Internet Of Things Perspective Research Articles

Energy-Efficient Task Scheduling Based on Traffic Mapping in Heterogeneous Mobile-Edge Computing: A Green IoT Perspective

As a key enabler of emerging 6G applications, mobile edge computing (MEC) improves the system performance by coordinating the computation resources between the mobile devices and edge. However, the energy consumption and carbon emission are boosted as the device number increases. This paper constructs a hierarchical network-assisted task offloading architecture for Green Internet of Things (IoT). Then the authors propose an energy-efficient scheduling based on traffic mapping with energy slack-space proportional pre-allocation algorithm (ESTMP) in the heterogeneous edge computing system to minimize the schedule length under certain energy constraints. The proposed algorithm is suitable for delay-sensitive mobile applications such as Augmented Reality (AR)/Virtual Reality (VR)/Mixed Reality (MR), which process massive multi-modal data. Simulation results demonstrate the significant advantages of the algorithm in terms of the schedule length of arriving parallel tasks, resource utilization and energy consumption.

Smart Energy Meters for Smart Grids, an Internet of Things Perspective

Smart energy has evolved over the years to include multiple domains integrated across multiple technology themes, such as electricity, smart grid, and logistics, linked through communication technology and processed in the cloud in a holistic way to deliver on global challenges. Advances in sensing, communication, and computation technologies have been made that enable better smart system implementations. In smart energy systems, sensing technologies have spanned multiple domains with newer techniques that are more accurate, have greater dynamic ranges, and are more reliable. Similarly, communication techniques have now evolved into very high-speed, flexible, and dynamic systems. Computation techniques have seen a quantum leap with greater integration, powerful computing engines, and versatile software stacks that are easily available and modifiable. Finally, the system integration has also seen advances in the form of management, automation, and analytics paradigms. Consequently, smart energy systems have witnessed a revolutionary transformation. The complexity has correspondingly grown exponentially. With regard to smart meters, the measurement component has to scale up to meet the demands of the evolved energy eco-system by relying on the advancements offered. The internet of things (IoT) is a key technology enabler in this scenario, and the smart meter is a key component. In recent years, metering technology has evolved in both complexity and functionality. Therefore, it must use the advances offered by IoT to deliver a new role. The internet of things (IoT) is a key technology enabler in this scenario and the smart meter a key component. In recent years, metering technology has evolved in both complexity and functionality. To deliver on its new role, it must use the advances offered by IoT. In this review, we analyze the smart meter as a combination of sensing, computing, and communication nodes for flexible and complex design paradigms. The components are, in turn, reviewed vis-à-vis the advances offered by IoT. The resultant gaps are reported for future design challenges in the conclusion. The identified gaps are the lack of usage of the full spectrum of the available technology and the lack of an inter-disciplinary approach to smart meter design.

MultiCNN-FilterLSTM: Resource-efficient sensor-based human activity recognition in IoT applications

With the recent advances in the Internet of Things (IoT) technologies, various human-centered applications have proliferated and improved the quality of users’ life. In the meantime, human activity recognition (HAR) has been considered as an essential component of human-centered applications in IoT due to its capability of providing substantial information about the user states. Whereas deep learning-based HAR methods have been recently proposed, there are still rooms to improve the HAR models, particularly from the perspective of IoT, as the models need to be precise but resource efficient. In this paper, to support IoT systems that require a resource-efficient model, we thereby propose a deep learning-based HAR model, called MultiCNN-FilterLSTM that combines a multihead convolutional neural network (CNN) with a long–short-term memory (LSTM) through a residual connection in which feature vectors are efficiently processed in hierarchical order. Accordingly, a novel approach to using LSTM cells, which we call filterwise LSTM (FilterLSTM), is proposed whereby the HAR model can learn the dependencies among the features at different hierarchical levels. The proposed HAR model has been exhaustively evaluated on two publicly available datasets. The proposed HAR model enhances the classification accuracy by 2.3%–4.4%, while it requires 21%–70% fewer operations than the state-of-the-art models. In addition, the proposed model is deployed to a Raspberry Pi 4 for further analysis in terms of deployment. The experimental results are presented to verify the merits of the proposed HAR model compared to the state-of-art models by exploiting hierarchical relationships and to deliver significant insights on the effectiveness of the proposed FilterLSTM from the perspective of the IoT system.

The Panel Spatial Econometric Analysis for Development of Green Intensive Agriculture Based on Edge Computing and Internet of Things.

To further promote the modernization of agriculture and the prosperity of green industry, the analyses are made on the intensive level of agriculture by using spatial econometric model under the Internet of Things (IoT), and the optimal defense strategy is adopted for edge network equipment to ensure the security of agricultural information. Initially, the present work introduces the related concepts of agricultural intensive development and analyzes the important role of IoT in the development process of agricultural modernization. Next, it briefly explains the spatial econometric analysis method, introduces two basic spatial analysis models-spatial lag model (SLM) and spatial error model (SEM), and explains their principles in detail. Then, it signifies the characteristics of IoT and edge computing (EC) and designs the optimal defense strategy of edge network equipment from the perspective of IoT. Finally, the simulation experiment is carried out based on the edge network defense strategy, and the spatial econometric analysis is carried out by taking the agricultural intensive development of counties in a Chinese province as an example. The experimental results show that with the increase of the number of edge network devices, the optimal strategy of edge network defense can be adopted while consuming certain computing resources. The agricultural technology input and intensive level in the jurisdiction have high spatial correlation, so it is necessary to establish a spatial econometric model for analysis. Additionally, the statistics of SLM is higher than that of SEM, which shows that SLM can better reflect the technology investment and spatial correlation than SEM does. Both industrial and agricultural division of labor and agricultural production link division of labor can promote the level of intensification, among which the promotion of industrial and agricultural division of labor is not very significant, while the promotion of agricultural production link division of labor is very significant.

Integrating the business networks and internet of things perspectives: A system of systems (SoS) approach for industrial markets

In industrial business-to-business (B2B) markets, physical entities (such as products, machines, materials, or other objects) are increasingly connected among each other. This Industrial Internet of Things (IIoT) is quickly developing thanks to advances in fields such as information systems, factory digitalization, data sciences, robotics. Thus, industrial markets appear both as business networks - encompassing connections between individual or organizational actors – and networks of connected things. The purpose of this research is to provide an integrative perspective that encompasses both types of networks. It seeks to contribute to the literature on industrial B2B markets in two ways. First, it proposes the system of systems (SoS) theory - which emphasizes diversity and autonomy of systems - as an integrative perspective. Second, it argues that this integrated perspective contributes to a new view on how resources are produced, combined, and used, and, therefore, on business network models. We discuss the implications for one of the most established models, the IMP Group's A-R-A model.

Sucre4Stem: Collaborative Projects Based on IoT Devices for Students in Secondary and Pre-University Education

This paper describes a new technological evolution of the <i>Sucre</i> project, which aims to foster a vocation for science and develop computational thinking and programming skills in pre-university students. This improved version is called <i>Sucre4Stem</i> and has been designed from the Internet of Things perspective. At a technological level, we differentiate two main tools, <i>SucreCore</i> and<i>SucreCode</i>. <i>SucreCore</i> provides a new, more compact design, encapsulates an advanced microcontroller and supports wireless connectivity with the ability to create online variables and functions. <i>SucreCode</i>, the block-based visual programming tool, has a revamped interface and allows wireless communication with <i>SucreCore</i>. At the pedagogical level, Sucre4Stem makes it easier to implement new group dynamics and to create novel types of collaborative projects between groups of students. In this article, we also explore how these collaborative projects can be carried out by taking advantage of the different types of communications between <i>SucreCore</i> and the server-side platform using shared online variables and functions.

Machine learning and Artificial Intelligence for Cyber security In Internet of Things Perspective

Machine learning and Artificial Intelligence for Cyber security In Internet of Things Perspective

Big Data Security Issues from the Perspective of IoT and Cloud Computing: A Review

Background: The data is one of the prime assets in today’s world. The continuous data generation ultimately creates huge volume of data that cannot be processed or stored by a normal relational database management system. This problem is addressed by a new concept: Big Data. Apart from the size of data, security and privacy of data are the more challenging issues in Big data technology. Objective: The primary objective of the research is to identify the potential security threats of different big data computing technologies and provide a defense mechanism to mitigate the issues. Methods: To identify the security issues, different existing big data systems are thoroughly analysed and observed. Security systems are completely dependent on the system architecture. This can be a single architecture (dependent on one computing technology) or multi architecture type (dependent on multiple computing technologies). The internal mechanism of different technologies is observed and how the attacks change the behavioural pattern of the systems is the main backbone of the research. Based on the behaviour of dissimilar attacks, a comprehensive defense mechanism is identified. Security and privacy challenges of mobile healthcare are also considered as a case study. Results: The complete lists of big data computing security threats in different layers of the systems are identified. Through this research the remedial measures of the different attacks are found. The security challenges of mobile healthcare technology and its predictive measurements are sorted out. The changes of big data security systems behaviour based on its architecture are of the major findings of this research. Conclusion: The integration of mobile healthcare along with Internet of Things (IoT) and blockchain computing can enhance the system level and hence security threats can be minimized.

Review on Online Monitoring and Control in Industrial Automation–An IoT Perspective

Internet of things (IoT) is developing much fast than any other technology. IoT framework can be called as a gathering of smart gadgets that connect on a shared premise to satisfy a shared objective. IoT systems may use different processing and communication architectures, technologies, and design methodologies. This selection is based on the target it must be achieved. This review work focussed on the step into the different communication protocols used in IoT systems.

Application Domains, Evaluation Data Sets, and Research Challenges of IoT: A Systematic Review

We are at the brink of Internet of Things (IoT) era where smart devices and other wireless devices are redesigning our environment to make it more correlative, flexible, and communicative. IoT is now evolving to Internet of Everything, as it incorporates and builds a system that includes wireless networks, sensors, cloud servers, analytics, smart devices, and advanced technologies. The IoT systems are equipped with embedded devices having network connectivity and sensors to have a machine-to-machine interaction. The field of IoT is advancing to provide smart solutions to various applications, such as transportation, healthcare, farming, to name a few. Considering the diverse perspective of IoT systems/network, this article aims at discussing different applications of IoT across various research domains and to highlight the use of IoT in a variety of applications. We have systematically reviewed applications of IoT with the data sets to understand the characteristics of the data collected by the IoT devices. In this article, a comprehensive survey on the role of IoT in various application domains is presented for the years 2015-2019. This article lists different commercialized solutions developed in various IoT application domains. The aim to discuss commercialized IoT paradigms is to highlight research efforts performed in the field of IoT that have been transformed into real-life solutions. This article also discusses research challenges in the field of IoT to strengthen the research for developing future IoT applications.

Energy Perspectives in IoT Driven Smart Villages and Smart Cities

The Internet-of-Things (IoT) consists of a large number of different and heterogeneous devices under one umbrella. Building a typical architecture for the devices used in IoT is a challenge due to the involvement of a vast number of devices, layers, protocols, middleware, and software. The sensors in IoT have to monitor the activities regularly, making the end node devices energy hungry. Traditional fixed batteries get drained out in limited time, requiring continuous replacement, thereby increasing the budget. This article focuses on consumer technologies in the perspective of IoT computing targeted for smart villages and smart cities. The article discusses security-by-design (SbD) concepts in the energy harvester technologies for sustainable and secured IoT with uninterrupted energy resource smart villages and smart cities.

Improving supply chain collaboration through operational excellence approaches: an IoT perspective

PurposeCollaboration is an important emerging dimension of sustainable supply chain management. How to improve supply chain collaboration (SCC) by means of operational excellence approaches has become an important research topic. The Internet of things (IoT), an important means of operational excellence, has also received increased attention. For better collaboration by the IoT, this study proposes a novel methodology to evaluate the measures of IoT adoption in SCC.Design/methodology/approachBased on the six-domain model and the common classification of collaboration, the measures of the IoT and the criteria of SCC are developed, respectively. A hybrid multi-step methodology that combines neutrosophic set theory, analytic hierarchy process (AHP) and technology for order preference by similarity to an ideal solution (TOPSIS) is proposed to complete the evaluation.FindingsThe results show that improving information transparency, strengthening the integration of management information systems and improving large data processing abilities are the most important measures of the IoT in improving SCC. Measures such as introducing sensing technology and laser scanning technology rank at the bottom and are relatively unimportant.Practical implicationsThe research results provide insights and references for firms to improve SCC by adopting appropriate IoT measures.Originality/valueMost of existing studies indicate the significance of technology in SCC. But this study shows a different conclusion that technologies rank the bottom, while information transparency is more important. And a suitable explanation is given. It further enriches the theoretical studies in SCC field.

Immersive Interconnected Virtual and Augmented Reality: A 5G and IoT Perspective

Despite remarkable advances, current augmented and virtual reality (AR/VR) applications are a largely individual and local experience. Interconnected AR/VR, where participants can virtually interact across vast distances, remains a distant dream. The great barrier that stands between current technology and such applications is the stringent end-to-end latency requirement, which should not exceed 20 ms in order to avoid motion sickness and other discomforts. Bringing AR/VR to the next level to enable immersive interconnected AR/VR will require significant advances towards 5G ultra-reliable low-latency communication (URLLC) and a Tactile Internet of Things (IoT). In this article, we articulate the technical challenges to enable a future AR/VR end-to-end architecture, that combines 5G URLLC and Tactile IoT technology to support this next generation of interconnected AR/VR applications. Through the use of IoT sensors and actuators, AR/VR applications will be aware of the environmental and user context, supporting human-centric adaptations of the application logic, and lifelike interactions with the virtual environment. We present potential use cases and the required technological building blocks. For each of them, we delve into the current state of the art and challenges that need to be addressed before the dream of remote AR/VR interaction can become reality.

Impact of an Integrated Approach in Disaster Management

In recent times, there have been several natural disasters, negatively affecting communities ranging from loss of lives, businesses, homes and economic disruption. Such serious effects on a community can be traced to poor disaster management arrangements. Several project management concepts as well as technologies have been researched and proven to improve disaster management. This article reviews existing literatures to make evident the concepts of project management such as project planning, execution, team collaboration and governance as well as technologies with a focus on the Internet of Things (IoT) through provision of early warning signs for mitigation and preparedness, big data analytics (BDA) for information gathering and unmanned aerial vehicles (UAVs) for emergency relief scenarios in disaster management. Findings of this article reveals the great impact and benefit of an integrated approach for effective disaster management. Hence, this paper recommends an integrated approach to disaster management from a project management and Internet of Things perspective.

Bikesharing ako nástroj regionálneho rozvoja z pohľahu IoT

A smart city is where networks and services become more efficient, using digital and telecommunications technologies in the country's population and businesses. One way to ensure the intelligent use of digital and telecommunications technologies for sound city governance can be the Internet of Things (IoT). The emphasis on the development of urban areas is based primarily on demographic statistics, which predict an increasing proportion of the urban population in the future. The aim of the paper is to provide an elementary framework for bikesharing as a tool for regional development from the perspective of IoT.

Communication Aspects of the Integration of Wireless IoT Devices with Distributed Ledger Technology

The pervasive need to safely share and store information between devices calls for the replacement of centralized trust architectures with decentralized ones. DLTs are seen as the most promising enabler of decentralized trust, but they still lack technological maturity, and their successful adoption depends on the understanding of the fundamental design trade-offs and their reflection in the actual technical design. This work focuses on the challenges and potential solutions for an effective integration of DLTs in the context of the Internet of Things (IoT). We first introduce the landscape of IoT applications and discuss the limitations and opportunities offered by DLTs. Then we review the technical challenges encountered in the integration of resource-constrained devices with distributed trust networks. We describe the common traits of lightweight synchronization protocols, and propose a novel classification rooted in the IoT perspective. We identify the need for receiving ledger information at the endpoint devices, implying a two-way data exchange that contrasts with the conventional uplink-oriented communication technologies intended for IoT systems.

A Review of Insider Threat Detection Approaches With IoT Perspective

Security professionals, government agencies, and corporate organizations have found an inherent need to prevent or mitigate attacks from insider threats. Accordingly, active research on insider threat detection has been conducted to prevent and mitigate adverse effects such as leakage of valuable information that may be caused by insiders. Along with the growth of Internet-of-Things (IoT), new security challenges arise in the existing security frameworks. Attack surfaces are significantly enlarged which could cause a severe risk in terms of company insider threat management. In this work, we provide a generalization of aspects of insider threats with IoT and analyze the surveyed literature based on both private and public sources. We then examine data sources considering IoT environments based on the characteristics and the structure of IoT (perceptual, network, and application layers). The result of reviewing the study shows that using the data source of the network and application layer is more suitable than the perceptual layer in the IoT environment. We also categorized each layer’s data sources according to their features, and we investigated research objectives and methods for each category. Finally, the potential for utilization and limitations under the IoT environment are presented at the end of each layer examination.

An IoT based Approach for Efficient Home Automation with ThingSpeak

With passage of time, technology is rapidly growing. People and daily life processes are highly dependent on internet. The Internet of Things (IoT) is an area of magnificent impact, growth and potential with the advent and rapid growth of smart homes, smart agriculture, smart cities and smart everything. Internet of Things (IoT) construct an environment in which everything is integrated and digitalized. People depend on smart phones and want to do their daily routine tasks in easy and quick way. Ordinary homes consist of multiple digital appliances that are controlled or managed by individual remote systems. It’s very hectic to use multiple individual remotes to control various component of homes. In current technological era, rather than home appliances, almost all type of home components available in digital forms. Various home automation systems with different specifications and implementations were proposed in literature. This research objective is to introduce an IoT based approach for efficient home automation system using Arduino and ThingSpeak. We have automated almost all essential aspects of smart home. Proposed system is efficient in terms of low power consumption, green building and increases the life of digital appliances. ThingSpeak cloud platform is used to integrate the home components; analyze and process the data. State of the art MQTT protocol is implemented for LAN communication. This paper will provide a path to IoT developers and researchers to sense, digitalize and control the homes in perspective of future IoT. Moreover, this work is serving as an instance of how life will be easier with the help of IOT applications.

A Multi-Protocol IoT Platform Based on Open-Source Frameworks.

Internet of Things (IoT) technologies have evolved rapidly during the last decade, and many architecture types have been proposed for distributed and interconnected systems. However, most systems are implemented following fragmented approaches for specific application domains, introducing difficulties in providing unified solutions. However, the unification of solutions is an important feature from an IoT perspective. In this paper, we present an IoT platform that supports multiple application layer communication protocols (Representational State Transfer (REST)/HyperText Transfer Protocol (HTTP), Message Queuing Telemetry Transport (MQTT), Advanced Message Queuing Protocol (AMQP), Constrained Application Protocol (CoAP), and Websockets) and that is composed of open-source frameworks (RabbitMQ, Ponte, OM2M, and RDF4J). We have explored a back-end system that interoperates with the various frameworks and offers a single approach for user-access control on IoT data streams and micro-services. The proposed platform is evaluated using its containerized version, being easily deployable on the vast majority of modern computing infrastructures. Its design promotes service reusability and follows a marketplace architecture, so that the creation of interoperable IoT ecosystems with active contributors is enabled. All the platform’s features are analyzed, and we discuss the results of experiments, with the multiple communication protocols being tested when used interchangeably for transferring data. Developing unified solutions using such a platform is of interest to users and developers as they can test and evaluate local instances or even complex applications composed of their own IoT resources before releasing a production version to the marketplace.

An overview of data fusion techniques for Internet of Things enabled physical activity recognition and measure

Due to importantly beneficial effects on physical and mental health and strong association with many rehabilitation programs, Physical Activity Recognition and Measure (PARM) has been widely recognised as a key paradigm for a variety of smart healthcare applications. Traditional methods for PARM relies on designing and utilising Data fusion or machine learning techniques in processing ambient and wearable sensing data for classifying types of physical activity and removing their uncertainties. Yet they mostly focus on controlled environments with the aim of increasing types of identifiable activity subjects, improved recognition accuracy and measure robustness. The emergence of the Internet of Things (IoT) enabling technology is transferring PARM studies to an open and dynamic uncontrolled ecosystem by connecting heterogeneous cost-effective wearable devices and mobile apps and various groups of users [35]. Little is currently known about whether traditional Data fusion techniques can tackle new challenges of IoT environments and how to effectively harness and improve these technologies. In an effort to understand potential use and opportunities of Data fusion techniques in IoT enabled PARM applications, this paper will give a systematic review, critically examining PARM studies from a perspective of a novel 3D dynamic IoT based physical activity collection and validation model. It summarized traditional state-of-the-art data fusion techniques from three plane domains in the 3D dynamic IoT model: devices, persons and timeline. The paper goes on to identify some new research trends and challenges of data fusion techniques in the IoT enabled PARM studies, and discusses some key enabling techniques for tackling them.