based on the premise that a motivational device that prompts users to engage with it can establish healthy daily routines. An online survey of 309 postpartum women who were living in the United States and were current users of SWWs revealed that the device encouraged them to spend time completing workout goals. Technological affordances (i.e. customization, navigability, and interactivity) and subsequent user engagement with the device positively predicted total workout hours among postpartum women. We present practical implications for postpartum care programs and smart wearable developers.

Managing open loop water resource value chain through IoT focused decision and information integration (DII) modelling using fuzzy MCDM approach

Water is a limited and invaluable resource that is essential for human survival. Negligence and unregulated water use have brought about a global water crisis. Proper management with a relevant decision and information integration approach can aid water to continue as a renewable resource. The water and wastewater industry must shift from outmoded, inefficient techniques to more sustainable, data-driven solutions to address water concerns and improve public health. The Internet of Things (IoT) has emerged as an innovative strategy for decision and information integration to drive an open-loop Water Value Chain (WVC) efficiently. The IoT-driven network allows objects to connect and communicate, gather data in real-time, analyze data and develop reasonable decision - making insights instantaneously. This study aims to find the enablers of IoT for an open-loop WVC. It examines 25 factors for IoT implementation in the open-loop WVC. The 25 factors are clustered into seven enablers using Principal Component Analysis (PCA). These principal components are analyzed by employing a Multi-Criteria Decision Making (MCDM) approach, i.e., the Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), which helps to find the cause-effect relationship to prioritize the enablers. The fuzzy set theory is used to address the uncertainty and vagueness in experts' opinions and data deficiency problems. The study reveals that the Ecosystem of an IoT network, IoT network configuration and adaptation and data mobility in an IoT network are the most prominent enablers to consider for the implementation of IoT in an open loop WVC. The study may be helpful for regulatory agencies and enterprises in water distribution and processing for identifying and prioritizing the potential enablers of IoT in an open-loop WVC.

Communicating Supraparticles to Enable Perceptual, Information-Providing Matter

Materials are the fundament of the physical world, whereas information and its exchange are the centerpieces of the digital world. Their fruitful synergy offers countless opportunities for realizing desired digital transformation processes in the physical world of materials. Yet, to date, a perfect connection between these worlds is missing. From the perspective, this can be achieved by overcoming the paradigm of considering materials as passive objects and turning them into perceptual, information-providing matter. This matter is capable of communicating associated digitally stored information, for example, its origin, fate, and material type as well as its intactness on demand. Herein, the concept of realizing perceptual, information-providing matter by integrating customizable (sub-)micrometer-sized communicating supraparticles (CSPs) is presented. They are assembled from individual nanoparticulate and/or (macro)molecular building blocks with spectrally differentiable signals that are either robust or stimuli-susceptible. Their combination yields functional signal characteristics that provide an identification signature and one or multiple stimuli-recorder features. This enables CSPs to communicate associated digital information on the tagged material and its encountered stimuli histories upon signal readout anywhere across its life cycle. Ultimately, CSPs link the materials and digital worlds with numerous use cases thereof, in particular fostering the transition into an age of sustainability.

Power-Efficient Multisensory Reservoir Computing Based on Zr-Doped HfO2 Memcapacitive Synapse Arrays

Hardware implementation tailored to requirements in reservoir computing would facilitate lightweight and powerful temporal processing. Capacitive reservoirs would boost power efficiency due to their ultralow static power consumption but have not been experimentally exploited yet. Here, this work reports an oxide-based memcapacitive synapse (OMC) based on Zr-doped HfO2 (HZO) for a power-efficient and multisensory processing reservoir computing system. The nonlinearity and state richness required for reservoir computing could originate from the capacitively coupled polarization switching and charge trapping of hafnium-oxide-based devices. The power consumption (≈113.4 fJ per spike) and temporal processing versatility outperform most resistive reservoirs. This system is verified by common benchmark tasks, and it exhibits high accuracy (>94%) in recognizing multisensory information, including acoustic, electrophysiological, and mechanic modalities. As a proof-of-concept, a touchless user interface for virtual shopping based on the OMC-based reservoir computing system is demonstrated, benefiting from its interference-robust acoustic and electrophysiological perception. These results shed light on the development of highly power-efficient human-machine interfaces and machine-learning platforms.

Intelligent Digital Twins for Personalized Migraine Care

Intelligent digital twins closely resemble their real-life counterparts. In health and medical care, they enable the real-time monitoring of patients, whereby large amounts of data can be collected to produce actionable information. These powerful tools are constructed with the aid of artificial intelligence, machine learning, and deep learning; the Internet of Things; and cloud computing to collect a diverse range of digital data (e.g., from digital patient journals, wearable sensors, and digitized monitoring equipment or processes), which can provide information on the health conditions and therapeutic responses of their physical twins. Intelligent digital twins can enable data-driven clinical decision making and advance the realization of personalized care. Migraines are a highly prevalent and complex neurological disorder affecting people of all ages, genders, and geographical locations. It is ranked among the top disabling diseases, with substantial negative personal and societal impacts, but the current treatment strategies are suboptimal. Personalized care for migraines has been suggested to optimize their treatment. The implementation of intelligent digital twins for migraine care can theoretically be beneficial in supporting patient-centric care management. It is also expected that the implementation of intelligent digital twins will reduce costs in the long run and enhance treatment effectiveness. This study briefly reviews the concept of digital twins and the available literature on digital twins for health disorders such as neurological diseases. Based on these, the potential construction and utility of digital twins for migraines will then be presented. The potential and challenges when implementing intelligent digital twins for the future management of migraines are also discussed.

Recent Advances in Nanomaterials Used for Wearable Electronics

In recent decades, thriving Internet of Things (IoT) technology has had a profound impact on people's lifestyles through extensive information interaction between humans and intelligent devices. One promising application of IoT is the continuous, real-time monitoring and analysis of body or environmental information by devices worn on or implanted inside the body. This research area, commonly referred to as wearable electronics or wearables, represents a new and rapidly expanding interdisciplinary field. Wearable electronics are devices with specific electronic functions that must be flexible and stretchable. Various novel materials have been proposed in recent years to meet the technical challenges posed by this field, which exhibit significant potential for use in different wearable applications. This article reviews recent progress in the development of emerging nanomaterial-based wearable electronics, with a specific focus on their flexible substrates, conductors, and transducers. Additionally, we discuss the current state-of-the-art applications of nanomaterial-based wearable electronics and provide an outlook on future research directions in this field.

Autonomous Vehicles Enabled by the Integration of IoT, Edge Intelligence, 5G, and Blockchain

The wave of modernization around us has put the automotive industry on the brink of a paradigm shift. Leveraging the ever-evolving technologies, vehicles are steadily transitioning towards automated driving to constitute an integral part of the intelligent transportation system (ITS). The term autonomous vehicle has become ubiquitous in our lives, owing to the extensive research and development that frequently make headlines. Nonetheless, the flourishing of AVs hinges on many factors due to the extremely stringent demands for safety, security, and reliability. Cutting-edge technologies play critical roles in tackling complicated issues. Assimilating trailblazing technologies such as the Internet of Things (IoT), edge intelligence (EI), 5G, and Blockchain into the AV architecture will unlock the potential of an efficient and sustainable transportation system. This paper provides a comprehensive review of the state-of-the-art in the literature on the impact and implementation of the aforementioned technologies into AV architectures, along with the challenges faced by each of them. We also provide insights into the technological offshoots concerning their seamless integration to fulfill the requirements of AVs. Finally, the paper sheds light on future research directions and opportunities that will spur further developments. Exploring the integration of key enabling technologies in a single work will serve as a valuable reference for the community interested in the relevant issues surrounding AV research.

IoT-Oriented Wireless Sensor Network and Sports Dance Movement Perception

The Internet of Things needs to connect different types of sensors in accordance with the agreement, and different agreements can be used for information and information exchange systems, which can facilitate the identification and control of intelligent systems. In many scenarios, location service application data are very important for obtaining accurate location information about nodes. In this paper, a wrist motion sensing sensor based on the PVDF piezoelectric film is developed. To realize the monitoring of wrist motion signals, this paper designs and manufactures a series of PVDF noninvasive sensors for motion perception. The characteristics of sports dance movements are reflected in the coordination between men and women, and the dance posture and movements must be synchronized with the music according to the level of music rhythm structure. The transfer of center of gravity is the main driving force of sports, and the gait of athletes is related to the transfer of center of gravity. Posture stability is the basic element of sports dance training. Only on this basis can it be possible to develop specific motion function trajectories and technical action forms.

Security Best Practices: A Critical Analysis Using IoT as a Case Study

Academic research has highlighted the failure of many Internet of Things (IoT) product manufacturers to follow accepted practices, while IoT security best practices have recently attracted considerable attention worldwide from industry and governments. Given current examples of security advice, confusion is evident from guidelines that conflate desired outcomes with security practices to achieve those outcomes. We explore a surprising lack of clarity, and void in the literature, on what (generically) best practice means, independent of identifying specific individual practices or highlighting failure to follow best practices. We consider categories of security advice, and analyze how they apply over the lifecycle of IoT devices. For concreteness in discussion, we use iterative inductive coding to code and systematically analyze a set of 1013 IoT security best practices, recommendations, and guidelines collated from industrial, government, and academic sources. Among our findings, of all analyzed items, 68% fail to meet our definition of an (actionable) practice, and 73% of all actionable advice relates to the software development lifecycle phase, highlighting the critical position of manufacturers and developers. We hope that our work provides a basis for the community to better understand best practices, identify and reach consensus on specific practices, and find ways to motivate relevant stakeholders to follow them.

The Need for Smart Architecture Caused by the Impact of COVID-19 upon Architecture and City: A Systematic Literature Review

The recent pandemic era of COVID-19 has shown social adjustment on a global scale in an attempt to reduce contamination. In response, academic studies relating to smart technologies have increased to assist with governmental restrictions such as social distancing. Despite the restrictions, architectural, engineering and construction industries have shown an increase in budget and activity. An investigation of the adjustments made in response to the pandemic through utilizing new technologies, such as the internet of things (IoT) and smart technologies, is necessary to understand the research trends of the new normal. This study should address various sectors, including business, healthcare, architecture, education, tourism and transportation. In this study, a literature review was performed on two web-based, peer-reviewed journal databases, SCOPUS and Web of Science, to identify a trend in research for the pandemic era in various sectors. The results from 123 papers revealed a focused word group of IoT, smart technologies, architecture, building, space and COVID-19. Overlapping knowledges of IoT systems, within the design of a building which was designed for a specific purpose, were discovered. The findings justify the need for a new sub-category within the field of architecture called “smart architecture”. This aims to categorize the knowledge which is required to embed IoT systems in three key architectural topics—planning, design, and construction—for building design with specific purposes, tailored to various sectors.

Digital technologies as enablers of supply chain sustainability in an emerging economy

Vietnam is a country with significant potential for growth as a global centre for manufacturing, as supply chains look to reduce their over-reliance on China in the aftermath of COVID-19. The objective of this study is to better understand the current adoption rates and growth potential of emerging Industry 4.0 (I4.0) digital technologies and ascertain their potential to drive successful future sustainability initiatives amongst Vietnamese supply chain firms. These technologies offer a wide range of sustainability benefits, from a potential to reduce waste production and lower energy consumption to increased opportunities for recycling and industrial symbiosis. This empirical study surveys 223 Vietnamese supply chain experts to learn how digital technologies are being utilized in that region, what levels of future investment are expected, what preparatory measures are being taken to leverage new technologies, and what scope for improved supply chain sustainability exists. The findings indicate a low level of I4.0 digital technology adoption amongst Vietnamese supply chain firms, with the Internet of Things (IoT) currently being the most prevalent (48 percent adoption rate). Drones, Big Data Analytics and IoT are the I4.0 digital technologies expected to have the greatest future impact on Vietnamese supply chains. Whilst I4.0 digital technology adoption is still at this early stage, that may present a greater opportunity for driving future sustainability outcomes, than interrupting and retrofitting solutions to already-established networks and infrastructure.

Developing a Smart Home Technology Innovation for People With Physical and Mental Health Problems: Considerations and Recommendations

Smart home technologies present an unprecedented opportunity to improve health and health care by providing greater communication and connectivity with services and care providers and by supporting the daily activities of people managing both mental and physical health problems. Based on our experience from conducting smart technology health studies, including a smart home intervention, we provide guidance on developing and implementing such interventions. First, we describe the need for an overarching principle of security and privacy that must be attended to in all aspects of such a project. We then describe 4 key steps in developing a successful smart home innovation for people with mental and physical health conditions. These include (1) setting up the digital infrastructure, (2) ensuring the components of the system communicate, (3) ensuring that the system is designed for the intended population, and (4) engaging stakeholders. Recommendations on how to approach each of these steps are provided along with suggested literature that addresses additional considerations, guidelines, and equipment selection in more depth.

A Review on Machine Learning, Artificial Intelligence, and Smart Technology in Water Treatment and Monitoring

Artificial-intelligence methods and machine-learning models have demonstrated their ability to optimize, model, and automate critical water- and wastewater-treatment applications, natural-systems monitoring and management, and water-based agriculture such as hydroponics and aquaponics. In addition to providing computer-assisted aid to complex issues surrounding water chemistry and physical/biological processes, artificial intelligence and machine-learning (AI/ML) applications are anticipated to further optimize water-based applications and decrease capital expenses. This review offers a cross-section of peer reviewed, critical water-based applications that have been coupled with AI or ML, including chlorination, adsorption, membrane filtration, water-quality-index monitoring, water-quality-parameter modeling, river-level monitoring, and aquaponics/hydroponics automation/monitoring. Although success in control, optimization, and modeling has been achieved with the AI methods, ML models, and smart technologies (including the Internet of Things (IoT), sensors, and systems based on these technologies) that are reviewed herein, key challenges and limitations were common and pervasive throughout. Poor data management, low explainability, poor model reproducibility and standardization, as well as a lack of academic transparency are all important hurdles to overcome in order to successfully implement these intelligent applications. Recommendations to aid explainability, data management, reproducibility, and model causality are offered in order to overcome these hurdles and continue the successful implementation of these powerful tools.

Colorful Luminescent Magnetic Supraparticles: Expanding the Applicability, Information Capacity, and Security of Micrometer-Scaled Identification Taggants by Dual-Spectral Encoding

(Sub)micrometer-scaled identification (ID) taggants enable direct identification of arbitrary goods, thereby opening up application fields based on the possibility of tracking, tracing, and anti-counterfeiting. Due to their small dimensions, these taggants can equip in principle even the smallest subcomponents or raw materials with information. To achieve the demanded applicability, the mostly used optically encoded ID taggants must be further improved. Here, micrometer-scaled supraparticles with spectrally encoded luminescent and magnetically encoded signal characteristics are reported. They are produced in a readily customizable bottom-up fabrication procedure that enables precise adjustment of luminescent and magnetic properties on multiple hierarchy levels. The incorporation of commonly used magnetic nanoparticles and fluorescent dyes, respectively, into polymer nanocomposite particles, establishes a convenient toolbox of magnetic and luminescent building blocks. The subsequent assembly of selected building blocks in the desired ratios into supraparticles grants for all the flexibility to freely adjust both signal characteristics. The obtained spectrally resolved visible luminescent and invisible magnetic ID signatures are complementary in nature, thus expanding applicability and information security compared to recently reported optical- or magnetic-encoded taggants. Additionally, the introduced ID taggant supraparticles can significantly enhance the coding capacity. Therefore, the introduced supraparticles are considered as next-generation ID taggants.

A Heuristic-Based Simulation for an Education Process to Learn about Optimization Applications in Logistics and Transportation

In the context of the DigiLab4U international project, this paper describes a simulation-based serious game that can be used as a virtual teaching lab in higher education courses, especially in Industrial and Systems Engineering, Data Science, Management Science and Operations Research, as well as Computer Science. The learning activity focuses on understanding distribution logistics problems related to transportation optimization using different techniques. These optimization challenges include the vehicle routing problem, the arc routing problem, and the team orienteering problem. As a result of the learning process in the virtual lab, it is expected that students acquire competencies and skills related to logistics and transportation challenges as well as problem-solving. These competencies and skills can be precious for students’ future careers, since they increase students’ analytical skills, capacity to understand heuristic-based algorithms, teamwork and interdisciplinary communication skills, programming skills, and statistical abilities. A preliminary version of this training activity has already been used in MSc and PhD courses held at universities in Spain, Italy, Ireland, and Portugal.

Interoperability in the era of digital innovation: An information systems research agenda

Digital innovation enables new forms of cyber-physical innovation based on digital business ecosystems. However, the realization of the opportunities arising from such innovation substantially hinges on interoperability, that is, the ability of two or more systems to exchange information and understand that exchanged information. While interoperability is a long-standing topic in research and practice alike and a valuable knowledge base exists, digital innovation poses novel challenges that might not be covered by conventional wisdom. Accordingly, we review the literature and, first, propose an organizing framework for existing interoperability knowledge involving the contextual conditions of low interoperability, the mechanisms to increase interoperability, and the associated outcomes. Second, we use the framework to identify previous research foci in the scholarly discourse about interoperability and to discuss the potential limitations of this past work in light of digital innovation. Third, we propose a research agenda that enables information systems (IS) research to address the identified limitations—involving conceptual, scoping, and methodological issues—and provide specific recommendations on how to address the identified issues in future IS research. Finally, we propose five major research topics for further inquiry by combining the challenges identified in current knowledge with the current shift toward hyper-connected ecosystems underlying digital innovation.

Exploring the experts’ perceptions of barriers to using internet of things for chronic disease management in Iran

Purpose

Internet of things (IoT) promises advantages in different sectors, especially the health-care sector. Due to its capabilities for chronic disease management, IoT has attracted the attention of researchers. Nowadays, there is research that focuses on the use of IoT for chronic disease management. However, the use of IoT in various contexts faces different barriers. This paper aims to explore Iranian experts’ conceptions of the barriers to using IoT in Iran regarding its application for chronic disease management.

Design/methodology/approach

This study follows a phenomenographic method to investigate Iranian experts’ conceptions of the barriers to using IoT in Iran regarding its application for chronic disease management.

Findings

The results show that there are four categories of description (governance, technical, economic and social barriers) that vary among experts’ conceptions.

Originality/value

The findings of the present work could provide valuable insights for managers and policymakers who want to address IoT barriers.

A novel pseudo-random number generator for IoT based on a coupled map lattice system using the generalised symmetric map

Pseudo-random number generators (PRNGs) are one of the building blocks of cryptographic methods and therefore, new and improved PRNGs are continuously developed. In this study, a novel method to generate pseudo-random sequences using coupled map lattices is presented. Chaotic maps only show their chaotic behaviour for a specified range of control parameters, what can restrict their application in cryptography. In this work, generalised symmetric maps with adaptive control parameter are presented. This novel idea allows the user to choose any symmetric chaotic map, while ensuring that the output is a stream of independent and random sequences. Furthermore, to increase the complexity of the generated sequences, a lattice-based structure where every local map is linked to its neighbouring node via coupling factor has been used. The dynamic behaviour and randomness of the proposed system has been studied using Kolmogorov–Sinai entropy, bifurcation diagrams and the NIST statistical suite for randomness. Experimental results show that the proposed PRNG provides a large key space, generates pseudo-random sequences and is computationally suitable for IoT devices.

Utilizing the Internet of Things in Public Sector

This study investigated the utility of the Internet of Things in the public sector and the factors influencing the satisfaction of its users. The study followed two directions, the first investigated managers’ perceptions and their satisfaction with using sensors for tracking vehicles. The second direction investigated drivers’ satisfaction with the system used. Results collected from 20 interviews conducted with managers revealed that cost reduction and more control over drivers’ behaviors are the contributions expected from the system. They reported the dissatisfaction of drivers based on violation of their privacy, inequity of implementation, and the low awareness of its utility. Surveys collected from drivers supported the role of trust and privacy, but failed to support the role of usefulness. The qualitative and quantitative nature of this research revealed valuable insights and concluded to important recommendations and future work.

Railway Track Stress–Strain Analysis Using High-Precision Accelerometers

We propose a new approach for railway path diagnostics on the basis of track line stress–strain analysis using the data provided by high-precision accelerometers. This type of sensor provides sufficient accuracy with lower costs, and enables the development of a railway digital twin, according to the concept of the Internet of Things. The installation of sensors on a railway track along its entire length allows real-time monitoring of the states of the technical parameters of the railway track, and using mathematical methods to evaluate its wear on the basis of constantly received data. This paper presents an original 3D model of a railway track line and the results of its analysis using a finite element method. To test the model, we performed an analysis of the normal stresses and deformations in the elements of a railway track by simulating the impact of rolling stock on a section of a railway track with intermediate rail fastenings, ZhBR-65SH. The research results were probated and tested at the testing ground of the Kuibyshev branch of Russian Railways, the Samara track. The proposed approach makes it possible to determine the load of the track, and knowing the movement of the rail, to calculate the structural stress in the elements of the railway track, to constantly monitor the parameters of the slope and rail subsidence.

Artificial Intelligence: the future of medicine, or an overhyped and dangerous idea?

INTRODUCTION

Contemporary discourse on Artificial Intelligence (AI) in medicine is oft-sensationalised to the point of bearing no resemblance to its everyday impact and potential - either to proselytise it as a saviour or to condemn its perilous, amoral and sprawling reach.This report aims to unravel the paucity of understanding underpinning this hyperbolic duality, whilst addressing the potential clearly defining its ethical use poses to the semi-public healthcare models in Ireland and Europe.

DISCUSSION

The report contrasts the challenge of regulating the breakneck development of AI, with healthcare's necessity for stringent quality control in ethical technological development to ensure patients' well-being.Physical, practical and philosophical approaches to Artificial Intelligence in medicine are explored through Beauchamp and Childress' principles of delivering care with beneficence, non maleficence, justice and autonomy. AI is scrutinised under Kantian deontological, Benthamite utilitarian and Rawlsian perspectives on health justice. Actor Network theory is used to explain sociotechnical interactions governing human stakeholders developing ethical AI.These analyses operate firstly to define AI concisely, then ground it in its contemporary and future functions in healthcare. They highlight the importance of aligning medical AI with accepted ethical standards as a necessity of its integrated use across healthcare.

CONCLUSION

This report concludes that balanced assessment of AI's role in healthcare requires improvement in three areas: improving clarity in definition of AI and its extant remit in medicine; aligning contemporary discourse on AI use with contemporary objective ethical, legal and system frameworks; and clearly identifying for dismissal a number of logical fallacies deliberately sensationalising AI's potential.

Connected healthcare: Improving patient care using digital health technologies

Now more than ever, traditional healthcare models are being overhauled with digital technologies of Healthcare 4.0 increasingly adopted. Worldwide, digital devices are improving every stage of the patient care pathway. For one, sensors are being used to monitor patient metrics 24/7, permitting swift diagnosis and interventions. At the treatment stage, 3D printers are under investigation for the concept of personalised medicine by allowing patients access to on-demand, customisable therapeutics. Robots are also being explored for treatment, by empowering precision surgery, rehabilitation, or targeted drug delivery. Within medical logistics, drones are being leveraged to deliver critical treatments to remote areas, collect samples, and even provide emergency aid. To enable seamless integration within healthcare, the Internet of Things technology is being exploited to form closed-loop systems that remotely communicate with one another. This review outlines the most promising healthcare technologies and devices, their strengths, drawbacks, and opportunities for clinical adoption.

Integrating Industry 4.0 and circular economy: a review

Purpose

Industry 4.0 and circular economy are the two major areas in the current manufacturing industry. However, the adoption and implementation of Industry 4.0 and circular economy worldwide are still in the nascent stage of development. To address this gap, the purpose of this article is to conduct a systematic literature review on integrating Industry 4.0 and circular economy. Further, identify the research gaps and provide the future scope of work in this area.

Design/methodology/approach

Content-based analysis was adopted for reviewing the research articles and proposed a transition framework that comprises of four categories, namely, (1) Transition from Industry 3.0 to Industry 4.0 and integration with circular economy; (2) Adoption of combined factors and different issues; (3) Implementation possibilities such as front-end technologies, integration capabilities and redesigning strategies; (4) Current challenges. The proposed study reviewed a total of 204 articles published from 2000 to 2020 based on these categories.

Findings

The article presents a systematic literature review of the last two decades that integrates Industry 4.0 and circular economy concepts. Findings revealed that very few studies considered the adoption and implementation issues of Industry 4.0 and circular economy. Moreover, it was found that Industry 4.0 technologies including digitalization, real-time monitoring and decision-making capabilities played a significant role in circular economy implementation. The major elements are discussed through the analysis of the transition and integration framework. The study further revealed that a limited number of developing countries like India have taken preliminary initiatives toward Industry 4.0 and circular economy implementation.

Research limitations/implications

The study proposes a transition and integration framework that identifies adoption and implementation issues and challenges. This framework will help researchers and practitioners in implementation of Industry 4.0 and circular economy.

Originality/value

Reviews of articles indicated that there are very few studies on integrating Industry 4.0 and circular economy. Moreover, there are very few articles addressing adoption and implementation issues such as legal, ethical, operational and demographic issues, which may be used to monitor the organization's performance and productivity.

On Blurry Boundaries When Defining Digital Biomarkers: How Much Biology Needs to Be in a Digital Biomarker?

Recent years have seen a rise in research where so called "digital biomarkers" represent the focal study interest. Many researchers understand that digital biomarkers describe digital footprints providing insights into healthy and pathological human (neuro-)biology. Beyond that the term digital biomarker is also used at times to describe more general concepts such as linking digital footprints to human behavior (which itself can be described as the result of a biological system). Given the lack of consensus on how to define a digital biomarker, the present short mini-review provides i) an overview on various definitions and ii) distinguishes between direct (narrow) or indirect (broad) concepts of digital biomarkers. From our perspective, digital biomarkers meant as a more direct (or narrow) concept describe digital footprints being directly linked to biological variables, such as stemming from molecular genetics, epigenetics, endocrinology, immunology or brain imaging, to name a few. More indirect concepts of digital biomarkers encompass digital footprints being linked to human behavior that may act as latent variables indirectly linked to biological variables.

An Overview of High-Performance Indoor Organic Photovoltaics

In recent years, indoor organic photovoltaics (IOPVs) have attracted increasing attention because of their ability to power microelectronic devices and sensors, especially for the internet of things (IoT). In contrast with silicon-based indoor PV, the IOPVs exhibit better performance due to their tunable bandgap via molecular design, which could achieve a better spectrum matched with the lighting sources. Based on the simulated power conversion efficiency (PCE) in theory, the maximum value can achieve over 50 % under the white LED illumination, which is much higher than the practical top PCE of 31 %, indicating there is room further to improve the performance of IOPVs by various optimization methods. Based on these benefits, the recent progress in IOPVs with different methods was summarizes, and light was shed on the remaining challenges for achieving practical applications in the future. In the end, some guidelines for the development of IOPVs were proposed.

Internet of Things and Other E-Solutions in Supply Chain Management May Generate Threats in the Energy Sector—The Quest for Preventive Measures

Energy firms are the beneficiaries and initiators of innovation, and energy investments are a crucial area of business activity that is specially protected in any country. This is no wonder, as energy security is the basis for the functioning of states and economies. The Internet of Things and Big Data create both new challenges and new threats. This study aimed to identify the potential threats and determine preventive measures, as well as to establish the agile principles related to energy firms’ logistics. The method of the narrative summary in combination with the literature searching method was used. Two conclusions emerged: first, research serves to develop the discipline of management science; second, the identification of risks associated with innovation serves practitioners. In addition, the study defined further research directions.

Improving service engagement in healthcare through internet of things based healthcare systems

Purpose

The purpose of the study was to empirically validate the linkages between IoT adoption and how it overarched influenced the patient care service engagement. This contributes to the body of knowledge and helps hospital managers to understand the relationship and relevance of IoT adoption; otherwise healthcare sector are late movers towards technology adoption. This gives a nuanced framework towards establishing empirically validated framework which will motivate healthcare services providers to be motivated to adopt and implement IoT enabled care delivery. The physician patient interaction and alignment during decision making will foster positive word of mouth, superior care service and reduce extra overheads for healthcare providers without compromise or rather with increment in service delivery proposition.

Design/methodology/approach

The study theoretically and empirically describes that with the adoption of internet of things (IoT) devices in health care, better services can be provided to patients by using partial least square – structure equation modelling-based robust technique and explains the better understanding of the health-care process with the help of information pervasiveness, physician-patient orientation and improved patient and physician involvement in the decision-making process.

Findings

This study shows that wearable IoT device adoption in health-care service delivery opens new opportunities and disrupts the conventional and traditional way of health-care service delivery by empowering the patient to take part in decision-making and enhancing their engagement in health-care service delivery.

Research limitations/implications

The study might influence by generalizability. Perception-based cross-examination knowledge from the patient’s perspective. It is likely that patients who use these devices will grow accustomed to using them and become more capable of using them. Thus, time-series tests have not been used to catch enhanced skills. New patients’ experiences will be altered over time. Regardless, non-response bias and traditional process bias received excessive interest.

Practical implications

The study aims at unravelling how the adoption of IoT enabled practices and usage of IoT devices bolsters the available data points in the context of healthcare especially with respect to patient care delivery. The study conceptualizes and empirically validates how the usage of IoT interface enabled technology enables better patient treatment and caregiver participation. The study puts forth a nuanced understanding regarding how pervasively available ubiquitous care information fosters shared decision making. This study further emphasizes that importance of ensuring a reliable computing environment devoid of privacy and security risks. The study attempts at Emphasizing empirically how the enhanced information pervasiveness catapults the patient-provider interactions, through health data exchange. Highlighting the importance of search feature in cloud storage and recovery mechanisms. The study not only fulfills the overarching linkage between enhanced service engagement with IoT adoption, it provides a mental map and ready to refer framework for hospital and healthcare experts to refer to, which prescribes thar care providers must build new methods aimed at empowerment of patients to participate and take more inclusive role. This unique confluence between patients and physicians will unravel the sync; helping not only avoid costly decision errors, but also improve patient care delivery environment. Patients should be permitted to participate in decision-making,inspire patients to be participatory.

Originality/value

The study efforts to empirically investigate and discover the link between how wearable sensor-based IoT enhances health-care service engagement is underway. Using primary data this linkage validation allows the community and readers at large to gain a nuanced understanding of how superior interaction is enabled by a digital-health-care process with the help of IoT-enabled information pervasiveness, physician-patient orientation and empowered involvement.

IoT Technologies as Instruments for SMEs’ Innovation and Sustainable Growth

This paper studies specific aspects related to the adoption of Internet of Things (IoT) technologies and the impact they have on the sustainable growth of Small and Medium Enterprises (SMEs) in the Romanian IT industry. It was considered that digital marketing in general, and IoT in particular, have enormous potential for the aforementioned entities, and the acceptance and adoption of IoTs by companies in different sectors can significantly influence the way they operate, leading to sustainable growth. Primary data obtained from quantitative marketing research based on a questionnaire were analyzed. The results showed that although a large proportion of the Romanian IT industry SMEs use advanced marketing technologies, relatively few of those have integrated IoT solutions to date, mainly due to specific cost challenges. Nevertheless, the outcomes highlight that these companies are aware of the IoT’s benefits and place the adoption of such solutions among their priorities in order to achieve sustainable growth of their businesses. Based on the research results, the main proposal for the business environment is to design viable marketing programs for these companies, as well as to allocate resources for business development aimed at educating human resources to effectively address specific internal and external activities through IoT for sustainable development.

iOntoBioethics: A Framework for the Agile Development of Bioethics Ontologies in Pandemics, Applied to COVID-19

Background: Few ontological attempts have been reported for conceptualizing the bioethics domain. In addition to limited scope representativeness and lack of robust methodological approaches in driving research design and evaluation of bioethics ontologies, no bioethics ontologies exist for pandemics and COVID-19. This research attempted to investigate whether studying the bioethics research literature, from the inception of bioethics research publications, facilitates developing highly agile, and representative computational bioethics ontology as a foundation for the automatic governance of bioethics processes in general and the COVID-19 pandemic in particular.

Research Design: The iOntoBioethics agile research framework adopted the Design Science Research Methodology. Using systematic literature mapping, the search space resulted in 26,170 Scopus indexed bioethics articles, published since 1971. iOntoBioethics underwent two distinctive stages: (1) Manually Constructing Bioethics (MCB) ontology from selected bioethics sources, and (2) Automatically generating bioethics ontological topic models with all 26,170 sources and using special-purpose developed Text Mining and Machine-Learning (TM&ML) engine. Bioethics domain experts validated these ontologies, and further extended to construct and validate the Bioethics COVID-19 Pandemic Ontology.

Results: Cross-validation of the MCB and TM&ML bioethics ontologies confirmed that the latter provided higher-level abstraction for bioethics entities with well-structured bioethics ontology class hierarchy compared to the MCB ontology. However, both bioethics ontologies were found to complement each other forming a highly comprehensive Bioethics Ontology with around 700 concepts and associations COVID-19 inclusive.

Conclusion:The iOntoBioethics framework yielded the first agile, semi-automatically generated, literature-based, and domain experts validated General Bioethics and Bioethics Pandemic Ontologies Operable in COVID-19 context with readiness for automatic governance of bioethics processes. These ontologies will be regularly and semi-automatically enriched as iOntoBioethics is proposed as an open platform for scientific and healthcare communities, in their infancy COVID-19 learning stage. iOntoBioethics not only it contributes to better understanding of bioethics processes, but also serves as a bridge linking these processes to healthcare systems. Such big data analytics platform has the potential to automatically inform bioethics governance adherence given the plethora of developing bioethics and COVID-19 pandemic knowledge. Finally, iOntoBioethics contributes toward setting the first building block for forming the field of “Bioethics Informatics”.

Current Progress and Future Prospects of Agriculture Technology: Gateway to Sustainable Agriculture

The agricultural industry is getting more data-centric and requires precise, more advanced data and technologies than before, despite being familiar with agricultural processes. The agriculture industry is being advanced by various information and advanced communication technologies, such as the Internet of Things (IoT). The rapid emergence of these advanced technologies has restructured almost all other industries, as well as advanced agriculture, which has shifted the industry from a statistical approach to a quantitative one. This radical change has shaken existing farming techniques and produced the latest prospects in a series of challenges. This comprehensive review article enlightens the potential of the IoT in the advancement of agriculture and the challenges faced when combining these advanced technologies with conventional agricultural systems. A brief analysis of these advanced technologies with sensors is presented in advanced agricultural applications. Numerous sensors that can be implemented for specific agricultural practices require best management practices (e.g., land preparation, irrigation systems, insect, and disease management). This review includes the integration of all suitable techniques, from sowing to harvesting, packaging, transportation, and advanced technologies available for farmers throughout the cropping system. Besides, this review article highlights the utilization of other tools such as unmanned aerial vehicles (UAVs) for crop monitoring and other beneficiary measures, such as optimizing crop yields. In addition, advanced programs based on the IoT are also discussed. Finally, based on our comprehensive review, we identified advanced prospects regarding the IoT, which are essential tools for sustainable agriculture.

Exploring the intellectual cores of the blockchain–Internet of Things (BIoT)

Purpose

Due to the rapid growth of blockchain technology in recent years, the fusion of blockchain and the Internet of Things (BIoT) has drawn considerable attention from researchers and industrial practitioners and is regarded as a future trend in technological development. Although several authors have conducted literature reviews on the topic, none have examined the development of the knowledge structure of BIoT, resulting in scattered research and development (R&D) efforts.

Design/methodology/approach

This study investigates the intellectual core of BIoT through a co-citation proximity analysis–based systematic review (CPASR) of the correlations between 44 highly influential articles out of 473 relevant research studies. Subsequently, we apply a series of statistical analyses, including exploratory factor analysis (EFA), hierarchical cluster analysis (HCA), k-means clustering (KMC) and multidimensional scaling (MDS) to establish the intellectual core.

Findings

Our findings indicate that there are nine categories in the intellectual core of BIoT: (1) data privacy and security for BIoT systems, (2) models and applications of BIoT, (3) system security theories for BIoT, (4) frameworks for BIoT deployment, (5) the fusion of BIoT with emerging methods and technologies, (6) applied security strategies for using blockchain with the IoT, (7) the design and development of industrial BIoT, (8) establishing trust through BIoT and (9) the BIoT ecosystem.

Originality/value

We use the CPASR method to examine the intellectual core of BIoT, which is an under-researched and topical area. The paper also provides a structural framework for investigating BIoT research that may be applicable to other knowledge domains.

Digitally driven new product development: an involved contemporary innovation case

Purpose

The purpose of this paper is to study the impact of real-time data emerging from implementation of the Internet of Things (IoT) and netnography on the efficiency of the new product development (NPD).

Design/methodology/approach

Customer-oriented organizations are the ones that survive in the market with a flow of new products to the market. Expectations like reduced timelines with quality focus provoke innovations. Customer inputs become the soul for a successful product wherein it becomes important to keep a constant stream of information flow back from the market. Literature review states that real-time data gathering with the implementation of IoT ensures the same. Along with real-time data, researchers have envisaged the need to identify the customer persona before incorporating customer opinion and sentiments vide netnography.

Findings

The organization can leverage the collaboration of IoT origin real-time data and sentiment analysis to effectively manage the NPD. Real-time customer data coupled with customer opinions and sentiments prove to be a game changer in the NPD process.

Originality/value

The originalities of this study are impact of IoT origin real-time data coupled with sentiment analysis on the NPD process. While impact of IoT origin data is reported in isolation similar to sentiment analysis, influence of collaboration of real-time data with sentiment analysis on NPD process is reported in this study.

Multimedia system and database simulation based on internet of things and cloud service platform

The existing stand-alone multimedia machines and online multimedia machines in the market have certain deficiencies, so they cannot meet the actual needs. Based on this, this research combines the actual needs to design and implement a multi-media system based on the Internet of Things and cloud service platform. Moreover, through in-depth research on the MQTT protocol, this study proposes a message encryption verification scheme for the MQTT protocol, which can solve the problem of low message security in the Internet of Things communication to a certain extent. In addition, through research on the fusion technology of the Internet of Things and artificial intelligence, this research designs scheme to provide a LightGBM intelligent prediction module interface, MQTT message middleware, device management system, intelligent prediction and push interface for the cloud platform. Finally, this research completes the design and implementation of the cloud platform and tests the function and performance of the built multimedia system database. The research results show that the multimedia database constructed in this paper has good performance.

Application of Internet of Things in academic buildings for space use efficiency using occupancy and booking data

Environmental sustainability in academic buildings can be improved with management interventions such as improving space use efficiency supported by large data from the Internet of Things (IoT). Due to the potentials, the interest in the use of IoT tools for facility management is high among universities. However, empirical studies on this topic are scarce. To address the knowledge gap in this area, this study proposes and examines a process model with steps to measure space use and to improve space use efficiency by IoT tools in academic buildings. The applicability of the model is investigated in 8 lecture halls in a university building by using occupancy and booking data from IoT tools. Four space use indicators are developed to visualize the data and quantify space use, and based on them, the strategies and interventions for space use efficiency are proposed and discussed.

Construction 4.0: A Literature Review

The construction industry is experiencing changes in its processes and work methods, and the advancement of new technologies in recent decades has led to a new concept known as Construction 4.0, coined in 2016 in Germany. Since its definition is still diffuse, it was deemed necessary to conduct a review on the publications in this field to grasp how this concept is being understood. For that purpose, a bibliometric analysis was conducted among 260 research articles using seven keywords. The results reveal that the number of publications is growing exponentially, with the USA, the UK, and China being leaders in this field; besides, four technologies are essential to understand Construction 4.0 at present time: 3D printing, big data, virtual reality, and Internet of Things. The results of this review suggest that further reviews should be conducted every 3 years to grasp the rapid evolution of Construction 4.0.

Deep artificial neural network based on environmental sound data for the generation of a children activity classification model

Children activity recognition (CAR) is a subject for which numerous works have been developed in recent years, most of them focused on monitoring and safety. Commonly, these works use as data source different types of sensors that can interfere with the natural behavior of children, since these sensors are embedded in their clothes. This article proposes the use of environmental sound data for the creation of a children activity classification model, through the development of a deep artificial neural network (ANN). Initially, the ANN architecture is proposed, specifying its parameters and defining the necessary values for the creation of the classification model. The ANN is trained and tested in two ways: using a 70-30 approach (70% of the data for training and 30% for testing) and with a k-fold cross-validation approach. According to the results obtained in the two validation processes (70-30 splitting and k-fold cross validation), the ANN with the proposed architecture achieves an accuracy of 94.51% and 94.19%, respectively, which allows to conclude that the developed model using the ANN and its proposed architecture achieves significant accuracy in the children activity classification by analyzing environmental sound.

High-Performance Al/PDMS TENG with Novel Complex Morphology of Two-Height Microneedles Array for High-Sensitivity Force-Sensor and Self-Powered Application

Triboelectric nanogenerators (TENGs) are widely applied to self-powered devices and force sensors. TENGs consist of the electrode-layer frequently made of high-cost conductors (Ag, Au, ITO) and the tribo-layer of rigid negative-triboelectricity fluoropolymers (PTFE, FEP). The surface morpholoy is studied for enhancing performance. Here, a high-performance Al/PDMS-TENG is proposed with a complex morphology of overlapped deep two-height microneedles (OL-DTH-MN) fabricated by the integrated process of low-cost CO₂ laser ablation and PDMS casting for self-powered devices and high-sensitivity force/pressure sensors. The high open-circuit voltage and short-circuit current of the OL-DTH-MN-TENG are 167 V and 129.3 µA. Also, the sensitivity of the force/pressure sensor of the OL-DTH-MN-TENG is very high, 1.03 V N^-1 and about 3.11 V kPa^-1 , at an area of 30 cm² that is much higher than the sensitivity of about 0.18-0.414 V N^-1 and 0.013-0.29 V kPa^-1 of conventional TENG sensors. Meanwhile, the high-performance OL-DTH-MN-TENG not only exhibits the energy storage capability of charging a 0.1 µF capacitor to 2.75 V at 1.19 s, to maximum 3.22 V, but also activates various self-powered devices including lighting colorful 226 LEDs connected in series, the "2020-ME-NCKU" advertising board, a calculator and a temperature sensor. Numerical simulation is also performed to support the experiments.

Technology innovations for food security in Singapore: A case study of future food systems for an increasingly natural resource-scarce world

Background

Food security is becoming an increasingly important global issue. Anthropogenic factors such as rapid urbanization and industrialization have strained finite resources like land and water. Therefore, against the impending threat of food security, the world can no longer rely on traditional methods to meet its needs. Instead, more creative and technologically advanced methods must be adopted to maximise diminishing natural resources. Singapore is a good case study of a small city-state that is trying to increase its own self-production of food using technology.

Scope and approach

This review highlights the technologies that Singapore have adopted in enhancing food security given its limitation in natural resources. These methodologies serve as a case study that can be used as a reference point in light of the increasingly finite natural resources. The review also presents the advantages of these techniques as well as challenges that need to be overcome for them to be more widely adopted.

Key findings and conclusion

To increase self-production of food and enhance its food security, Singapore has employed the use of technologies such as vertical farming and aquaponics in urban farming, nutrient recovery from food waste, biodegradable food packaging from durian rinds, natural preservatives, insect farming, microalgae and cultivated meat as alternative protein sources. These technologies workaround Singapore's land and natural resource constraints, which many countries around the world can adapt. However, many of them are still relatively nascent with numerous challenges, which have to be addressed before they can be widely accepted and implemented.

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Long term agriculture and pollution have led to depletion of natural resources.

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Technology innovations can be used to mitigate natural resource constraints.

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Singapore has adopted numerous technologies to enhance food security.

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Areas include urban farming, processing technology and alternative food sources.

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Singapore's model provides a good example to increase self-production of food.

Organic semiconductors for visible light communications

Organic semiconductors are an important class of optoelectronic material that are widely studied because of the scope for tuning their properties by tuning their chemical structure, and simple fabrication to make flexible films and devices. Although most effort has focused on developing displays and lighting from these materials, their distinctive properties also make them of interest for visible light communications (VLCs). This article explains how their properties make them suitable for VLC and reviews the main uses that have been explored. On the transmitter side, record white VLC communication has been achieved by using organic semiconductors as colour converters, while direct modulation of organic light-emitting diodes is also possible and could be of interest for display-to-display communication. On the receiver side, organic solar cells can be used to harvest power and data simultaneously, and fluorescent antennas enable fast and sensitive receivers with large field of view. This article is part of the theme issue 'Optical wireless communication'.

Improving Recommendation Accuracy Using Social Network of Owners in Social Internet of Vehicles

The latest manifestation of “all connected world" is the Internet of Things (IoT), and Internet of Vehicles (IoV) is one of the key examples of IoT these days. In Social IoV (SIoV), each vehicle is treated as a social object where it establishes and manages its own Social Network (SN). Incidentally, most of the SIoV research in the literature is related to proximity-based connectivity and interactions. In this paper, we bring people in the loop by incorporating their SNs. While emphasizing a recommendation scenario, in which vehicles may require recommendations from SNs of their owners (in addition to their own SIoV), we proposed an agent-based model of information sharing (for context-based recommendations) on a hypothetical population of smart vehicles. Some important hypotheses were tested using a realistic simulation setting. The simulation results reveal that a recommendation using weak ties is more valuable than a recommendation using strong ties in pure SIoV. The simulation results also demonstrate that recommendations using the most-connected person in the social network are not more valuable than recommendation using a random person in the social network. The model presented in this paper can be used to design a multi-scale recommendation system, which uses SIoV and a typical SN in combination.