Smart Era Research Articles

Codoping of Lead‐Free Double Perovskites Promotes Near‐Infrared Photoluminescence

AbstractIn the rapidly developing smart era, near‐infrared luminescent materials have important applications in various fields that are closely related to people. Nag and co‐workers provided a first codoping strategy to achieve efficient near‐infrared photoluminescence in lead‐free double perovskite materials. Through the introduction of Bi3+ ions, a new energy state is formed that leads to the absorption of lower‐energy light. The excited state formed by this light absorption subsequently excites f‐electrons of Er3+ or Yb3+ ions, and the relaxation of these f‐electrons results in near‐infrared photoluminescence. This may open a new chapter in the application of perovskites for infrared detection and human sensing.

Content Based Image Retrieval from Auto Encoders Using Keras and Tensor Flow Python API a Deep Learning Technique

As the technology is evolving new methods and techniques are determined and implemented in a smart way to improve and achieve a greater insight in this smart era. The retrieval of image is popularly growing in this emerging trend. In this paper we have used how to build a very simple image retrieval system using a special type of Neural Network called auto encoders. Here the images can be retrieved with visual contents textures, shape and this method of image retrieval is called content based image retrieval.

IoEV-Chain: A 5G-Based Secure Inter-Connected Mobility Framework for the Internet of Electric Vehicles

Recent advances in 5G-based disruptive technologies have ushered in a new smart era of interconnected mobility. Hence, smart city planners around the globe are facing the challenges of leveraging these new modalities of future mobility solutions. Some key innovations toward disruptive mobility are the next generation of the Internet of electric vehicles and ultra-high-speed 5G communication paradigms. However, adding security to IoEV data remains of great concern. In this study, we offer a novel secure blockchain and off-chainbased 5G mobility framework that enables the security of IoEV data at rest, in transmission, and in the storage medium. We address the 5G security vulnerabilities in the areas of mutual authentication and authorization, remote software updates, confidentiality and integrity protection, secure provisioning of 5G services, secure storage of IoEV and personal data, and location tracking. We present our experience in building the architecture and the implementation of the framework, in addition to the system evaluation results.

Smart Heritage: Media for Realizing Cultural Heritage Conservation in The Smart City Era

Smart Heritage is a relatively new system and management media that initiated by INTACH Heritage Academy (2007) to answer the challenge that addresses the Cultural Heritage Conservation in the Smart City Era by using the advancement of Information Communication Technology (ICT). It has begun to be applied in a city that has implemented the concept of Smart City. This paper discusses whether Smart Heritage is relevant to the issue about sustainable cultural heritage within the scope of Smart City development along with the growth of a millennial generation, because that we are going towards to the Smart era that almost everything is ICT oriented.

HEALTH Growth with Active Transformation of Mind and Body Through Abundant Natural Methods

The ongoing technological developments have totally transformed the lives of human beings. With the emergence of the smart era and the smart city concept, a few smart gadgets like phones, earplugs, and laptops have become an extended part of the human body. The natural body, that has taken the present form as a result of millions of years of evolution, is trying hard to adapt to these artificial extensions. The constant burden of these superficial parts is taking a toll on the body and has resulted in various Physical, Psychological and Psychosomatic (P3) disease. A number of P3 disease like depression, hypertension, insomnia, diabetes, cardiac arrests and cancer are set in very early in the life of human beings. With the rapid growth of technology, it has become imperative to find methods for a parallel growth of the human mind and body to be able to be the smart human beings of the smart era. In this paper, we present a novel method, called Active transformation of Mind and body through Abundant Natural Methods (ATMAN). Alongside, the growth of the human body in terms of Harmony, Energy, Aesthetics, Limberness, Tranquility and Happiness (HEALTH) has been elucidated. A relationship has been established between ATMAN and HEALTH.

Investigations on System Modeling Simulations for Solving Heterogeneous WSN Task Assignment Problem using Multilayer Feed Forward Neural Networks

In the modern smart era, various real-time applications are achieved through Heterogeneous Wireless Sensor Networks (HeWSN) comprising a set of multi-functional wireless sensor nodes. In comparison to legacy nodes, the contemporary nodes are smaller and faster with multi-sensing capabilities. The real-time application missions are achieved by effectively assigning tasks to the ideal nodes in the HeWSN by employing a task assignment algorithm. Though various WSN tasks assignment algorithms have been proposed from time to time, it requires maximal human intervention to achieve the application missions. To mitigate human intervention, the task assignment in WSN could be powered by machine learning techniques. Despite the technological advancements, WSN is still assumed to be resource-constrained and employing a powerful machine learning technique may not be ideal. Investigations of the existing machine learning techniques catering to the needs of the WSN have been carried out and have led to the selection of Multilayer Feed Forward Network (MLFFN). Further, a HeWSN application is modelled and simulated to train the system. A total of 39,000 individual experimentations was performed by varying the hidden layers and training sets. Performance analysis was performed on the successful task assignment ratio. Investigations performed are (i) finding the highest successful task assignment ratio, (ii) configuration of the hidden layer and training set ranges in which the maximum successful task assignment ratio is obtained. In a nutshell, in-depth discussions to adapt MLFFN in a HeWSN application has been presented along with the future scope of the work

Towards the “Homo Deus” excellence perspective?

PurposeThe evolution of management underlines the importance of the human, systemic, technological and contingency element and their interaction along with an amplified awareness of organizations for achieving excellence. This paper aims to discuss whether the fusion of digital, biological and physical world leads to a new excellence perspective and to investigate the potential value of informative neuroscientific findings for setting the foundations for smart services.Design/methodology/approachThis study is based on a literature review regarding the advances of neurosciences and its implications for business. Their usefulness and potential contribution for the provision of smart services are investigated.FindingsThe fusion of technological evolution and biological sciences may potentially give birth to a new excellence conceptualization complemented by genetic data whose consequences are hard to predict. Neurosciences offer insights for various human behavior areas that can be used by business practitioners, to refine their thinking and management style and build brain-friendly organizational contexts. The combination of using neuroscientific evidence and technology in service systems sets the foundations for an “intelligent” provision of services in a quality context.Originality/valueThe paper investigates the conceptual development of excellence within the receding context of the “smart era” and the potential contribution of neurosciences for the provision of smart services with reference to quality pioneers’ theories and ideas.

스마트 환경에서의 협력과 SCM 성과: O2O 스타트업을 중심으로

O2O service is getting more attention in the business environment of the smart era that started from the 4th industrial revolution. O2O service has been actively operated recently with the participation of many startup companies. Also, SCM has been widely introduced in O2O service industry. In this study, we conducted an empirical analysis on the effect of collaborative methods and the collaborative SCM between O2O startups and suppliers on SCM performance. A frequency analysis, exploratory factor analysis, reliability analysis, confirmatory factor analysis, and correlation analysis were conducted for validity and reliability of our model. The research hypotheses were verified through model fit analysis and the structural causality of the research concept was examined through the path analysis of the structural equation. We found that collaborative methods had no significant effect on collaborative SCM, however collaborative methods and collaborative SCM had a significant influence on SCM performance.

Visual Information Retrieval for Videos Based on Feature Extraction using Machine Learning Techniques

Information retrieval is one of the important areas of research with highest scope for data mining combined with machine learning. The proposed research focus on visual information retrieval by applying machine learning techniques. The usage of multimedia data such as text, images, videos are abundantly increasing day by day in this smart era. Also the need for information classification and retrieval are getting exponential demands to fulfill the research and end user requirements. The tech giants are conducting their researches to develop efficient retrieval systems for videos. Video retrieval is considered to be the toughest and challenging research in the recent times. Due to large storage space, lengthy play time, multiple sequence of frames, spatial temporal challenges, lack of visual relevancy, less hardware and processing support. The proposed visual information retrieval has got higher scope of research with the above listed problems.

Smart City System Design

Recent global smart city efforts resemble the establishment of electricity networks when electricity was first invented, which meant the start of a new era to sell electricity as a utility. A century later, in the smart era, the network to deliver services goes far beyond a single entity like electricity. Supplemented by a well-established Internet infrastructure that can run an endless number of applications, abundant processing and storage capabilities of clouds, resilient edge computing, and sophisticated data analysis like machine learning and deep learning, an already-booming Internet of Things movement makes this new era far more exciting. In this article, we present a multi-faceted survey of machine intelligence in modern implementations. We partition smart city infrastructure into application, sensing, communication, security, and data planes and put an emphasis on the data plane as the mainstay of computing and data storage. We investigate (i) a centralized and distributed implementation of data plane’s physical infrastructure and (ii) a complementary application of data analytics, machine learning, deep learning, and data visualization to implement robust machine intelligence in a smart city software core. We finalize our article with pointers to open issues and challenges.

Contracting in the Smart Era: The Implications of Blockchain and Decentralized Autonomous Organizations for Contracting and Corporate Governance

This paper explores blockchain technology’s potential to alter contracting both in the market and within organizations. We identify and discuss how blockchain reduces certain types of transaction c...

SEMIoTICS: Semantically Enhanced IoT-Enabled Intelligent Control Systems

In today’s “smart era” there is a growing ecosystem of Internet of Things (IoT)-enabled devices, which exploit (wireless) Internet connectivity and use standard communication protocols to interact with each other and the environment. As various IoT components are becoming widely available in the marketplace, a key challenge from a feedback control viewpoint is the ability to seamlessly integrate new IoT components or modify existing configurations in feedback control settings without having to halt the operation of the system and redesign the overall feedback control scheme. This paper exploits technologies from the semantic Web domain, for the design of a novel semantically enhanced IoT-enabled intelligent control system (SEMIoTICS) architecture. The proposed SEMIoTICS scheme incorporates a supervisor module able to facilitate the semantic modeling of IoT components and the subsequent online composition/reconfiguration of feedback control loops. We demonstrate the applicability of the SEMIoTICS architecture through illustrative scenarios from the smart buildings domain.

Smart Tourism and Poverty Reduction

Rural poverty has constrained the social and economic development in China. Tourism is a driver for positive change, which plays a significant role in delivering sustainable solutions for people, the planet, prosperity and peace. Smart tourism is a new model of tourism informationization based on cloud computing, the mobile terminal application as the core and characterized by interactive and other efficient information services. Smart rural tourism poverty reduction is one of the most effective ways to achieve targeted poverty reduction. With the increasing integration of “Internet + tourism”, tourism has entered smart era. This study tries to analyze the application of the smart tourism, and examines the benefits to targeted poverty reduction in China. The main methodology is case study based on the operation of “Smart tourism supporting poverty reduction platform in Chengdu.” The findings as follows: smart tourism effectively solve the problems such as backward infrastructure, serious homogenization, extensive operation, lack of service concept and lack of brand concept in rural tourism development; build smart rural tourism data center and application platform to provide intelligent management system to farmers; rural tourism system as the foundation, improve the intelligent management, marketing and service of rural tourism, and promote the sustainable development. Results may be useful for government institutions, NGOs and companies as well. This study has the referential value in the targeted poverty reduction process in China, through the analyse of the latest smart tourism platform can find the current advantages and defects and make up for flaw timely. Last but no least, in order to better reduce poverty and implement smart tourism, some recommendations to the government such as continuously implementing digital transformation, government as a lead organization to coordinate all players to share tasks together, introducing explicit policies enables consistent execution of government at all levels.

Destination-aware context-based routing protocol with hybrid soft computing cluster algorithm for VANET

Due to the rapid topology change, frequent link failure, high vehicle mobility and hard delay constraints, the vehicular ad hoc network (VANET) became a hot research topic in this smart era. VANET has vast application areas including road congestion notification, parking, traffic management, smart transportation, road-side business advertisements. In all these applications, the messages should reach the target location within certain time limits. So, there must be efficient soft computing-enabled routing in VANET which meets these delay constraints. Two soft computing algorithms were proposed in this paper: First, a hybrid clustering algorithm is proposed which combines the geographic- and context-based clustering approaches. The hybrid clustering reduces the control overhead and traffic in the network. Second, the destination-aware routing protocol is proposed for inter-clustering routing which improves the overall packet delivery ratio and reduces the end-to-end delay. The performance of the proposed approach is compared with the well-known cluster-based approaches. The result shows that the proposed approach outperforms the existing approaches.

Priority Neuron: A Resource-Aware Neural Network for Cyber-Physical Systems

Advances in sensing, computation, storage and actuation technologies have entered cyber-physical systems (CPSs) into the smart era where complex control applications requiring high performance are supported. Neural networks (NNs) models are proposed as a predictive model to be used in model predictive control (MPC) applications. However, the ability to efficiently exploit resource hungry NNs in embedded resource-bound settings is a major challenge. In this paper, we propose priority neuron network (PNN), a resource-aware NNs model that can be reconfigured into smaller subnetworks at runtime. This approach enables a tradeoff between the model's computation time and accuracy based on available resources. The PNN model is memory efficient since it stores only one set of parameters to account for various subnetwork sizes. We propose a training algorithm that applies regularization techniques to constrain the activation value of neurons and assigns a priority to each one. We consider the neuron's ordinal number as our priority criteria in that the priority of the neuron is inversely proportional to its ordinal number in the layer. This imposes a relatively sorted order on the activation values. We conduct experiments to employ our PNN as the predictive model of a vehicle in MPC for path tracking. To corroborate the effectiveness of our proposed methodology, we compare it with two state-of-the-art methods for resource-aware NN design. Compared to state-of-the-art work, our approach can cut down the training time by 87% and reduce the memory storage by 75% while achieving similar accuracy. Moreover, we decrease the computation overhead for the model reduction process that searches for n neurons below a threshold, from O(n) to O(logn).

Financing for renewable energy projects: A decision guide by developmental stages with case studies

In terms of development cycle, renewable energy (RE) projects entail funding supports from the technological innovation stage onwards. Due to uncertainties in resource availability and technical risk, only a limited variety of funding sources are available for startups. As the RE development project passes through this early stage into technical maturity, more funding sources may be attracted to bring it to commercial fruition. When the technology is eventually deployable to mass applications, even more funding venues exist, sometimes enabling exit of the original innovators via transfer of ownership, or fostering asset growth with investor participation in built facilities. Due to the environmental benefits to be harvested, governments have a pivotal role to play in relation to funding, either directly or indirectly at all stages.This research is aimed at identifying the developmental stages of RE projects and studying the inter-relationships with stakeholders, under the influence of technology push and market pull. Discussions are focused on different types of RE projects and modes of financing, culminating in a diagrammatic model depicting the various decision factors to assist funding-raising activities at different RE developmental stages. Illustrations are provided through a series of carefully selected case studies in western countries. This is followed by a discussion on RE development financing in the Asian context, with conclusions drawn in the light of recent emergence of new business models and a smart era. Decision makers in RE projects may regard this article as a guide for their fund raising activities.

Formation Features of the Customer Segments for the Network Organizations in the Smart Era

Modern network society is based on the advances of information era of Smart, connecting information and communication technologies, intellectual resources and new forms of managing in the global electronic space. It leads to domination of network forms of the organization of economic activity. Many experts prove the importance of segmentation process of consumers when developing competitive strategy of the organization. Every company needs a competent segmentation of the customer base, allowing to concentrate the attention on satisfaction of requirements of the most perspective client segments. The network organizations have specific characteristics; therefore, it is important to understand how they can influence on the formation of client profiles. It causes the necessity of the network organizations’ research in terms of management of high-profitable client segments. The aim of this study is to determine the characteristics of the market segmentation and to choose the key customers for the network organizations. This purpose has defined the statement and the solution of the following tasks: to explore characteristic features of the network forms of the organization of economic activity of the companies, their prospects, Smart technologies’ influence on them; to reveal the work importance with different client profiles; to explore the existing methods and tools of formation of key customer segments; to define criteria for selection of key groups; to reveal the characteristics of customer segments’ formation for the network organizations. In the research process, methods of the system analysis, a method of analogies, methods of generalizations, a method of the expert evaluations, methods of classification and clustering were applied. This paper explores the characteristics and principles of functioning of network organizations, the appearance of which is directly linked with the development of Smart society. It shows the influence on the Smart technologies in the development of the network economy and in the emergence of network forms of organization of economic activity. The review of the methods and modern tools of segmentation of customer base is given. The article offers the author’s interpretations of the peculiar features of client segments’ formation, specific to the network organizations.

Big data projects: just jump right in!

PurposeThis paper aims to provide a roadmap for organizations to build big data projects and reap the most rewards out of their data. It covers all aspects of big data project implementation, from data collection to final project evaluation.Design/methodology/approachIn each stage of the proposed roadmap, we introduce different sets of information and communications technology platforms and tools to assist IT professionals and managers in gaining a comprehensive understanding of the methods and technologies involved and in making the best use of them. The authors also complete the picture by illustrating the process through different real-world big data projects implementations.FindingsBy adopting the proposed roadmap, companies and organizations willing to establish an effective and rewarding big data solution can tackle all implementation challenges in each stage of their big data project setup: from strategy elaboration to final project evaluation. Their expectations of privacy and security are also baked, in advance, into the big data project design.Originality/valueWhile technologies to build and run big data projects have started to mature and proliferate over the last couple of years, exploiting all potentials of big data is still at a relatively early stage. The value of this paper consists in providing a clear and systematic methodology to move businesses and organizations from an opinion-operated era where humans’ skills are a necessity to a data-driven and smart era where big data analytics plays a major role in discovering unexpected insights in the oceans of data routinely generated or collected.

The smart era of electrochemical energy storage devices

The smart era of electrochemical energy storage devices

핵심 기술 및 특허 추출을 위한 IP 마이닝에 관한 연구

최근 사회는 아날로그 시대를 거쳐 디지털, 스마트 시대로 접어들었고, 모든 분야의 기술은 끊임없는 변화와 매우 빠른 발전을 하고 있다. 이러한 경쟁사회에서 지식재산, 특히 특허분석을 통한 R&D 전략 수립은 기술경쟁력 향상에 많은 도움이 될 수 있다. 특허문서는 명칭, 요약, 상세한 설명, 청구항, 기술분류정보 등 서지정보, 기술문헌과 권리문헌으로 이루어져 있어 대중은 이를 통해 해당 기술에 대한 많은 정보를 수집할 수 있다. 특허문서의 특징을 정량적으로 활용하고 기술 분석을 실시함으로써 분석대상 기술의 동향을 파악하는 것뿐만 아니라, 해당 기술 분야의 핵심기술과 특허를 탐색하여 경쟁력을 향상시키는 것이 가능하다. 본 논문은 특허 데이터에 대한 정량적인 방법을 기반으로 한 핵심 기술과 핵심 특허의 도출 방법을 제안한다. 특허문서에 포함되어 있는 기술분류정보, IPC 코드에 통계분석과 사회네트워크분석을 적용하여 연구개발이 활발한 분야와 중심성이 높은 기술을 탐색한다. 그 후 특허의 인용정보와 패밀리정보 분석을 통해 핵심 기술 분야에서 중요성이 높은 특허를 추출하여, 최종적으로 기술경영 및 특허경영 전략 수립 방법을 제안한다. Society has been developed through analogue, digital, and smart era. Every technology is going through consistent changes and rapid developments. In this competitive society, R&D strategy establishment is significantly useful and helpful for improving technology competitiveness. A patent document includes technical and legal rights information such as title, abstract, description, claim, and patent classification code. From the patent document, a lot of people can understand and collect legal and technical information. This unique feature of patent can be quantitatively applied for technology analysis. This research paper proposes a methodology for extracting core technology and patents based on quantitative methods. Statistical analysis and social network analysis are applied to IPC codes in order to extract core technologies with active R&D and high centralities. Then, core patents are also extracted by analyzing citation and family information.