Internet Of Things Hub Research Articles

IoT-Based Monitoring, Communication, and Control of Small Wind Turbines Using IoT Cloud Service

Addressing global climate change requires a shift to sustainable and renewable energy sources. Utilizing wind power via wind turbines presents a viable remedy. However, because wind patterns are unpredictable and these turbines are located in remote areas, effectively operating wind farms continues to be a difficulty. In this work, we present an integrated system that uses IOT Cloud Service to monitor, connect with, and manage small wind turbines utilizing IoT (Internet of Things) technology. We solve the issues with data collection and control those older turbines without supervisory control and data acquisition (SCADA) systems confront by fusing cloud-enabled IoT hubs with on-site sensing units. Our method guarantees effective control of wind energy devices, two-way communication, and real-time monitoring. With an emphasis on utilizing IoT cloud services, this paper offers a thorough examination of the application of Internet of Things (IoT) technology for the monitoring, communication, and control of tiny wind turbines. In decentralized and off-grid energy applications, small wind turbines are vital, and maximizing energy output and guaranteeing long-term sustainability requires optimizing their performance and maintenance. The scalability, flexibility, and real-time capabilities required to efficiently operate small wind energy projects are sometimes absent from traditional monitoring and control systems.

ROBUST MALWARE DETECTION FOR INTERNET OF (BATTLEFIELD) THINGS DEVICES USING DEEP EIGENSPACE LEARNING

Internet of Things (IoT) in military settings by and large comprises of an assorted scope of Internet- associated gadgets and hubs (for example clinical gadgets and wearable battle outfits). These IoT gadgets and hubs are a significant objective for digital lawbreakers, especially state-supported or country state entertainers. A typical assault vector is the utilization of malware. In this paper, we present a profound learning based strategy to identify Internet Of Battlefield Things (IoBT) malware through the gadget's Operational Code (OpCode) succession. We change OpCodes into a vector space and apply a profound Eigenspace learning way to deal with characterize pernicious and benevolent applications. We likewise show the strength of our proposed approach in malware identification and its manageability against garbage code addition assaults. Ultimately, we make accessible our malware test on Github, which ideally will profit future exploration endeavors (for example to encourage assessment of future malware location draws near)

Centralised Transcutaneous Monitoring using IOT

Abstract: The centralized transcutaneous monitoring using internet of things (IoT) is a cutting-edge healthcare approach that makes use of IoT technology's promise to revolutionize remote patient monitoring. The goal of this work is to enable healthcare professionals to remotely access and monitor crucial patient data to provide fast and accurate diagnoses. The proposed work creates a framework for collecting patient data from transcutaneous monitoring devices by seamlessly integrating IoT devices equipped with WiFi modules. then, this data is sent to the Azure IoT Hub, a cloud-based platform that enables safe, privacy management and storage. According to the Agile methodology, the project progresses through numerous significant phases. These include upgrading the operating system from Windows Embedded Compact (WEC7) to the more modern WEC13, integrating WiFi through Node MCU, establishing a secure data transmission channel between IoT devices and Azure IoT Hub, creating a user-centric web portal using Angular JS, and working actively with the marketing department to match the project with the changing requirements of the healthcare industry. These efforts culminate in an online portal that provides real-time patient data to healthcare providers. This interface provides a wide range of features, such as data visualizations, detailed graphs, and device-specific insights. The initiative redefines the boundaries of patient monitoring and diagnostics, serving as a symbol of the synergy between cutting-edge technology and medical care. The data can be viewed anytime and anywhere by the doctors

A Cloud-Based Cyber-Physical System with Industry 4.0: Remote and Digitized Additive Manufacturing

With the advancement of additive manufacturing (AM), or 3D printing technology, manufacturing industries are driving towards Industry 4.0 for dynamic changed in customer experience, data-driven smart systems, and optimized production processes. This has pushed substantial innovation in cyber-physical systems (CPS) through the integration of sensors, Internet-of-things (IoT), cloud computing, and data analytics leading to the process of digitization. However, computer-aided design (CAD) is used to generate G codes for different process parameters to input to the 3D printer. To automate the whole process, in this study, a customer-driven CPS framework is developed to utilize customer requirement data directly from the website. A cloud platform, Microsoft Azure, is used to send that data to the fused diffusion modelling (FDM)-based 3D printer for the automatic printing process. A machine learning algorithm, the multi-layer perceptron (MLP) neural network model, has been utilized for optimizing the process parameters in the cloud. For cloud-to-machine interaction, a Raspberry Pi is used to get access from the Azure IoT hub and machine learning studio, where the generated algorithm is automatically evaluated and determines the most suitable value. Moreover, the CPS system is used to improve product quality through the synchronization of CAD model inputs from the cloud platform. Therefore, the customer’s desired product will be available with minimum waste, less human monitoring, and less human interaction. The system contributes to the insight of developing a cloud-based digitized, automatic, remote system merging Industry 4.0 technologies to bring flexibility, agility, and automation to AM processes.

Design of Small Multiband Full-Screen Smartwatch Antenna for IoT Applications

Smartwatch is a potential candidate for the Internet of Things (IoT) hub. However, the performance of smartwatch antennas is severely restricted by the smartwatch structure, especially when the antennas are designed by traditional methods. For adapting smartwatches to the role of IoT hub, a novel method of designing multi-band smartwatch antenna is presented in this paper, aiming at increasing the number of frequency bands, omni-directivity, and structural suitability. Firstly, the fundamental structure (including the full screen and the system PCB) of the smartwatch is analyzed as a whole by characteristic mode analysis (CMA). Thus, abundant resources of characteristic modes are introduced. The fundamental structure is then modified as the radiator of a multi-band antenna. Then, a non-radiating capacitive coupling element (CCE) excites the desired four 0.5-wavelength modes from this structure. This method could fully utilize the intrinsic modes of the smartwatch structure itself, thus exhibits multiple advantages: significantly small size, smaller ground, omni-directional radiation, and fitting to the full-screen smartwatch structure.

Which Way to Cope with COVID-19 Challenges? Contributions of the IoT for Smart City Projects

Many activities and sectors have come to a halt due to the COVID-19 crisis. People and workers’ habits and behaviors have changed dramatically, as the use of technologies and connections, virtual reality, and remote support have been enhanced. Businesses and cities have been forced to quickly adapt to the new challenges. Digital technologies have allowed people to have better access to public services due to improved use of resources. Smart cities have significant potential for linking people to work and services as never done before. Additionally, the technological convergence produces data that can enhance interactions and decisions toward the “new normal”. In this paper, the aim is to assess how Portugal is prepared to respond to the accelerated process that this context demands from cities. Portuguese SMEs have developed a good capacity for entrepreneurship and innovation; however, they are still behind in converting the knowledge acquired in sales and exports and there is still limited collaboration at the public-private level. The acceleration of smart cities through the Internet of Things (IoT) may encourage changes in these issues. A more assertive alignment between the emergent technologies and the digitization goals of companies is required. This paper opens a discussion around major needs and trends of IoT (and related technologies) since the pandemic has leveraged them. The relationship between innovation and city smartness is approached to assess main contributing and limiting variables (through the European Innovation Scoreboard), to clarify future directions toward smarter services. The tourism sector, as the largest export economic activity in the country, is addressed in this matter. An analytical framework (using, for example, Power BI and Azure IoT Hub) around this approach can choose and support the most suitable areas of development in the country.

MoSIoT: Modeling and Simulating IoT Healthcare-Monitoring Systems for People with Disabilities.

The need to remotely monitor people with disabilities has increased due to growth in their number in recent years. The democratization of Internet of Things (IoT) devices facilitates the implementation of healthcare-monitoring systems (HMSs) that are capable of supporting disabilities and diseases. However, to achieve their full potential, these devices must efficiently address the customization demanded by different IoT HMS scenarios. This work introduces a new approach, called Modeling Scenarios of Internet of Things (MoSIoT), which allows healthcare experts to model and simulate IoT HMS scenarios defined for different disabilities and diseases. MoSIoT comprises a set of models based on the model-driven engineering (MDE) paradigm, which first allows simulation of a complete IoT HMS scenario, followed by generation of a final IoT system. In the current study, we used a real scenario defined by a recognized medical publication for a patient with Alzheimer’s disease to validate this proposal. Furthermore, we present an implementation based on an enterprise cloud architecture that provides the simulation data to a commercial IoT hub, such as Azure IoT Central.

A distributed system for supporting smart irrigation using Internet of Things technology

AbstractIn this paper, we present the design and implementation of a smart irrigation system using Internet of Things (IoT) technology, which can be used for automating the irrigation process in agricultural fields. It is expected that this system would create a better opportunity for farmers to irrigate their fields efficiently, as well as eliminating the field's under‐watering, which could stress the plants. The developed system is organized into three parts: sensing side, cloud side, and user side. We used Microsoft Azure IoT Hub as an underlying infrastructure to coordinate the interaction between the three sides. The sensing side uses a Raspberry Pi 3 device, which is a low‐cost, credit‐card sized computer device that is used to monitor in near real‐time soil moisture, air temperature and relative humidity, and other weather parameters of the field of interest. Sensors readings are logged and transmitted to the cloud side. At the cloud side, the received sensing data is used by the irrigation scheduling model to determine when and for how long the water pump should be turned on based on a user‐predefined threshold. The user side is developed as an Android mobile app, which is used to control the operations of the water pump with voice recognition capabilities. Finally, this system was evaluated using various performance metrics, such as latency and scalability.

WITHDRAWN: Smart campus student management system based on 5G network and Internet of Things

Abstraction Smart Campus and Smart University Internet of Things (IoT) arrangement distributed computing for observing utilizing IT foundation like those utilized in keen urban areas utilizing the Internet, enact a majority of frameworks of college you at that point. A difficult that is as yet numerous colleges, has stayed at the phase of advanced grounds. It is hard to finish the change from the advanced grounds to keen grounds. The primary issue is, however that is the grounds have the main information, and it has been digitized with no data. Consequently, not just the savvy grounds, it is important to give network between the most recent radio and IoT hubs and colleges to give great correspondence wired innovation passage, and all the more exactly, energy utilization not just diminishes not just create models, hubs to boost battery life mono Internet. The use of the most recent key innovation is the start of the advancement of savvy grounds and colleges. Smart Campus/University, are the most pertinent grounds brilliant extension, and the most recent depicted in detail the fundamental qualities of the correspondence design and cycle after characterized. Thusly, helpful direction for the future organizer of the University will be answerable for making the Internet and savvy grounds and age of college improvement of the things of the provider.

A Prospect Theoretic Approach for Trust Management in IoT Networks Under Manipulation Attacks

As Internet of Things (IoT) and Cyber-Physical systems become more ubiquitous in our daily lives, it necessitates the capability to measure the trustworthiness of the aggregate data from such systems to make fair decisions. However, the interpretation of trustworthiness is contextual and varies according to the risk tolerance attitude of the concerned application. In addition, there exist varying levels of uncertainty associated with an evidence upon which a trust model is built. Hence, the data integrity scoring mechanisms require some provisions to adapt to different risk attitudes and uncertainties. In this article, we propose a prospect theoretic framework for data integrity scoring that quantifies the trustworthiness of the collected data from IoT devices in the presence of adversaries who try to manipulate the data. In our proposed method, we consider an imperfect anomaly monitoring mechanism that tracks the transmitted data from each device and classifies the outcome (trustworthiness of data) as not compromised, compromised, or undecided . These outcomes are conceptualized as a multinomial hypothesis of a Bayesian inference model with three parameters. These parameters are then used for calculating a utility value via prospect theory to evaluate the reliability of the aggregate data at an IoT hub. In addition, to take into account different risk attitudes, we propose two types of fusion rule at IoT hub—optimistic and conservative. Furthermore, we put forward asymmetric weighted moving average scheme to measure the trustworthiness of aggregate data in presence of On-Off attacks. The proposed framework is validated using extensive simulation experiments for both uniform and On-Off attacks. We show how trust scores vary under a variety of system factors like attack magnitude and inaccurate detection. In addition, we measure the trustworthiness of the aggregate data using the well-known expected utility theory and compare the results with that obtained by prospect theory. The simulation results reveal that prospect theory quantifies trustworthiness of the aggregate data better than expected utility theory.

Model-Based Interoperability IoT Hub for the Supervision of Smart Gas Distribution Networks

Industrial monitoring environments have evolved from single monolithic systems to widely distributed heterogeneous systems. These include the Internet of Things (IoT), Industrial IoT, Cyber-Physical Systems, and Enterprise Application. One of the key challenges is the integration of heterogeneous systems and data exchange interoperability. In the industrial smart gas project, in which this work takes place, current standard-based or middleware solutions are not sufficient to handle these issues and often require specific ad hoc developments. This paper proposes a generic, modular, and extensible interoperability architecture based on modeling principles. We provide a free software implementation and illustrate the approach on industrial use cases. Some criteria are then proposed for a first qualitative evaluation.

Exploring the key services and players in the smart car market

The traditional role of cars as a means of transport is now expected to undergo major changes as a result of the emerging smart car industry, whereby connection to the Internet can not only improve traffic safety by enabling self-driving but also entertain passengers. Under these circumstances, it is important to explore the killer services that are expected to be in high demand by consumers and keystone players in the emerging market. This study identifies the promising services from a consumer's perspective using analytic hierarchy process analysis and examines experts' views on which industries and firms, as keystone players, are expected to provide the competitive killer services in the market. The results show that the service that consumers find the most important is driving assistance, followed by infotainment and Internet of Things hubs. Meanwhile, the experts rank the importance of industrial player as in the order of Information Technology device manufacturers, followed by platform providers, automobile manufacturers, and network providers, while at the company level, the rank is in the order of Samsung Electronics, Hyundai Motor, Naver, and SK Telecom, respectively. These findings show that consumers regard smart cars as futuristic vehicles, yet continue to emphasize their conventional value as a means of transport, while the experts expect that among the various industry players, IT companies are most likely to enable the concept of the smart car to become a reality.

Automation of an IoT hub using artificial intelligence techniques

Fog computing is used for reducing the complexity level of a network architecture and processes the data in a fog node IoT Hub. The Internet of Things (IoT) will connect billions of devices, such as smart objects, which are heterogeneous in terms of hardware software and communication interfaces. The IoT has to this point grown as numerous vertical idea of the IoT, rather than focusing at the real creation of a highly interoperable infrastructure for the development of applications. For managing the various devices present in the hub we create an IP-based infrastructure so that the elements can be able to balance the diversified devices and the network elements are used to enhance the direct end to end communication which is much required. With all the above considerations we propose a Fog node i.e. an IoT hub that can be placed at the end of multiple networks thereby increasing the capability by implementing various functions such as allocation of resources border routers cache proxy servers etc. As the implementation of fog node is through the IoT hub here we would like to automate the resource allocation that takes place in the IoT hub.

Osmotic Message-Oriented Middleware for the Internet of Things

Message-oriented middleware is a key technology in todays Internet of Things (IoT). Centralized message brokers facilitate decoupled device-to-device communication and can transparently scale to handle many millions of messages per second. However, Cloud-based solutions, such as AWS IoT or Azure IoT Hub, cannot satisfy the stringent QoS and privacy requirements of many modern IoT scenarios. Instead, distributed middleware needs to leverage the ever- increasing amount of resources at the edge of the network to provide reliable, ultra-low-latency, and privacy-aware message routing. But the heterogeneity and volatility inherent to Edge resources, and the unpredictability of mobile clients, make it extremely challenging to provide resilient coordination mechanisms and guaranteed message delivery. Applying Osmotic Computing principles to message-oriented middleware opens new opportunities for solving these challenges.

IoT and Its Implications for Informed Consent

This report is based on a three-hour long workshop between representatives of the PETRAS IoT Hub, Pinsent Masons, and the HMG Department for Transport. The workshop is part of an ongoing investigation that explores the connections between some of the different dimensions likely to shape conceptions and applications of consent in the emerging Internet of Things (IoT). The impetus for the workshop was the recognition that two significant developments will challenge conventional approaches to online consent. From a technical perspective, the IoT will significantly increase personal data collection, use and re-use. From a regulatory perspective, the General Data Protection Regulation (GDPR) which comes into force in May 2018, will make much higher demands on practices of giving and obtaining consent. Combined, these two factors suggest that consent will be a major issue for all actors in the next five years and it requires some careful analysis now in order to adequately prepare for these developments.

Internet Orchestra of Things: A Different Perspective on the Internet of Things

The Internet of Things (IoT) is defined as a global network that links together living and/or non-living entities, such as people, animals, software, physical objects or devices. These entities can interact with each other, gather, provide or transmit information to the IoT. Although the Internet of Things is a relatively new concept, various platforms are already available. Some of them are open platforms, enabling both the integration of people, systems, and objects from the physical and virtual world, and the visualization of data. For example, there are already some IoT platforms used, like Google Cloud Platform, Microsoft Azure IoT Hub, Amazon Web Services IoT Platform, IBM Watson IoT Platform, Nimbits, Open.Sen.se, ThingWorx, and ThingSpeak. But what if things could not only “work” and “speak”, but also “sing”? We propose a game in which the things connected to IoT can play in real time different sounds, according to the values of some monitored parameters. These things can be grouped in the IoT platform to create a virtual orchestra and make music. Besides this game allowing the creation of great songs, it can be widely used to explain the new ideas behind the fast emerging areas of the Internet of Things. In addition to many technical challenges, it is also worth considering the effect the IoT concept will have on people, society, and economy as a whole.

DESIGN AND IMPLEMENT AN INTEROPERABLE INTERNET OF THINGS APPLICATION BASED ON AN EXTENDED OGC SENSORTHINGS API STANDARD

Abstract. The Internet of Things (IoT) is an infrastructure that interconnects uniquely-identifiable devices using the Internet. By interconnecting everyday appliances, various monitoring and physical mashup applications can be constructed to improve people’s daily life. However, IoT devices created by different manufacturers follow different proprietary protocols and cannot communicate with each other. This heterogeneity issue causes different products to be locked in multiple closed ecosystems that we call IoT silos. In order to address this issue, a common industrial solution is the hub approach, which implements connectors to communicate with IoT devices following different protocols. However, with the growing number of proprietary protocols proposed by device manufacturers, IoT hubs need to support and maintain a lot of customized connectors. Hence, we believe the ultimate solution to address the heterogeneity issue is to follow open and interoperable standard. Among the existing IoT standards, the Open Geospatial Consortium (OGC) SensorThings API standard supports comprehensive conceptual model and query functionalities. The first version of SensorThings API mainly focuses on connecting to IoT devices and sharing sensor observations online, which is the sensing capability. Besides the sensing capability, IoT devices could also be controlled via the Internet, which is the tasking capability. While the tasking capability was not included in the first version of the SensorThings API standard, this research aims on defining the tasking capability profile and integrates with the SensorThings API standard, which we call the extended-SensorThings API in this paper. In general, this research proposes a lightweight JSON-based web service description, the “Tasking Capability Description”, allowing device owners and manufacturers to describe different IoT device protocols. Through the extended- SensorThings API, users and applications can follow a coherent protocol to control IoT devices that use different communication protocols, which could consequently achieve the interoperable Internet of Things infrastructure.

DESIGN AND IMPLEMENT AN INTEROPERABLE INTERNET OF THINGS APPLICATION BASED ON AN EXTENDED OGC SENSORTHINGS API STANDARD

The Internet of Things (IoT) is an infrastructure that interconnects uniquely-identifiable devices using the Internet. By interconnecting everyday appliances, various monitoring and physical mashup applications can be constructed to improve people’s daily life. However, IoT devices created by different manufacturers follow different proprietary protocols and cannot communicate with each other. This heterogeneity issue causes different products to be locked in multiple closed ecosystems that we call IoT silos. In order to address this issue, a common industrial solution is the hub approach, which implements connectors to communicate with IoT devices following different protocols. However, with the growing number of proprietary protocols proposed by device manufacturers, IoT hubs need to support and maintain a lot of customized connectors. Hence, we believe the ultimate solution to address the heterogeneity issue is to follow open and interoperable standard. Among the existing IoT standards, the Open Geospatial Consortium (OGC) SensorThings API standard supports comprehensive conceptual model and query functionalities. The first version of SensorThings API mainly focuses on connecting to IoT devices and sharing sensor observations online, which is the sensing capability. Besides the sensing capability, IoT devices could also be controlled via the Internet, which is the tasking capability. While the tasking capability was not included in the first version of the SensorThings API standard, this research aims on defining the tasking capability profile and integrates with the SensorThings API standard, which we call the extended-SensorThings API in this paper. In general, this research proposes a lightweight JSON-based web service description, the “Tasking Capability Description”, allowing device owners and manufacturers to describe different IoT device protocols. Through the extended- SensorThings API, users and applications can follow a coherent protocol to control IoT devices that use different communication protocols, which could consequently achieve the interoperable Internet of Things infrastructure.