Data management techniques for Internet of Things Diène, Bassirou; Rodrigues, Joel J.P.C.; Diallo, Ousmane ...
Mechanical systems and signal processing,
April 2020, 2020-04-00, 20200401, Letnik:
138
Journal Article
Recenzirano
•Identification of the most relevant concepts of IoT data management.•Presentation and taxonomy of the current solutions proposed for IoT data management.•Study of IoT applications with generated ...data types, Highlighting IoT and IIoT link.•Discussion of the relevant open research challenges in data management for IoT.•Proposal of possible solutions for further contributions in IoT’s data management.
Internet of Things (IoT) is a network paradigm in which physical, digital, and virtual objects are equipped with identification, detection, networking, and processing functions to communicate with each other and with other devices and services on the Internet in order to perform the users’ required tasks. Many IoT applications are provided to bring comfort and facilitate the human life. In addition, the application of IoT technologies in the automotive industry has given rise to the concept of Industrial Internet of Things (IIoT) which facilitated using of Cyber Physic Systems, in which machines and humans interact. Due to the diversity, heterogeneity, and large volume of data generated by these entities, the use of traditional database management systems is not suitable in general. In the design of IoT data management systems, many distinctive principles should be considered. These different principles allowed the proposal of several approaches for IoT data management. Some middleware or architecture-oriented solutions facilitate the integration of generated data. Other available solutions provide efficient storage and indexing structured and unstructured data as well as the support to the NoSQL language. Thus, this paper identifies the most relevant concepts of data management in IoT, surveys the current solutions proposed for IoT data management, discusses the most promising solutions, and identifies relevant open research issues on the topic providing guidelines for further contributions.
A Reference Model for Internet of Things Middleware da Cruz, Mauro A. A.; Rodrigues, Joel José P. C.; Al-Muhtadi, Jalal ...
IEEE internet of things journal,
04/2018, Letnik:
5, Številka:
2
Journal Article
Internet of Things (IoT) is a term used to describe an environment where billions of objects, constrained in terms of resources ("things"), are connected to the Internet, and interacting ...autonomously. With so many objects connected in IoT solutions, the environment in which they are placed becomes smarter. A software, called middleware, plays a key role since it is responsible for most of the intelligence in IoT, integrating data from devices, allowing them to communicate, and make decisions based on collected data. Then, considering requirements of IoT platforms, a reference architecture model for IoT middleware is analyzed, detailing the best operation approaches of each proposed module, as well as proposes basic security features for this type of software. This paper elaborates on a systematic review of the related literature, exploring the differences between the current Internet and IoT-based systems, presenting a deep discussion of the challenges and future perspectives on IoT middleware. Finally, it highlights the difficulties for achieving and enforcing a universal standard. Thus, it is concluded that middleware plays a crucial role in IoT solutions and the proposed architectural approach can be used as a reference model for IoT middleware.
For the purpose of usability feature extraction and prediction, an innovative metaheuristic algorithm is introduced. Generally, the term “usability” is defined by the several researchers with respect ...to the hierarchical-based software usability model and it has become one of the important methods in terms of software quality. In hierarchically based software, its usability factors, attributes, and its characteristics are combined. The paper presented an algorithm, i.e., modified crow search algorithm (MCSA) mainly for extraction of usability features from hierarchical model with the optimal solution under the search for useful features. MCSA is an extension of original crow search algorithm (CSA), which is a naturally inspired algorithm. The mechanism of this algorithm is based on the process of hiding food and prevents theft and hence introduced this CSA in the field of software engineering practices as an inspiration. The algorithm generates a particular number of selected features/attributes and is applied on software development life cycles models, finding out the best among them. The results of the presented algorithm are compared with the standard binary bat algorithm (BBA), original CSA, and modified whale optimization algorithm (MWOA). The outcomes conclude that the proposed MCSA performs well than the standard BBA and original CSA as the proposed algorithms generate fewer number of feature selection equal to 17 than 18 in BBA, 23 in CSA, and 19 in MWOA.
The emergence of the Internet of Things (IoT) and its applications has taken the attention of several researchers. In an effort to provide interoperability and IPv6 support for the IoT devices, the ...Internet Engineering Task Force (IETF) proposed the 6LoWPAN stack. However, the particularities and hardware limitations of networks associated with IoT devices lead to several challenges, mainly for routing protocols. On its stack proposal, IETF standardizes the RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) as the routing protocol for Low-power and Lossy Networks (LLNs). RPL is a tree-based proactive routing protocol that creates acyclic graphs among the nodes to allow data exchange. Although widely considered and used by current applications, different recent studies have shown its limitations and drawbacks. Among these, it is possible to highlight the weak support of mobility and P2P traffic, restrictions for multicast transmissions, and lousy adaption for dynamic throughput. Motivated by the presented issues, several new solutions have emerged during recent years. The approaches range from the consideration of different routing metrics to an entirely new solution inspired by other routing protocols. In this context, this work aims to present an extensive survey study about routing solutions for IoT/LLN, not limited to RPL enhancements. In the course of the paper, the routing requirements of LLNs, the initial protocols, and the most recent approaches are presented. The IoT routing enhancements are divided according to its main objectives and then studied individually to point out its most important strengths and weaknesses. Furthermore, as the main contribution, this study presents a comprehensive discussion about the considered approaches, identifying the still remaining open issues and suggesting future directions to be recognized by new proposals.
Nowadays research is heading towards the integration of cloud computing and Internet of Things thus creating a Cloud of Things (CoT). This combination generates a new paradigm for pervasive and ...ubiquitous computing. However, reliable CoT-based services, particularly, highly delay-sensitive services, such as, healthcare, require energy-efficient CoT architectures. Considerable efforts have been proposed to improve the efficiency of CoT architectures. This paper analyses CoT architectures and platforms, as well as the implementation of CoT in the context of smart healthcare. Subsequently, the paper explains some related issues of CoT, including the lack of standardization. Moreover, it focuses on energy efficiency with an in depth analysis of the most relevant proposals available in the literature. An evaluation of all the energy efficiency solutions investigated in this paper shows there is still a need to improve energy efficiency, especially regarding QoS and performance.
The development of non-invasive optoelectronic technologies for human blood monitoring is one of the important research areas for medicine. A critical analysis of optoelectronic methods of blood ...research and the micromechanical systems based on them is carried out in this article. A design realization of a polarizing portable system for non-invasive monitoring of hematocrit as one of the basic homeostatic constants of the human body containing information about the microphysical parameters of blood cells has been substantiated. A physical model of polarized radiation conversion in a video information system of laser sensing of a biological research object has been formed. Visual and quantitative differences in the spatial distribution of polarization parameters of the scattered radiation for the states of the body with different hematocrit levels have been revealed. A scheme of a multichannel imaging portable system, based on a smartphone using miniature optical and microelectronic components of information conversion for non-invasive monitoring of microphysical blood parameters, has been created. The system implements the principle of polarimetric blood photometry and a multiparametric analysis of the polarization properties of the laser radiation scattered by blood. The developed portable optoelectronic system, based on a smartphone, can be used for rapid blood diagnostics in disaster medicine and the presence of clinical contraindications to the formation of invasive tests. The proposed polarization-based approach is a promising automated alternative to traditional devices and systems for the research of microphysical blood parameters.
Omnidirectional optoelectronic systems (OOES) find applications in many areas where a wide viewing angle is crucial. The disadvantage of these systems is the large distortion of the images, which ...makes it difficult to make wide use of them. The purpose of this study is the development an algorithm for the precision calibration of an omnidirectional camera using a statistical approach. The calibration approach comprises three basic stages. The first stage is the formation of a cloud of points characterizing the view field of the virtual perspective camera. In the second stage, a calibration procedure that provides the projection function for the camera calibration is performed. The projection functions of traditional perspective lenses and omnidirectional wide-angle fisheye lenses with a viewing angle of no less than 180° are compared. The construction of the corrected image is performed in the third stage. The developed algorithm makes it possible to obtain an image for part of the field of view of an OOES by correcting the distortion from the original omnidirectional image.Using the developed algorithm, a non-mechanical pivoting camera based on an omnidirectional camera is implemented. The achieved mean squared error of the reproducing points from the original omnidirectional image onto the image with corrected distortion is less than the size of a very few pixels.
Wireless Sensor Networks (WSNs) have gained great significance from researchers and industry due to their wide applications. Energy and resource conservation challenges are facing the WSNs. ...Nevertheless, clustering techniques offer many solutions to address the WSN issues, such as energy efficiency, service redundancy, routing delay, scalability, and making WSNs more efficient. Unfortunately, the WSNs are still immature, and suffering in several aspects. This paper aims to solve some of the downsides in existing routing protocols for WSNs; a Lightweight and Efficient Dynamic Cluster Head Election routing protocol (LEDCHE-WSN) is proposed. The proposed routing algorithm comprises two integrated methods, electing the optimum cluster head, and organizing the re-clustering process dynamically. Furthermore, the proposed protocol improves on others present in the literature by combining the random and periodic electing method in the same round, and the random method starts first at the beginning of each round/cycle. Moreover, both random and periodic electing methods are preceded by checking the remaining power to skip the dead nodes and continue in the same way periodically with the rest of the nodes in the round. Additionally, the proposed protocol is distinguished by deleting dead nodes from the network topology list during the re-clustering process to address the black holes and routing delay problems. Finally, the proposed algorithm’s mathematical modeling and analysis are introduced. The experimental results reveal the proposed protocol outperforms the LEACH protocol by approximately 32% and the FBCFP protocol by 8%, in terms of power consumption and network lifetime. In terms of Mean Package Delay, LEDCHE-WSN improves the LEACH protocol by 42% and the FBCFP protocol by 15%, and regarding Loss Ratio, it improves the LEACH protocol by approximately 46% and FBCFP protocol by 25%.
The increasing use of interconnected sensors to monitor patients with chronic diseases, integrated with tools for the management of shared information, can guarantee a better performance of health ...information systems (HISs) by performing personalized healthcare. The early diagnosis of chronic diseases such as hypertensive disorders of pregnancy represents a significant challenge in women’s healthcare. Computational learning techniques are useful tools for pattern recognition in the assessment of an increasing amount of integrated data related to these diseases. Hence, in this paper, the use of machine learning (ML) techniques is proposed for the assessment of real data referred to hypertensive disorders in pregnancy. The results show that the averaged one-dependence estimator algorithm can help in the decision- making process in uncertain moments, thus improving the early detection of these chronic diseases. The best-evaluated computational learning algorithm improves the performance of HISs through its precise diagnosis. This method can be applied in electronic health (e-health) environments as a useful tool for handling uncertainty in the decision-making process related to high-risk pregnancy.
Summary
The exchange of information among health professionals is a common practice among clinics, laboratories, and hospitals. Cloud‐based clinical data exchange platforms enable valuable ...information to be available in real time and in a secure and private manner. The increasing availability of data in health information systems allows specialists to extract knowledge using pattern recognition techniques for the identification and prediction of risk situations that could lead to severe complications for a patient. Hence, this paper proposes the use of a neuro‐fuzzy machine learning technique for predicting the most complex hypertensive disorder in pregnancy called HELLP syndrome. This classifier serves as an inference mechanism for cloud‐based mobile applications, for effective monitoring through the analysis of symptoms presented by pregnant women. Results show that the proposed model achieves excellent results regarding several indicators, such as precision (0.685), recall (0.756), the F‐measure (0.705), and the area under the receiver operating characteristic curve (0.829). This technique can accurately predict situations that could lead to the death of both a mother and fetus, at any location and time.
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