Advances In Internet Of Things Research Articles

Reliability Modeling of Mesh Storage Area Networks for Internet of Things

With advances in Internet of Things (IoT), intelligent data sensors are being added to more and more devices that interact with human’s daily life in areas, such as medical services, smart grids, and financial services. IoT has made big contributions to data growth, requiring highly reliable data storage solutions. Storage area networks (SANs) are one of such solutions. To meet high reliability and availability requirements, SANs have to provide fault tolerance through redundancy to minimize or eliminate system downtime, thus preventing business discontinuity due to catastrophic events. Mesh is one of the common SAN topologies that have been applied to implement a fault tolerant SAN in practice. In this paper, failure behavior of a mesh SAN is modeled using a dynamic fault tree (DFT) in the case of perfect links, or a network graph in the case of imperfect links. Based on the constructed DFT or network graph model, reliability of the mesh SAN is evaluated using a binary decision diagram-based method. Results obtained from the case study can provide insights into the behavior of general mesh SAN systems, providing guidelines in the reliable design and operation of SANs.

Non-parametric sequence-based learning approach for outlier detection in IoT

Although study on outlier detection techniques has long been an area of much research, few of those works relate to an Internet of Things (IoT) environment. In the last few years, with the advent of IoT and its numerous smart objects, data generated from sensors have increased exponentially. Since on the basis of these data many critical decisions are taken, it is therefore necessary to absolutely ensure its accuracy, correctness and integrity before any processing starts. Most algorithms in the past assumes outliers to be always an Error, that is caused by a malfunctioning sensor. However, this is not always true because an outlier could also be an important event that should not be neglected. This stresses the need to devise algorithms that is suited for an IoT environment which considers both Error, that is a result of faulty sensors or an Event, which is an indication of an abnormal phenomenon. This paper proposes a sequence based learning approach for outlier detection that works for both Error and Event. Simulations are performed on few benchmark datasets, a medical dataset and a real world dataset obtained through an experimental test bed. The results reveal exceptionally high accuracies with up to 99.65% for Error detection and 98.53% for Event detection.

MQRP: Mobile sinks-based QoS-aware data gathering protocol for wireless sensor networks-based smart grid applications in the context of industry 4.0-based on internet of things

The recent advances in internet of things (IoT) and industrial wireless sensor networks (IWSNs) paradigm provide a promising opportunity for upgrading today’s elderly electricity industrial systems and even allow the fourth stage of the industrial revolution, referred to as smart grid industry (SGI) 4.0. In SGI 4.0 paradigm, the WSNs are considered as promising solutions due to their advantages, such as cable replacement, ease of deployment, flexibility, and cost reduction. However, harsh and complex smart grid (SG) environments pose great challenges to guarantee reliable communication for WSNs-based SG applications due to equipment noise, electromagnetic interference, multipath effects and fading in SG environments. This results in deteriorating the quality-of-service (QoS) requirements as well as the network lifetime of multi-hop communication-based WSNs for SG applications. Thus, for SGI 4.0 paradigm to come true, a WSN-based highly reliable communication infrastructure is crucial that will wirelessly connect and integrate power system components for more efficient, reliable, and intelligent operations of the next-generation electricity power grids. To address these challenges, in this paper a novel multi-mobile sinks-based QoS-aware data gathering protocol (called MQRP) for WSNs-based SG applications has been proposed to empower SGI 4.0. The extensive simulations study is carried through a network simulation tool called EstiNet9.0. The obtained experimental facts show that the proposed scheme has not only improved the QoS performance metrics, such as packet delivery ratio, memory utilization, control message overhead, residual energy, network lifetime, and throughput, but also reduced packet error rate and end-to-end delay compared to existing data collection schemes.

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems.

Intrusion Detection in PLC-Based Industrial Control Systems Using Formal Verification Approach in Conjunction with Graphs

Vulnerability in industrial control systems (ICS) has increased radically in the past few decades. This can be accounted to reasons including accessibility of ICS through Internet, development of sophisticated attack methods, and advancement in Internet of Things (IoT). The damage that can be caused by attackers on insecure ICS could cost hundreds of human lives and a huge state economy. Therefore, having such systems every where around us makes the concern for security nothing but a priority. Programmable logic controllers (PLCs) are the central devices of ICS and also a target to attacks which aim at gaining access and privilege to the control logic of the controller. A successful alteration or intrusion of the control logic by attackers can have a catastrophic effect on the plant. In this paper, control logic intrusion detection methodology for PLC-based control systems is proposed. The methodology implements the detection process by comparing a potentially intruded PLC program with a trusted version of the program. In order to achieve this goal, a scheme is proposed that operates in sequence of stages by first translating the PLC program to formal models (based on previous research work), then translating the formal models to graphs followed by performing a comparison between a trusted system model graph and a potentially intruded system graph. In the last stage of the methodology, graph discrepancy analysis is made in order to identify any intrusions. For demonstration purposes, a water level control system is presented as a case study, which is modeled using UPPAAL toolbox. We have verified our methodology by developing an in-house software. Our test results prove the concept that intrusions can be shown as discrepancies in the graphs generated from the UPPAAL-based formal modeling, which can be detected utilizing the proposed graph comparison approach. The premise of our study is that logic intrusions in PLC based ICS can be identified by the changes in the PLC code, and the methodology we proposed can successfully detect those changes by observing the code’s graph model.

A Design Space for Virtuality-Introduced Internet of Things

Augmented reality (AR) and virtual reality (VR) technologies have been dramatically expanded in recent years. In the near future, we expect that diverse digital services that employ Internet of Things (IoT) technologies enhanced with AR and VR will become more popular. Advanced information technologies will enable the physical world to be fused with the virtual world. These digital services will be advanced via virtuality, which means that things that do not physically exist make people believe in their existence. We propose a design space for digital services that are enhanced via virtuality based on insights extracted from three case studies that we have developed and from discussions in focus groups that analyze how existing commercial IoT products proposed in a commercial crowdfunding platform, Kickstarter, could be enhanced through virtuality. The derived design space offers three dimensions to design a digital service to fuse IoT technologies with virtuality: (1) Taxonomy of IoT; (2) Visualizing Level, and (3) Virtuality Level. The design space will help IoT-based digital service designers to develop advanced future IoT products that incorporate virtuality.

Energy efficient and QoS-aware routing protocol for wireless sensor network-based smart grid applications in the context of industry 4.0

Recently, there have been great advances in internet of things (IoT) and wireless sensor networks (WSNs) leading to the fourth industrial revolution in power grid, namely, Smart Grid Industry 4.0 (SGI 4.0). In the Smart Grid Industry 4.0 framework, the WSNs have the potential to improve power grid efficiency by cable replacement, deployment flexibility, and cost reduction. However, the smart grid (SG) environment that the WSNs operate in is very challenging because of equipment noise, dust, heat, electromagnetic interference, multipath effects and fading, which make it difficult for current WSNs to provide reliable communication. For SGI 4.0 to come true, a WSN-based highly reliable communication infrastructure is essential for successful operation of the next-generation electricity power grids. To address this need, in this paper a novel dynamic clustering based energy efficient and quality-of-service (QoS)-aware routing protocol (called EQRP), which is inspired by the real behavior of the bird mating optimization (BMO), has been proposed. The proposed distributed scheme improves network reliability significantly and reduces excessive packets retransmissions for WSN-based SG applications. Performance results show that the proposed protocol has successfully reduced the end-to-end delay and has improved packet delivery ratio, memory utilization, residual energy, and throughput.

Interoperable agro-meteorological observation and analysis platform for precision agriculture: A case study in citrus crop water requirement estimation

Advances in Internet of Things (IoT) based sensing systems have improved capabilities to precisely monitor environmental conditions. Plants are sessile organisms and are affected by biotic and abiotic stresses caused due to surrounding environmental conditions such as soil water content, pest/disease infestation, and soil health. High-resolution sensing (Wireless Sensor Networks (WSN) Systems) of agro-meteorological parameters helps to solve critical issues about the crop-weather-soil continuum. Currently, many WSN systems are deployed all over the World for precision agriculture purposes. Although there have been many improvements in the communication aspects of the WSN's, the data dissemination and near real-time analysis components for taking dynamic decision, particularly in agriculture domain has not matured. The current WSN systems do not have a standardized way of data discovery, access, and sharing, which impedes the integration of data across various distributed sensor networks. This study addresses above issues through the adaptation of a framework based on Open Geospatial Consortium (OGC) standards for Sensor Web Enablement (SWE). For precision agriculture applications a cost-effective, standardized sensing system (hardware and software) has been developed, which includes functionalities such as sensors plug-n-play, remote monitoring, tools for crop water requirement estimation, pest, disease monitoring, and nutrient management. Also, the modeling techniques were integrated with the interoperable web-enabled sensing system for addressing water management problems of horticultural crops in semi-arid areas.

Leveraging heterogeneous device connectivity in a converged 5G-IoT ecosystem

As mobile communications technology is completing its fifth-generation (5G) cycle, it becomes increasingly capable of supporting novel usage scenarios with stringent performance requirements. Beyond seamless broadband connectivity for humans, 5G systems are preparing to enable a wide range of machine-type applications, thus advancing the vision of the Internet of Things (IoT). Facilitated by the rapidly converging 5G-IoT ecosystem, next-generation industrial IoT services, however, pose unprecedented research problems, primarily along the lines of providing wireless connectivity with ubiquitous availability, extreme reliability, and ultra-low latency. To this end, the first part of this paper11The work of O. Galinina was supported in part with a personal research grant by the Finnish Cultural Foundation and in part by a Jorma Ollila grant from Nokia Foundation. The work of S. Andreev was supported in part by a Postdoctoral Researcher grant from the Academy of Finland and in part by a Jorma Ollila grant from Nokia Foundation. presents a concise update on the novel requirements and challenges in the context of the emerging Industrial Internet infrastructure. In the second part, we introduce and solve a new optimization problem formulation aimed at improving performance reliability for advanced IoT devices equipped with several radio access technologies. We argue that by intelligently leveraging such heterogeneous multi-connectivity, future 5G-grade IoT applications will be able to improve their levels of operational reliability. Our conclusions are corroborated by rigorous mathematical derivations as well as several realistic numerical examples.

Industrial Internet of Things monitoring solution for advanced predictive maintenance applications

Abstract Internet of Things (IoT) solutions in industrial environments can lead nowadays to the development of innovative and efficient systems aiming at increasing operational efficiency in a new generation of smart factories. In this direction the article presents in detail an advanced Industrial IoT (IIoT) solution, the NGS-PlantOne system, specially designed to enable a pervasive monitoring of industrial machinery through battery-powered IoT sensing devices, thus allowing the development of advanced predictive maintenance applications in the considered scenario. To the end of evaluating the performance of the developed IIoT system in a real environment, the NGS-PlantOne solution has been first installed and then set in operation in a real electricity power plant. The deployed testbed, based on 33 IoT sensing devices performing advanced temperature and vibration monitoring tasks, has been kept in operation for two months while evaluating transmission delays and system operating life through power consumption measures. Performance results show as the developed IIoT solution benefits from all the advantages provided by the adopted IoT protocols, guaranteeing that each node is reachable through simple IP-based techniques with an acceptable delay, and showing an estimated average life of 1 year in case of each IoT smart device is configured to send collected and elaborated data every 30 min.

Secure IoT Devices for the Maintenance of Machine Tools

Through the Internet of Things (IoT) interaction between objects becomes possible in a way we have never seen before. With the advent of IoT and its introduction into almost all aspects of life, safety and security of IoT devices has to be considered for their whole life cycle. This concerns not only the large amounts of data that needs to be exchanged securely but also the design of the hardware of the devices themselves. Security has to be designed right from the start into IoT devices rather than added on later.This paper will introduce a global strategy for secure Design for IoT which includes:•Safe solutions for environments with rich information•Guarantee that the devices are functioning as intended by the manufacturer and are not damaged•Life cycle security across devices, networks and data centers•Support for industry standards and interoperability of devices•Ability to solve the challenges of the information link•Secure Clouds for traditional systems.This paper lays the foundation for the creation of a safe remote monitoring system for machine tools through IoT devices and analyses the critical issues focusing on the manufacturing environment.

A privacy preserving biometric-based three-factor remote user authenticated key agreement scheme

Advancement in Internet of Things (IOT) and remote user communication is facilitated, where a user need not be physically present. However, security and privacy challenges arrive as client–server communication is done via public network. To lower down the security and privacy threats, authentication and key agreement (AKA) protocols are being designed and analyzed. AKA protocols' goal is to ensure authorized and secure access of recourses. Recently, Li et al. proposed a biometric based three-factor remote user authentication scheme for client–server environment. Their scheme uses biometric identifier to resist guessing attacks. In this article, we discussed the security of Li et al.'s scheme, and show its vulnerability to known session specific temporary information attack. Additionally, it does not provide three-factor authentication and user's privacy. It also has some flows in authentication phase. We proposed a novel AKA protocol, which can overcome the weaknesses of Li et al.'s scheme without losing its original merits. Through the analysis, we show that our scheme is secure against various known attacks including the attacks found in Li et al.'s scheme. Furthermore, we demonstrate the validity of the proposed scheme using the BAN (Burrows, Abadi, and Needham) logic. Our scheme is also comparable in terms of computation overheads with Li et al.'s scheme and other related schemes.

Multi-layer cloud architectural model and ontology-based security service framework for IoT-based smart homes

The Smart Home concept, associated with the pervasiveness of network coverage and embedded computing technologies is assuming an ever-growing significance for people living in the highly developed areas. However, the heterogeneity of devices, services, communication protocols, standards and data formats involved in most of the available solutions developed by different vendors, is adversely affecting its widespread application. In this paper, promoted by several promising opportunities provided by the advances in Internet of Things (IoT) and Cloud Computing technologies for facing these challenges, a novel multi-layer cloud architectural model is developed to enable effective and seamless interactions/interoperations on heterogeneous devices/services provided by different vendors in IoT-based smart home. In addition, to better solve the heterogeneity issues in the presented layered cloud platform, ontology has been used as a promising way to address data representation, knowledge, and application heterogeneity, and an ontology-based security service framework is designed for supporting security and privacy preservation in the process of interactions/interoperations. Challenges and directions for future work on smart home management have been also discussed at the end of this paper.

Guest Editorial

Guest Editorial

Predicting household water use behaviour for improved hygiene practices in internet of things environment via dynamic behaviour intervention model

Recent advances in Internet of Things (IoT) enabled technologies allow the intelligent sensor systems to effectively and efficiently observe and identify human behaviour in many applications, particularly in energy consumption and healthcare sectors. One typical case is that how to use IoT technologies to understand human water use behaviour for improved and sustained hygiene practice. Traditionally, static behaviour intervention models are widely utilised to simulate behaviour intervention process over time. These static methods can predict targeted human behaviour reasonably well, but lack of capabilities on understanding and responding behaviour change process in IoT environments. In this study, the authors proposed a dynamic behaviour intervention model for predicting household water user behaviour for improved hygiene practices. This model is based on an expanded theory of planned behaviour (ETPB), and adopted structure equation model approach and control engineering concept. A case study of household water consumption model using artificial neural network is utilised to evaluate intervention trend of proposed ETPB dynamic behaviour model with system parameter identification. The ETPB dynamic model has been proved to be effective for modelling human behaviour intervention process.

A Trend Analysis Method for IoT Technologies Using Patent Dataset with Goal and Approach Concepts

With the recent tremendous advances in Internet of Things (IoT), analyzing technology trends and providing high quality services also play an important role in analyzing big data. Patent data has been on the rise, and the importance of patents also has been increasing to demand a company's competitiveness and to claim technology rights since patents contain important feature technologies that can be used to analyzing new technology trends and to find competitor companies or technologies. Especially IoT techniques are evolving rapidly and a number of new technologies have emerged. Hence a variety of analysis techniques on inventions patented by specific companies are required. In this paper, a trend analysis method is proposed to extract patterns from patent dataset using ETI relations. The experiment results based on the real patent dataset of IoT domain invented a specific organization show that the characteristics of the organization that have the expansion relations is 98.6 % and the transition relations is 1.4 % among ETI relations. Furthermore, we verify proposed dictionaries are useful for enhancing the accuracy to extract ETI relations from a patent network automatically.

Internet of things capability and alliance

Purpose– The purpose of this paper is to examine the role of capability and alliance arising from the internet of things (IoT), specifically in the relationships between strategic orientations (entrepreneurial and market foci) with product and process innovations. In addition, it investigates the direct relationship between IoT capability and alliance. Improving these relationships assist in ensuring that new knowledge from the IoT can be translated into tangible business innovations that contribute to economic development.Design/methodology/approach– Data from 207 new high-technology IoT ventures in China were obtained after three-wave mailing (i.e. two reminders). Following a rigorous process to purify and validate the measurement scale items, the study used structural equation modeling to test the conceptual model.Findings– Findings demonstrate that an IoT capability only enhances product innovation, however, with the addition and support from IoT alliance, both product and process innovation can be achieved in new high-tech IoT ventures. This nuanced insight suggests that new high-tech IoT ventures should focus on building their IoT capability, and at the same time, develop IoT alliances with value chain partners in order to fully take advantage of IoT and gain a better position to formulate more novel offerings.Originality/value– The study is first to contribute with a much needed framework of IoT and entrepreneurship by examining the role of IoT capability further in the relationships between: entrepreneurial orientation and market orientation with product and process innovations arising from IoT; and the role of IoT alliance (interfirm relations, partnerships, etc.) on the relationship above.

Using Battery-Less RFID Tags with Augmented Capabilities in the Internet of Things

Driven by user demand for new smart systems in the framework of the Internet of Things (IoT) and fueled by technological advances in Radiofrequency Identification (RFID), an increasing number of new IoT-oriented RFID-based devices has appeared in recent years in scientific literature. Some of them conjugate canonical RFID identification with extra functionalities such as sensing, reasoning, memorization, and actuation. In this way, IoT challenging applications can be developed, which distribute processing load till to the extreme nodes of the network, while lying upon the well-established RFID infrastructure. In this work, a reasoned panoramic on the potentialities in the IoT framework of augmented RFID tags is presented and classified. Two applicative scenarios are envisioned, presented and discussed, to illustrate how augmented RFID devices may support advanced IoT systems.

Design of Chemical Industrial Park Integrated Information Management Platform Based on Cloud Computing and IOT (The Internet of Things) Technologies

Chemical industry is the fundamental strategic industry in national economy and one of pillar industries in China. A wealth of chemical industrial parks has been built one after another in many places, where lots of chemical enterprises are established. In the normal operation of those enterprises, their raw materials or products manufactured, transported and stored are usually featured by flammable, explosive or toxic properties, resulting in frequent occurrence of pollution and personal accidents and causing great threats to surrounding environment. This thesis realizes an integrated information management platform based on currently advanced cloud computing and IOT (The Internet of Things) technologies, so as for integrated management of chemical industrial parks. This thesis designs the architectural structure of said integrated information management platform, expounds the roles and realization approaches of the basic support platform and the business service platform, analyzes the principles and methods for realization of regionally coordinate emergency management operation mechanism based on the information management platform, that of IOT architecture technology and that of RFID and Wireless Sensor Network (WSN), and discusses that the standard unification of heterogeneous data under cloud computing is realized by means of multisource data integration middleware. The said platform can accomplish the wholeprocess, real-time and dynamic follow-up and control of chemicals and hazardous materials and also provide effective service for users’ decision-making by mining and analyzing tremendous data of a chemical industrial park with Agent-middleware technology. The information management platform is capable of assessing the safety factors of chemical enterprises at peacetime, giving necessary warning before accidents and offering effective technical support for rescue via expert system, emergency plan system, monitoring system and positioning system. The realization of chemical industrial park integrated information management platform based on cloud computing and IOT technologies will greatly improve the management level of chemical industrial parks, intensify surveillance, achieve information resource sharing and lower the probability of accident occurrence.

Advances in internet of things and cyber physical systems and its application to smart ship

Advances in internet of things and cyber physical systems and its application to smart ship