Development Of Internet Of Things Research Articles

PETRAS: a socio-technical framework for Internet of Things research and development

This paper presents a case application of a socio-technical framework for Internet of Things (IoT) research and development in the United Kingdom. Applying a socio-technical system approach to IoT, this paper seeks to provide a clear understanding of the interplay between technical and non-technical aspects of IoT research and development. It describes the socio-technical requirements for IoT design and development and provides the current snapshot of research in the United Kingdom to meet these requirements. Finally, the paper provides useful information on how to conceptualize IoT research within human-centered contexts and a useful guide for centre design and evaluation to those developing new research centres or seeking to reinvigorate existing ones.

IoT applications in asset management: A review of accounting and tracking techniques

In the digital age, the confluence of Internet of Things (IoT) technologies with asset management practices heralds a transformative era, promising unprecedented efficiency and strategic advantage. This paper delves into the intricacies of this integration, exploring the evolution, challenges, and potential of IoT in reshaping asset management paradigms. With a keen aim to elucidate the transformative impact of IoT and navigate the complexities of its integration into asset management systems, the study adopts a qualitative research methodology, underpinned by a systematic literature review. This approach enables a comprehensive exploration of the subject matter, ensuring a nuanced understanding of the IoT's potential and pitfalls within the asset management domain. The findings illuminate a landscape where IoT applications significantly enhance asset utilization rates, underscored by empirical success stories and quantifiable improvements in operational efficiency. However, the journey reveals barriers—technical, organizational, and cultural—that impede seamless IoT adoption. Addressing these challenges, the paper offers strategic recommendations, emphasizing the need for strategic alignment, inter-organisational collaboration, and robust data management strategies to overcome integration hurdles. Conclusively, the study not only achieves its aim of highlighting the potential of IoT in asset management but also charts a course for future endeavors in this field. It posits that the strategic integration of IoT technologies stands as a cornerstone for the next generation of asset management practices, promising a future marked by enhanced efficiency, economic viability, and strategic agility. The recommendations provided serve as a compass for organizations embarking on the IoT integration journey, guiding them towards a horizon of transformative potential.

Designing Privacy-Aware IoT Applications for Unregulated Domains

Internet of Things (IoT) applications (apps) are challenging to design because of the heterogeneous systems on which they are deployed. IoT devices and apps may collect and analyse sensitive personal data, which is often protected by data privacy laws, some within highly regulated domains such as healthcare. Privacy-by-design (PbD) schemes can be used by developers to consider data privacy at the design stage. However, software developers are not widely adopting these approaches due to difficulties in understanding and interpreting them. There are currently a limited number of tools available for developers to use in this context. We believe that a successful PbD tool should be able to (i) assist developers in addressing privacy requirements in less regulated domains, as well as (ii) help them learn about privacy as they use the tool. The findings of two controlled lab studies are presented, involving 42 developers. We discuss how such a PbD tool can help novice IoT developers comply with privacy laws (e.g., GDPR) and follow privacy guidelines (e.g., privacy patterns). Based on our findings, such tools can help raise awareness of data privacy requirements at design. This increases the likelihood that subsequent designs will be more aware of data privacy requirements.

Flextory: Flexible Software Factory of IoT Data Consumers.

The success of the Internet of Things (IoT) has driven the development, among others, of many different software architectures for producing, processing, and analyzing heterogeneous data. In many cases, IoT applications share common features, such as the use of a platform or middleware, also known as message broker, that collects and manages data traffic between endpoints. However, in general, data processing is very dependent on the case study (sensors that send temperature data, drones that send images, etc.). Thus, the applications responsible for receiving and processing data, which we call consumers, have to be built ad hoc, since some of their elements have to be specially configured to solve specific needs of the case study. This paper presents Flextory, a software factory tool to make it easier for IoT developers to automatically construct configurable consumer applications, which we call FLEX-consumers. Flextory guides developers through the process of generating Java consumers by selecting some desired features such as, for instance, the particular communication protocol to be used. This way, the developer only has to concentrate on designing the algorithm to process the data. In short, the use of Flextory will result in consumer applications with configurable behavior, namely FLEX-consumers, that can connect to a messaging server (for example RabbitMQ) and process the received messages.

IoHT Based Tele-Healthcare Support System for Feasibility and Perfor-mance Analysis

With the rapid development in Internet of Things (IoT) it come up with the subbranch Internet of Healthcare Things or the Internet of Medical Things. With the help of portable healthcare sensors and the wearable devices now, ambulance can be converted into critical diagnostics unit on the wheels. Monitoring the home care patient is not the just part of IoT application where doctor can remotely monitor the patient situation by the means of sensors. It requires a complete system may called as telemedicine where multiple components will play similar priority role to monitor the patient status using sensors, let the doctor connect the patient, data analytics calculate the progression, AI engine will detect the emergency and act upon. The proposed system is to design and developing centralized tele-healthcare support system and systematic analytics sharing with multiple level of user with privacy protection. This will allow different authorities to take advantages from patient generated records.

IoT-Based HydroM8 Self-Watering Plant: A Design Thinking Approach and Business Model Analysis

The Internet of Things (IoT) generates new business opportunities by connecting physical objects with a multitude of sensors. IoT research mainly focused on technology and business models are relatively unexplored, although developing IoT business models is important for successful IoT service. The aim of this research is to prototyping business model for IoT development HydroM8 Self-Watering Plant. This research has a generic design thinking framework and business model for IoT through literature analysis and interviews. To create the developing of the HydroM8 Self-Watering Plant, the researcher undertakes case studies of a group of students who are in the process of finding problems, creating ideas, design product, to testing the HydroM8 Self-Watering Plant product using IoT that combines internet technology and smartphones. In addition, a group of students also made a Business Model which will later be used as planning, especially in the Competitive Advantages, Key Resources, Key Partners, Cost Structure to added value and sell products that will later be marketed to consumers. This research acts as a starting point for designing or developing business models for IoT services. The findings suggest that the HydroM8 Self-Watering Plant has a considerable chance of success rate for potential users, especially those who like to water plants but do not have enough time. The HydroM8 Self-Watering Plant can be a tool for caring (watering plants automatically) and this tool can provide information to users when their plants have been watered. This HydroM8 Self-Watering Plant has the potential to significantly impact for the community of agriculture sector and promote sustainable water use efficiency.

Navigating the Landscape of IoT, Distributed Cloud Computing: A Comprehensive Review

This comprehensive academic exploration delves into the revolutionary convergence of the Internet of Things (IoT) with distributed cloud computing, redefining the realms of data processing, storage, and communication. The paper critically analyzes scholarly work from reputable journals, providing profound insights into this integration's multifaceted applications and underlying technological frameworks. The relevance of IoT, a network of interconnected devices and sensors, is emphasized through its significant impact on diverse sectors, including healthcare, education, agriculture, and smart cities. This impact is magnified by its extensive data collection, processing, and analysis capabilities, enabled through cloud computing platforms. The objective of the paper is to methodically compare and contrast contemporary scholarly contributions, shedding light on the diverse applications and technological infrastructures of IoT in conjunction with distributed cloud computing. This endeavor encompasses an examination of IoT-based cloud infrastructure, detailed analysis of specific needs, implementations, and applications of IoT-based cloud computing, and a review of various IoT cloud platforms. The paper also highlights the benefits of integrating IoT with cloud computing, elucidating significant advantages and potential future directions of this technology. Through this scholarly inquiry, the paper aims to offer an in-depth perspective on the state-of-the-art developments in IoT and distributed cloud computing. It underscores their significance and potential in shaping the future of digital technology and its applications across various domains.

Enhancing emergency medical response through IoT: A focus on security and privacy

The healthcare industry is globally crucial. With an increasing demand for quality services, there is a need for innovative technologies like the Internet of Things (IoT) to enhance rapid and effective emergency response. This research explores IoT applications in emergency healthcare response, focusing on theoretical frameworks and design principles. It investigates the integration of IoT technologies into these systems while prioritising data security and privacy without relying on experimental data. The study offers innovative ideas for future research, highlighting the significance of addressing privacy and ethics in healthcare IoT usage. It emphasises protecting sensitive health data and promoting responsible IoT implementation in emergency healthcare settings. In conclusion, the study affirms the potential of IoT in enhancing emergency healthcare responses while emphasising the necessity of addressing privacy and ethical concerns within healthcare applications of these technologies. This research seeks to contribute to the ongoing development of IoT in healthcare by emphasising the importance of safeguarding patient information and ensuring that ethical considerations are at the forefront of implementation efforts.

The Internet of Things (IoT) in World Practice: Review and Analysis

This article explores the contemporary realm of the Internet of Things (IoT) and its influence on society and the economy. The primary emphasis lies in examining the principal patterns within the realm of IoT, encompassing the escalation of connected device quantities and the utilisation of 5G networks. The article encompasses various facets, including an overview of the evolution and possibilities of IoT, encompassing the advancement of intelligent urban areas and the influence of 5G networks. The analysis of threats and vulnerabilities related to this technology focuses on detecting common flaws, including weak passwords, unsecured network services, and inadequate privacy measures.
 Furthermore, the essay presents concrete hazards in diverse sectors that employ IoT technology. Particular emphasis is given to potential cybersecurity vulnerabilities in healthcare, manufacturing, agriculture, retail, transport and logistics, energy, and smart cities. These businesses have distinct challenges and hazards due to incorporating IoT technologies.
 The authors also analyse the substantial financial commitment to IoT and its profound influence on the worldwide economy, including data on the expansion of the IoT market and investments in IoT technologies and smart cities. The findings emphasise that the Internet of Things (IoT) substantially influences society and the economy. However, it necessitates meticulous consideration of cybersecurity and privacy concerns. The authors underscore the significance of creating efficacious cyber security policies to safeguard against the possible hazards presented by IoT technology.
 
 

Advancements and Challenges in IoT Simulators: A Comprehensive Review.

The Internet of Things (IoT) has emerged as an important concept, bridging the physical and digital worlds through interconnected devices. Although the idea of interconnected devices predates the term "Internet of Things", which was coined in 1999 by Kevin Ashton, the vision of a seamlessly integrated world of devices has been accelerated by advancements in wireless technologies, cost-effective computing, and the ubiquity of mobile devices. This study aims to provide an in-depth review of existing and emerging IoT simulators focusing on their capabilities and real-world applications, and discuss the current challenges and future trends in the IoT simulation area. Despite substantial research in the IoT simulation domain, many studies have a narrow focus, leaving a gap in comprehensive reviews that consider broader IoT development metrics, such as device mobility, energy models, Software-Defined Networking (SDN), and scalability. Notably, there is a lack of literature examining IoT simulators' capabilities in supporting renewable energy sources and their integration with Vehicular Ad-hoc Network (VANET) simulations. Our review seeks to address this gap, evaluating the ability of IoT simulators to simulate complex, large-scale IoT scenarios and meet specific developmental requirements, as well as examining the current challenges and future trends in the field of IoT simulation. Our systematic analysis has identified several significant gaps in the current literature. A primary concern is the lack of a generic simulator capable of effectively simulating various scenarios across different domains within the IoT environment. As a result, a comprehensive and versatile simulator is required to simulate the diverse scenarios occurring in IoT applications. Additionally, there is a notable gap in simulators that address specific security concerns, particularly battery depletion attacks, which are increasingly relevant in IoT systems. Furthermore, there is a need for further investigation and study regarding the integration of IoT simulators with traffic simulation for VANET environments. In addition, it is noteworthy that renewable energy sources are underrepresented in IoT simulations, despite an increasing global emphasis on environmental sustainability. As a result of these identified gaps, it is imperative to develop more advanced and adaptable IoT simulation tools that are designed to meet the multifaceted challenges and opportunities of the IoT domain.

Optimizing Internet of Things Fog Computing: Through Lyapunov-Based Long Short-Term Memory Particle Swarm Optimization Algorithm for Energy Consumption Optimization.

In the era of continuous development in Internet of Things (IoT) technology, smart services are penetrating various facets of societal life, leading to a growing demand for interconnected devices. Many contemporary devices are no longer mere data producers but also consumers of data. As a result, massive amounts of data are transmitted to the cloud, but the latency generated in edge-to-cloud communication is unacceptable for many tasks. In response to this, this paper introduces a novel contribution-a layered computing network built on the principles of fog computing, accompanied by a newly devised algorithm designed to optimize user tasks and allocate computing resources within rechargeable networks. The proposed algorithm, a synergy of Lyapunov-based, dynamic Long Short-Term Memory (LSTM) networks, and Particle Swarm Optimization (PSO), allows for predictive task allocation. The fog servers dynamically train LSTM networks to effectively forecast the data features of user tasks, facilitating proper unload decisions based on task priorities. In response to the challenge of slower hardware upgrades in edge devices compared to user demands, the algorithm optimizes the utilization of low-power devices and addresses performance limitations. Additionally, this paper considers the unique characteristics of rechargeable networks, where computing nodes acquire energy through charging. Utilizing Lyapunov functions for dynamic resource control enables nodes with abundant resources to maximize their potential, significantly reducing energy consumption and enhancing overall performance. The simulation results demonstrate that our algorithm surpasses traditional methods in terms of energy efficiency and resource allocation optimization. Despite the limitations of prediction accuracy in Fog Servers (FS), the proposed results significantly promote overall performance. The proposed approach improves the efficiency and the user experience of Internet of Things systems in terms of latency and energy consumption.

A Review of IoT Firmware Vulnerabilities and Auditing Techniques.

In recent years, the Internet of Things (IoT) paradigm has been widely applied across a variety of industrial and consumer areas to facilitate greater automation and increase productivity. Higher dependability on connected devices led to a growing range of cyber security threats targeting IoT-enabled platforms, specifically device firmware vulnerabilities, often overlooked during development and deployment. A comprehensive security strategy aiming to mitigate IoT firmware vulnerabilities would entail auditing the IoT device firmware environment, from software components, storage, and configuration, to delivery, maintenance, and updating, as well as understanding the efficacy of tools and techniques available for this purpose. To this effect, this paper reviews the state-of-the-art technology in IoT firmware vulnerability assessment from a holistic perspective. To help with the process, the IoT ecosystem is divided into eight categories: system properties, access controls, hardware and software re-use, network interfacing, image management, user awareness, regulatory compliance, and adversarial vectors. Following the review of individual areas, the paper further investigates the efficiency and scalability of auditing techniques for detecting firmware vulnerabilities. Beyond the technical aspects, state-of-the-art IoT firmware architectures and respective evaluation platforms are also reviewed according to their technical, regulatory, and standardization challenges. The discussion is accompanied also by a review of the existing auditing tools, the vulnerabilities addressed, the analysis method used, and their abilities to scale and detect unknown attacks. The review also proposes a taxonomy of vulnerabilities and maps them with their exploitation vectors and with the auditing tools that could help in identifying them. Given the current interest in analysis automation, the paper explores the feasibility and impact of evolving machine learning and blockchain applications in securing IoT firmware. The paper concludes with a summary of ongoing and future research challenges in IoT firmware to facilitate and support secure IoT development.

ViLanIoT: A visual language for improving Internet of Things systems representation

With the rapidly evolving and changing nature of Internet of Things (IoT) technologies, there is an absence of tools to support the IoT system design and development. For example, there is not a specialized tool for representing IoT systems. The common solution to this problem is to use general-purpose modeling tools, such as the Unified Modeling Language (UML) and its extensions, which have some disadvantages when representing IoT systems. This paper proposes a new visual language, called ViLanIoT, for making representations of IoT systems conceived as cyber–physical systems. We argue that diagrams obtained with ViLanIoT are more understandable and intuitive compared to improvised representations found in literature. To illustrate the use of ViLanIoT, we represent a smart campus system with visual elements according to our proposal. In addition, we also present a study of the application of ViLanIoT. In ViLanIoT, the inclusion of visual elements for each component reflecting semantic meaning improves the understandability, clarity, and simplicity of IoT system representations.

Adoption of Internet of Things in Telecommunications: An Emerging Market Case

This paper has presented a case of the adoption of Internet of Things (IoT) technology in telecommunications in Pakistan. Through an exploratory case study, it has explored the need for IoT technology, the role of the telecom sector in IoT development, IoT strategies and business models adopted, challenges confronted, and benefits gained by telecom operators in Pakistan. The business-centric, customer-centric, and country-centric approaches were the basis for IoT technology adoption by telecom operators. By providing networks and connectivity, the telecom sector has played a significant role in the development of IoT. The telecom operators have developed their business strategies and used different business models to capitalize on their digital enabler role in the IoT domain. They also have faced challenges related to technological integration, infrastructure resources, and human resources when adopting IoT technology. The benefits realized by telecom operators were improved operational planning and processes, increased productivity, enhanced organizational performance, and IoT knowledge. These findings can guide practitioners, regulators, and policymakers in understanding the opportunities and implications of IoT in telecommunications.

An RFID-Powered Multisensing Fusion Industrial IoT System for Food Quality Assessment and Sensing

The development in Internet of Things (IoT) have empowered revolution in almost all walks of life. Although substantial effort has been made to bring IoT in manufacturing, there is still technical challenges of providing solutions of real-time pervasive multi-sensing, quality evaluation and boundary-less information sharing, which put people at risk from deteriorated food products and food adulteration. This investigation presents an Industrial IoT-based system for food product quality assessment and prediction. This research completes the real-time food quality assessment via radio frequency identification-based multi-sensor fusion for the first time. Also, a novel concept of shelf-life prediction is proposed. The RFID-powered sensors provide a new idea for nondestructive food product and environment sensing. A five-layer architecture considering sensing, controlling, communication, interfaces, and data analysis is highlighted. A novel RFID metadata structure is first proposed to achieve multi-dimensional information traceability and global data sharing. Machine learning-based multi-sensor fusion is proposed to provide accurate quality assessment and prediction. The proposed system is implemented as a smart shelf system to demonstrate its feasibility and advantages. The system is of great significance in improving food safety, reducing food waste and providing powerful information support for food manufacturing line and supply chain management.

A survey of security challenges, attacks in IoT

A network of linked devices that can gather, process, and exchange data is known as the Internet of Things (IoT). It delivers several benefits such as convenience, efficiency and automation. However, IoT also poses significant security concerns that necessity to be describe like the heterogeneity and diversity of IoT devices with different hardware, software and communication protocols. Now a days the large scale and complexity of IoT systems, which may involve multiple stakeholders, domains and layers. The limited resources and capabilities of IoT devices, which may affect their ability to perform security functions such as encryption, authentication and update. The vital and evolving features of IoT environments, which may introduce new threats and vulnerabilities over time. These challenges require novel and holistic approaches to ensure that privacy and security of IoT systems and its users. With the develop of security standards and best practices for IoT devices and systems it should include Implementation of security by design and security by default principles for IoT development and deployment by adopting risk-based and adaptive security mechanisms for IoT management, operation and enhanced security awareness and education among IoT users and stakeholders.

Design and Implementation of IoT-Based Weather Monitoring System

Due to advancement in technology, various fields have boosted the development of systems that improve people’s life quality, contributing to the welfare of the community by providing relevant and pertinent information for decision-making. On the Internet of Things (IoT), the systems demand measuring and monitoring several environmental variables. The heterogeneity of the captured data and the measuring instruments used to hinder the interoperability among the different components of the IoT. The problems are raised an interest in the development of methods and tools that support the heterogeneity of the data from the sensors, the measurements, and the measuring devices. Some existing tools have resolved some of these interoperability problems. However, it forces to IoT developers to use sensors from specific brands, limiting their generalized use in the community. Furthermore, it is required to solve the challenge of integrating different protocols in a same IoT project. Besides, by generating alerts, it may help making decisions daily, considering the data provided by the sensors. it is required to solve the challenge of integrating different protocols in a same IoT project. To overcome the limitations of the existing glitches, there is need to develop a framework based on network of sensors via software that allows communication-using protocols in a specific environment to monitor the quality of air and to alarm users about this. In this paper, a prototype of proposal is mentioned about the architecture, list of hardware, software and different APIs are utilized to gather data in a systematic way so as users can visualize data in a semantic view. The visualization is shown later by using Matplotlib, Seaborn tools of Machine Learning (ML) and Deep Learning (DL) to plot the temperature along with humidity in a historical span. The result shows that accuracy obtained via Machine Learning Classifier is 87% in the context of Weather Prediction.

SMART-FCD: IOT DATA INTEROPERABILITY USING SENSOR BASED FUZZY LINKED RULES FOR CROSS DOMAIN APPLICATIONS

Internet of Things (IoT) is connected everywhere and enables massive information exchange between objects and people. The unified global IoT must manage a massive amount of data generated by these connected smart which arises the interoperability challenges such as lack of communication protocols, device support, and accepted open standards in smart environments. To combat these issues, a novel Smart-Fuzzy linked rules for Cross Domain application (Smart-FCD) framework is proposed to ensure interoperability by enabling efficient communication and data exchange between multiple platforms and systems. Initially, the heterogenous data from the sensors such as temperature sensors and humidity sensors, and the descriptions are implemented according to the Sensor Measurement List (SenML) language. After composing, semantic modelling will occur which converts the relational data into Resource Description Framework (RDF) format. The Linked Open Vocabulary for the Internet of Things (LOV4IoT) dataset is used to extract interoperable domain knowledge, which is then fed into the related sensor-based fuzzy rules. The IoT preset semantic models which utilise interoperable datasets and domain instances, which are updated via fuzzy association rules. Semantic Web of Things (SWoT) is a technology that assists in creating semantic-based IoT applications, thus IoT developers may use it to create intelligent applications. The sensor data, RDF simulation, evolution time and latency are some of the parameters that are used to evaluate the effectiveness of the proposed Smart-FCD methodology.

Design and Development of IoT based Smart System for Monitoring Laboratory Environment

This study was conducted to address the critical issue of the poor safety management system in laboratories, through the design of a smart laboratory management facility based on the Internet of Things (IoT). In this design, three major safety parameters-fire, temperature and carbon (ii) oxide (CO) levels were monitored by appropriate sensors, which transmit data to the microcontroller (Arduino) for interpretation. The Arduino microprocessor processed the data received from the sensor(s), makes decisions based on the predefined algorithms. Based on the decisions made by the Arduino, the microprocessor sends instructions to a relay module triggered the necessary actions to be taken by the output hardware devices-fire extinguisher, air conditioning system and exhaust fan unit. The temperature monitoring system was designed at an operational range of 18°C to 25°C, the CO control unit was designed to maintain the CO concentration inside the laboratory at a level not exceeding 4 parts per million (ppm), as approved by the World Health Organization; while fire control unit was designed to detect the presence of smoke of naked fire inside the building. In the event that any of these parameters breach safety thresholds, the smart structure's safety system will trigger the appropriate responses. The designed structure was built in compliance with international safety standards. Results obtained through the testing and evaluation of the system revealed that the smart system had overall performance efficiency of 91% and false output of 9%. The system's failure rate of 9% can be reduced by employing advanced sensors and adjusting the delay rate. The findings of this study revealed that IoT and automation can successfully monitor and protect the working environment inside laboratories.

Security Trends in Internet-of-things for Ambient Assistive Living: A Review

Abstract: The Internet of Things (IoT) has revolutionized our society and become indispensable to modern existence. The IoT allows users to access their electronic gadgets from any location. The widespread adoption of IoT across sectors, from manufacturing to surveillance to elder care, has contributed to its rising profile. New security risks and challenges arise with the growth of the IoT. With the development of IoT, the likelihood of an attack by hackers has increased. The burden of addressing these dangers falls on researchers and security professionals. This article looks into the challenges of IoT security in a real-world Ambient Assisted Living (AAL) environment. This work discusses the numerous security attacks employed by cybercriminals in AAL IoT. In addition, this research investigates the varied responses to the risks. We discussed the state-of-the-art technologies available for protecting AAL IoT networks. This work analyses and compares the majority of the latest technologies available. In conclusion, we offer a few suggestions for where the field could go from the current scenario