Smart Communication Research Articles

Examining the Adoption of Sustainable eMobility-Sharing in Smart Communities: Diffusion of Innovation Theory Perspective

The transport sector is undergoing disruption due to trends such as tightening environmental targets, digitalization, and servitization, contributing to low-carbon mobility and offering citizen-oriented services. As a response, various initiatives, such as electric mobility (eMobility), have emerged that promote sustainable road transport and active mobility in the last few years. However, irrespective of the potential of eMobility, there are still few studies that examine individuals’ intention and adoption of eMobility-sharing services in smart communities. Accordingly, this study aims to develop a model grounded on the Diffusion of Innovation (DoI) theory to investigate the factors that impact individuals’ adoption of eMobility-sharing service and how to improve the adoption of eMobility-sharing service. A mixed-mode methodology was employed; quantitative data from survey questionnaires were used to gather data, and Statistical Package for Social Science (SPSS) was used to analyze the data. Additionally, qualitative data via interview was collected to demonstrate in ArchiMate modeling language how eMobility-sharing services are practically implemented as a use case study within smart communities. Findings from this study offer a model that focuses on eMobility-sharing adoption from the perspective of smart communities. Additionally, the findings offer a better understanding of how such integrated, multimodal systems fit with the sustainable mobility needs of citizens. More importantly, general recommendations to policymakers and practitioners to increase the uptake of shared eMobility are provided.

Internet of Things (IoT) in Buildings: A Learning Factory

Advances towards smart ecosystems showcase Internet of Things (IoT) as a transversal strategy to improve energy efficiency in buildings, enhance their comfort and environmental conditions, and increase knowledge about building behavior, its relationships with users and the interconnections among themselves and the environmental and ecological context. EU estimates that 75% of the building stock is inefficient and more than 40 years old. Although many buildings have some type of system for regulating the indoor temperature, only a small subset provides integrated heating, ventilation, and air conditioning (HVAC) systems. Within that subset, only a small percentage includes smart sensors, and only a slight portion of that percentage integrates those sensors into IoT ecosystems. This work pursues two objectives. The first is to understand the built environment as a set of interconnected systems constituting a complex framework in which IoT ecosystems are key enabling technologies for improving energy efficiency and indoor air quality (IAQ) by filling the gap between theoretical simulations and real measurements. The second is to understand IoT ecosystems as cost-effective solutions for acquiring data through connected sensors, analyzing information in real time, and building knowledge to make data-driven decisions. The dataset is publicly available for third-party use to assist the scientific community in its research studies. This paper details the functional scheme of the IoT ecosystem following a three-level methodology for (1) identifying buildings (with regard to their use patterns, thermal variation, geographical orientation, etc.) to analyze their performance; (2) selecting representative spaces (according to their location, orientation, use, size, occupancy, etc.) to monitor their behavior; and (3) deploying and configuring an infrastructure with +200 geolocated wireless sensors in +100 representative spaces, collecting a dataset of +10,000 measurements every hour. The results obtained through real installations with IoT as a learning factory include several learned lessons about building complexity, energy consumption, costs, savings, IAQ and health improvement. A proof of concept of building performance prediction based on neural networks (applied to CO2 and temperature) is proposed. This first learning shows that IAQ measurements meet recommended levels around 90% of the time and that an IoT-managed HVAC system can achieve energy-consumption savings of between 10 and 15%. In summary, in a real context involving economic restrictions, complexity, high energy costs, social vulnerability, and climate change, IoT-based strategies, as proposed in this work, offer a modular and interoperable approach, moving towards smart communities (buildings, cities, regions, etc.) by improving energy efficiency and environmental quality (indoor and outdoor) at low cost, with quick implementation, and low impact on users. Great challenges remain for growth and interconnection in IoT use, especially challenges posed by climate change and sustainability.

Prosumers integration in aggregated demand response systems

In recent years, the increasing popularity of renewable energy and energy-efficient technologies is creating a new movement towards more sustainable communities. Understanding energy consumption is important for the optimisation of resources and the implementation of ecological trends. This paper integrates electricity consumers into a cooperative framework for planning sustainable smart communities through aggregators, which reallocates consumers’ demand according to available renewable energy supply collected from consumers and service providers. The aggregated demand response also includes consumers involved in energy production activities through microgeneration capabilities. A characterisation study of the different types of demand preferences is performed by defining scenarios of communities and consumers’ behaviours, which are validated through a reputation factor. The results show that the system adequately manages demand reallocation following the preferences and contribution of consumers and/or prosumers. Besides, this research analyses the current energy policy concerning demand flexibility, demand aggregation and microgeneration capacity, and their regulations in Spain. Finally, microgeneration acceptance, the role of aggregators and prosumers in the scheduling process is also investigated through a series of surveys.

Technology Enabled Intelligent Solution in Human Resource Management for Smart Cities

The foundation of smart cities is based on an autonomous and decentralized architecture, which consists of sophisticated information and communication technologies (ICT) in convergence with technology enabled solution to improve the business management process in industry 4.0. This study tends to examine the adoption of blockchain technologies (DLT) in the human resource management (HRM) of organizations in building solutions for IOT (Internet of things) smart cities. The current study explores a unique set of factors selected from the extensive literature and acquired information from fifteen experts having significant experience of blockchain technology in their respective organizations. An integrated fuzzy analytic hierarchy process (F-AHP) is applied to prioritize the identified success factors. Further, the modified decision-making trial and evaluation laboratory (M-DEMATEL) method is utilized to represent the complicated causal relationships among different sub-factors on blockchain-HRM integration. The findings show the application of blockchain will foster a paradigm change in IOT based smart communities, where recruiters verify the candidate credentials including education, skills, and work experience. The payroll managers would determine the more effective way to make work less complex and moderate, enabling timelier payments to global employees. Furthermore, DLT would enhance the employee learning records and update the real-time information in HRM database technologies. Thus, providing a detailed guide for future Industry 4.0 developers about how blockchain can improve the next generation of industrial applications. The developed method can help the decision-makers and provide a foundational view to examine the benefits of implementing blockchain technology in the HRM setting of an organization before they choose to integrate in order to enhance Industry 4.0 technologies. This research will be a novel attempt to synthesize the key factors and subfactors about technology enabled solution within the intelligent HRM process, shedding light to rethink HRM strategies to incorporate blockchain technology in organizations.

A DLT-based framework for secure IoT infrastructure in smart communities

In the field of smart communities, significant progress has been made in recent years. The objective of constructing smart communities is to improve the quality of life of their inhabitants. To accomplish this objective, technologies such as Internet of Things (IoT) and Artificial Intelligence (AI) were deployed. The data gathered and processed by IoT devices, particularly those with centralized control, are however susceptible to availability, integrity, and privacy risks. Due to its inherent properties of transparency, immutability, and underlying secure-by-design architecture, Distributed Ledger Technology (DLT) and Smart Contracts enable distributed, decentralized, automated workflows that can be incorporated to automate the management of the next generation of IoT networks. Using a potential use case, a conceptual architecture for securing smart communities with DLT is developed and explained. In this paper, a framework for IoT eco-systems is proposed that provides seamless integration between IoT and DLT to create a decentralized trusted architecture that ensures the trustworthiness of IoT eco-systems at design time and a trust reputation model based on the architecture to protect it at run-time. In addition, the initial implementation steps are described for this framework.

Research on security control technology of smart community based on personnel positioning management

Research on security control technology of smart community based on personnel positioning management

Retracted: Building an Urban Smart Community System Based on Association Rule Algorithms

Retracted: Building an Urban Smart Community System Based on Association Rule Algorithms

A sharing economy model for a sustainable community energy storage considering end-user comfort

A promising solution for the current and future power system challenges like the increasing penetration of demand-side distributed energy resources and the economies of scale of individual energy storage systems could be the concept of the smart Community Energy Storage (CES). This paper focuses on developing an energy cooperation framework between photovoltaic prosumers and CES. In the proposed structure, an appropriate environment is provided in the energy community to consider several smart homes that together form an energy community. They can store and generate energy by some central devices, including combined heat and power unit, thermal storage system, and electrical energy storage. Furthermore, each end-user individually owns a rooftop PV system and a heating, ventilation, and air conditioning system where the uncertainty of the PV generation unit is modeled by a scenario-based approach. The main question of this study is what benefits an energy community provides to the set of end-users. The goal of the energy community manager of the smart CES as the objective function of the scheduling problem is to minimize energy cost and end-user discomfort level, where ε-constraint method is used to solve the multi-objective CES scheduling problem. The main contribution of this paper is introducing the sharing economy concept and considering the role of occupants' thermal comfort, the impacts of time importance and end-user thermal sensitivity, and the impact of thermal comfort in the CES. The proposed model is structured as a mixed integer linear programming problem that is implemented in the GAMS software. Results show that by using CES, the energy cost decreases about 28.48% while the end-user discomfort level significantly improves.

Mind the gap: The AURORAL ecosystem for the digital transformation of smart communities and rural areas

Rural areas play a crucial role in addressing challenges related to climate change, food provision, biomass, and energy. At the same time, digital solutions have proven essential in improving safety, quality of life, and resilience in daily life. However, the lower population density and the lack of digital infrastructure in such rural areas make it difficult to develop technology-driven private businesses and public services. This can negatively impact socio-economic indicators and hinder the development of new services to cover peoples’ needs. For this reason, in this document, we seek to provide a stronger focus on rural regions in digitalization efforts and create new opportunities for rural communities. For that, we analyze the barriers and needs of the rural environment and present AURORAL, a digital service platform designed to meet the needs and contexts of rural areas. This ecosystem, comprising sustainable and multi-interoperable apps and services, can help communities succeed in innovation and smart transformation, providing the necessary infrastructure to facilitate long-lasting social, environmental, and economic benefits by prioritizing openness, interoperability, and decentralization. On the principle that the full potential of these technologies can only be realized when they are integrated into societal and economic activity and organization, AURORAL aims to promote economic growth and digitalization in the rural domain and contribute to bridging the digital divide between rural and urban areas.

Towards smart communities using solar photovoltaic technologies: A comparative assessment by novel wins in league theory

In the present work, hybrid energy systems based on various types of solar photovoltaic technologies is investigated for rural electricity supply. Five configurations are considered based on solar tracking systems, including biaxial, uniaxial and non-tracking. Solar photovoltaic size is optimized by HOMER software. Choosing the appropriate configuration is based on considering the simultaneous effect of six criteria, including renewable fraction (RF), solar capacity factor (CF), initial equipment cost, levelized cost of energy (LCOE), CO2 emission and energy security. In this study, for the first time the theory of Wins in League (WIL) is used to select the best system. This theory is a form of classical multicriteria decision-making methods. Technical evaluations showed that the highest amount of RF and CF is related to the vertical uniaxial and biaxial tracking system, respectively. The solar system without tracking has the lowest LCOE, but the horizontal uniaxial tracking system has the highest LCOE. In general, LCOE between different configurations ranges from 0.198 to 0.207 $/kWh, and solar energy is proper for electrification in Iranian rural areas. The results of the WIL theory also show that, the biaxial solar tracking system is best option in rural areas.

A tri-layer stochastic framework to manage electricity market within a smart community in the presence of energy storage systems

In recent years, with the restructuring of the electricity market, the main goal of all market participants is to maximize their profits. Among these, the stability of the system as well as the consumers' comfort index (CI) are two important points that should be considered in the scheduling. Hence, this paper presents a tri-layer model for managing a competitive electricity market in the presence of microgrids and demand response (DR) aggregators, in which microgrids determine their strategy for market participation by considering the CI of consumers. In the first layer of the proposed model, the DR aggregator buys part of the consumers load through shiftable and curtailable demand response programs (DRPs), and offers it for sale in the market. The second layer, microgrids do their scheduling with the aim of minimizing operating costs and maximizing the CI, and submit their offers/bids into the market. Finally, in the third layer, the market-clearing price (MCP) is determined by the market manager with the aim of maximizing social welfare. This model is formulated in mixed-integer linear programming (MILP) format and is solved through CPLEX solver in GAMS environment. The simulation results show that the two-objective modelling of the operation problem, despite a 12.18 % increase in total operating costs, increases the average CI by 5.57 %. The results also demonstrate that DR aggregator through the implementation of DRPs leads to a reduction in MCP during the peak period and thus a 5.01 % reduction in total operating costs.

Cooperative Power Bidding of Smart Community Grids With an Aggregator-Prosumer-Based Hierarchical Framework

The progressive development of electricity markets envisions the participation of smart community grids in energy trading, but it is still challenging to guarantee global optimality for uncertain power management of multiple entities under a hierarchical framework. To tackle the cooperative strategic bid-ding problem with uncertainties, this paper proposes a hierar-chical three-stage robust optimization (HTS-RO) method. With respect to the bilayer coordination framework involving an ag-gregator gathering multiple prosumers, a novel HTS-RO bidding model is firstly established relying on the canonical centralized two-stage RO model. In the first stage, the aggregator performs power bidding in the upper layer according to the derived power flow information of the shared buses from the lower-layer prosumers. Considering renewable-load uncertainties and pri-vacy preservation, each prosumer conducts its own robust scheduling via the second and third stages based on the bidding prices from the aggregator and submits its optimal results of the shared bus back to the aggregator. For the robust scheduling model of each prosumer, the second stage identifies the basic plans of the nominal scenario, and the third stage checks the fea-sibility of the basic plans under uncertainties. To solve the re-sulting intractable multi-level mixed-integer nonlinear pro-gramming, a tri-loop decomposition-based iterative algorithm is tailored to ensure that the distributed computation converges to the optimal solution with the overall profit, thereby achieving the equivalent split of the centralized optimization into a hierarchical manner. Numerical tests on generic smart community grids with multiple prosumers validate the applicability and superiority of the proposed HTS-RO method for power bidding.

Retracted: Measures and Suggestions for Smart Community Development Based on Urban Renewal

Retracted: Measures and Suggestions for Smart Community Development Based on Urban Renewal

SMART Communication: An Emerging Era of Communication

SMART Communication: An Emerging Era of Communication

Intrusion detection system to advance IoT security environment

Nowadays, with the technological improvement, communications with the things become easier. It helps people to live an easier life, live and work smarter as well as take back control of their lives completely. this smart communication is done in an environment that called Internet of Things (IoT) environment. The Internet of Thing is multiple physical objects that communicate using the internet, allowing sending, and receiving of data. Since it’s a data so it's prone to attack in a goal of steal it, change it and so many reasons. In addition, nowadays hackers are everywhere with so many types. So, it needs to protect those data and the devices, if Internet of Things devices doesn't have enough security to protect the system from being compromised, then many threats and attacks will occur. If the administrator does not apply strong security and develop a plan for system and device prevention, the Internet of Things environment will be weak, which will make the system and devices prone to attack. Unauthorized access will be prevented if the login system includes a signature matching system. This research aims to analyze the traffic security and analyze threats and risks using IoT devices from intruders by applying an IDS to the IoT environment. when the attacker will try to enter to the traffic or send any packets to any IoT devices, the intrusion detection system will send an alert to the administrator that there's something wrong need to check, the IDS will detect the attacker's name, type and from which device he tries to enter to the system, it will analyze the traffic system, as well as will prevent the devices and data from threats.

Mapping a Decade of Smart Homes for the Elderly in Web of Science: A Scientometric Review in CiteSpace

Challenges caused by the care of the ageing population in many countries are becoming increasingly severe. However, high expenditures on healthcare services and the cost of infrastructure construction will be an unbearable burden for both the government and individuals. Due to its security, convenience, and lower prices compared with traditional medical care, smart home technology, which includes information and communication technologies (ICTs), artificial intelligence (AI), and the Internet of Things (IoT), can reduce the care burden. While smart home studies targeting older adults have increased, systematic analysis of these studies is lacking. CiteSpace enables rapid clustering and visualisation of the literature using scientific diagrams, exhibiting the results more comprehensibly. This analysis of academic research published within the last decade (from 2012 to 2023) through a scientometric approach can help to understand the historical variations, the latest technologies and emerging trends, and the research clusters that have emerged related to the study of smart homes for the elderly (SHFTE). The study results showed that recent research mainly centres on IoT for home automation and home-based healthcare, including wearable device applications and information security analysis. Research trends regarding SHFTE have focused primarily on developing and updating smart technologies based on the IoT, sensors, and related home monitoring. Therefore, greater emphasis must be placed on connecting smart homes and intelligent buildings with communities and societies, developing the potential of smart communities, and investigating the application of smart integration to the home and community in cities.

Fabrication of coral tentacle-like ZIF-67 derived NiCo-LDH/Ag nanowires on cotton fibers for wearable supercapacitor electrode materials

Wearable flexible electronic devices suitable for the human body have promising prospects in areas such as health monitoring and smart communication. Therefore, rational design and fabrication of flexible electrode materials is of great importance for efficient energy storage in wearable electronic devices. In this work, a unique coral tentacle-like interconnected network structured nickel-cobalt layered double hydroxide/silver nanowires/cotton (NiCo-LDH/AgNWs/Cotton) flexible electrode material is developed by a facile three-step method: (ⅰ) AgNWs are adsorbed on cotton fibers to form a conductive network by dipping, (ⅱ) ZIF-67 precursors grow on AgNWs/Cotton by in-situ, and (ⅲ) ZIF-67 precursors are converted into interconnected NiCo-LDH nanosheets by hydrothermal. The NiCo-LDH/AgNWs/Cotton electrode material exhibits an ultra-high areal capacitance (823.9 mF cm−2 at 1 mA cm−2), and decent cycling performance (77.7 % after 1000 cycles). The assembled symmetrical supercapacitor exhibits 8.63 μWh cm−2 energy density at a power density of 0.26 mW cm−2. In addition, NiCo-LDH/AgNWs/Cotton electrode material also have excellent flexibility, mechanical properties, and electromagnetic shielding. This study achieves high-value utilization of cotton fibers and provides fresh ideas for the development of flexible supercapacitors.

ANALYSIS OF THE FEATURES OF EFFECTIVE IMPLEMENTATION OF SOLAR POWER PLANTS IN LOCAL ENERGY SUPPLY SYSTEMS

It is shown that renewable energy sources (RES) are increasingly dominating the electricity market in many countries, while the amount of electricity generation by solar power plants (SPP) has been growing at a record pace in recent years. It is noted that although the share of RES continues to grow and the photovoltaic industry is developing rapidly, the industry still faces many challenges, in particular, how to continue to reduce the Levelized Cost of Energy (LCOE), improve the efficiency of operation and maintenance, and maintain the stability of the power grid, to ensure system security. The effective implementation of solar generation requires an analysis of the prospects for the development of local electric power systems that include SPP, the development of mechanisms and appropriate regulatory, methodological, technical and organizational support that will contribute to the effective development of solar generation, the construction of modern system (schematic) solutions.
 The analysis of the features of the development of green generation in Poland and Ukraine was carried out, the positive factors that influenced the development of renewable energy sources in Ukraine were determined, which made it possible to form the technical, economic and organizational conditions for the successful development of solar generation, in particular, information was provided on new players in developed energy markets according to the Fourth Energy EU package. The analysis showed that when increasing the efficiency of SPP systems, planning and demand management in the electric network, effective functioning of Energy Smart Community (ESC) become important.
 The basic components of the effective functioning of electric power systems with SPP are highlighted, namely: concepts of configurations of photovoltaic systems, Smart-inverters, Energy Storage System (ESS), formation of Virtual Power Plant (VPP) based on SPP. It is shown that each of the four concepts involves the connection of a series of photovoltaic panels or strings and power electronics devices (DC converters and inverters), which are configured taking into account the peculiarities of the functioning of various structural (schematic) solutions. The advantages of using Smart-inverters as a new technology that can help integrate solar energy and other distributed energy resources into the electrical network are evaluated. Smart inverters are used to help the electrical grid cope with intermittent generation, helping the electrical grid remain stable and maintain voltage and frequency requirements.
 It was determined that in any photovoltaic system, the ESS itself becomes a central component that significantly affects the cost, maintenance requirements, reliability and design of the SPP, and the important parameters of the ESS that affect the operation and performance of the photovoltaic system are the battery maintenance requirements, battery life, available power and efficiency. Trends in the market of advanced energy storage systems for SPPs for the next decade are presented. The functioning of virtual power plants based on SPP, as a network of aggregated distributed energy resources that are remotely connected and work together with flexible electricity consumers, is aimed at maximizing the benefits of participants. The possibilities and trends of SPP development in the near future, which are based on the research of Huawei, are presented.

A comprehensive review of energy efficient routing protocols for query driven wireless sensor networks

In this current era of communications and networking, The Internet of things plays the main role in the making of smart communication and networking. In this article, we have focused on the literature survey on wireless sensor networks which are energy efficient. Various standard protocols are reviewed along with some enhanced protocols which makes the network energy efficient. The comparison of the standard and enhanced protocols with respect to various applications in wireless sensor networks is thoroughly done in this article. The outcomes of the enhanced protocols are also briefly discussed. For easier analysis to future researchers, a comparative table which lists the enhanced protocols which are compared with standard counterparts along with the factors for energy efficiency of the protocols. This article also comments on the issues and challenges of the protocols which can be further analyzed for making the wireless sensor network more energy efficient.

A contemplative overview of smart communities: a hybrid analytical approach

PurposeThis study aims to uncover and develop explicit knowledge of existing smart communities (SCs) to guide services and business solutions for enterprises and serve community users in a well-thought-out manner. These sagacious frameworks will assist in analyzing trends and reaching out to pre-existing setups with different degrees of expertise.Design/methodology/approachA systematic overview is provided in this paper to unify insights and competencies toward building SCs; a hybrid analytical approach is used consisting of machine learning and bibliometric analysis. Scopus and Web of Science (WoS) are the primary databases for this purpose.FindingsSCs implement cutting-edge technologies to enhance mobility, elevating information and communication technology (ICT) skills and data awareness while improving business processes and efficiency. This system of SC is an evolution of the conventional method. It provides a foundation for intelligent community services based on individual users and technologies such as the Internet of Things (IoT), artificial intelligence, cloud computing and big data. Manufacturing-based, service-based, retail-based, resource management and infrastructure-based SCs exist in the literature.Originality/valueThe paper summarizes a conceptual framework of SCs based on existing works around SCs. To the best of the authors’ knowledge, this is the first systematic literature review that uses a hybrid approach of topic modeling and bibliometric analysis to understand SCs better.