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  • Leveraging the GQM+ Strategy approach and Industry 4.0 technologies for environmental sustainability in manufacturing

    Giancarlo Nota, Alonso Toro Lazo
    J Smart Environ Green Comput 2022;2:143-62. DOI: 10.20517/jsegc.2022.13
    Abstract
    Aim: In the last years, sustainability has been identified as an enormous problem, with many ... MORE
    Aim: In the last years, sustainability has been identified as an enormous problem, with many facets gaining increasing attention. In this broad scenario, the availability of models for environmental sustainability constitutes a conceptual tool to guide industries towards reducing the environmental impact deriving from production. This work aims to contribute to the research on environmental sustainability in manufacturing by proposing a model that leverages the Goal Question Metrics approach and technologies of Industry 4.0.Methods: The Goal Question Metrics approach and technologies of Industry 4.0 are leveraged by proposing a model that contributes to environmental sustainability in manufacturing.Results: A model is proposed that can be used as a conceptual tool to support improvement programs in environmental sustainability.Conclusion: The application of the Goal Question Metrics+ Strategies to a case study of an automotive industry shows how the approach, combined with the implementation of Industry 4.0 technologies, contributes to the efficient use of natural resources and also reduces the emissions in the atmosphere. LESS      Full article
    Original Article|Published on: 30 Sep 2022
    Full-Text | PDF-1.1M

  • Solar powered UAV charging strategy design by machine learning

    Prakash Ravi, ... Mark J Scott
    J Smart Environ Green Comput 2022;2:126-42. DOI: 10.20517/jsegc.2022.02
    Abstract
    Aim: The rapid growth in the number of ground users over recent years has introduced ... MORE
    Aim: The rapid growth in the number of ground users over recent years has introduced the issues for a base station of providing more reliable connectivity and guaranteeing the reasonable quality of service (QoS). Thanks to the unique features of unmanned aerial vehicles (UAVs), such as flexibility in deployment, large coverage range and lower cost, UAVs can help the base station to provide wireless connectivity to the ground users, e.g., in rural and remote areas. As the energy limitation is the main concern for UAVs, the motivation is to provide uninterrupted connection to ground users in the next generation wireless networks using solar powered UAV-assisted air networks.Methods: The research uses global horizontal irradiance (GHI) data from the National Renewable Energy Laboratory, small cell power ratings for communication, and UAV parameters. In addition, the TensorFlow library and Python programming language were also used to develop machine learning models and simulate the UAV flying time.Results: In this paper, we develop a novel resource management system for UAVs, which consists of an energy harvesting deep learning model to predict the future power harvested from the solar panel and a consumption model which determines user arrival rate. With energy consumption and harvesting predictions, the resource management system adaptively switches the power consumed by a UAV for communication. In addition, based on the future energy availability and user's arrival rate, the resource management system communicates with other UAVs and enables energy coordinating scheduling among multiple UAVs to support user communications. The experiment results demonstrate that by using adaptive energy scheduling among UAVs, the flying time of the UAVs is improved by 40% during nighttime and by 37% when performing energy coordination among multiple UAVs.Conclusion: In this work, the UAV based communications have been researched. To understand more about UAVs and air segments, some literature review has been done based on previous works. Finally, alteration of the transmission power using several methodologies has been accomplished to increase the flying time of the UAV. LESS      Full article
    Original Article|Published on:  1 Sep 2022
    Full-Text | PDF-830K

  • Performance analysis for wireless-powered IoT networks with hybrid non-orthogonal multiple access

    Huiwen Qi, ... Han Zhang
    J Smart Environ Green Comput 2022;2:105-25. DOI: 10.20517/jsegc.2022.04
    Abstract
    Aim: In this paper, we study a wireless-powered Internet of Things (IoT) network, where a ... MORE
    Aim: In this paper, we study a wireless-powered Internet of Things (IoT) network, where a hybrid access point (HAP) charges IoT devices with wireless energy transfer technology (WET) and collects their data by wireless information transfer (WIT).Methods: To improve spectral efficiency, we propose a hybrid non-orthogonal multiple access (NOMA)-based transmission scheme. On the one hand, NOMA technology is applied for WIT. On the other hand, when some devices transmit data, the HAP can simultaneously charge the other devices, namely concurrent WET and WIT, such that the other devices can harvest more energy to achieve a better rate with some rate loss of these devices due to interference. %During the transmission of some devices, the WET is simultaneously conducted, such that other devices can harvest more energy to achieve a better rate with a rate loss of these devices due to the interference. How to divide devices into the interference and non-interference groups, namely device grouping, and how to pair devices, e.g., device pairing, becomes critical issues in terms of the achieved network throughput and fairness.Results: We first formulate the network throughput maximization problem by optimizing the pairing and grouping policies. To simplify the analysis, we then investigate two specific hybrid NOMA-based transmission schemes. In the former, all devices are firstly paired based on the max-min criterion, where the "best" device is paired with the "worst" one, and then grouped in either ascending or descending order; this is referred to as the first-pairing-then-grouping (FPTG) scheme. In the latter, devices are first grouped and then paired; this is referred to as the first-grouping-then-pairing (FGTP) scheme. By applying the order statistics theory, we theoretically analyze the achieved network throughput and derive the corresponding pairing and grouping policies. Furthermore, we study the max-min fairness of the proposed hybrid NOMA-based scheme.Conclusion: Simulation results validate the significant improvement of the proposed hybrid NOMA-based scheme in terms of network throughput and fairness. LESS      Full article
    Original Article|Published on: 20 Aug 2022
    Full-Text | PDF-493K

  • Different approaches of bibliometric analysis for data analytics applications in non-profit organisations

    Idrees Alsolbi, ... Mukesh Prasad
    J Smart Environ Green Comput 2022;2:90-104. DOI: 10.20517/jsegc.2022.09
    Abstract
    Aim: Profitable companies that used data analytics have a double gain in cost reduction, demand ... MORE
    Aim: Profitable companies that used data analytics have a double gain in cost reduction, demand prediction, and decision-making. However, using data analysis in non-profit organisations (NPOs) can help understand and identify more patterns of donors, volunteers, and anticipated future cash, gifts, and grants. This article presents a bibliometric study of 2673 to discover the use of data analytics in different NPOs and understand its contribution.Methods: We characterise the associations between data analysis techniques and NPOs using, Bibliometrics R tool, a co-term analysis and scientific evolutionary pathways analysis, as well as identify the research topic changes in this field throughout time.Results: The findings revealed three key conclusions may be drawn from the findings: (1) In the sphere of NPOs, robust and conventional statistical methods-based data analysis procedures are dominantly common at all times; (2) Healthcare and public affairs are two crucial sectors that involve data analytics to support decision-making and problem-solving; (3) Artificial Intelligence (AI) based data analytics is a recently emerging trending, especially in the healthcare-related sector; however, it is still at an immature stage, and more efforts are needed to nourish its development.Conclusion: The research findings can leverage future research and add value to the existing literature on the subject of data analytics. LESS      Full article
    Original Article|Published on: 29 Jul 2022
    Full-Text | PDF-2.9M

  • A case study in smart manufacturing: predictive analysis of cure cycle results for a composite component

    Micaela Lucia Bangerter, ... Fabrizio Leone
    J Smart Environ Green Comput 2022;2:76-89. DOI: 10.20517/jsegc.2022.11
    Abstract
    Aim: This work proposes a workflow monitoring sensor observations over time to identify and predict ... MORE
    Aim: This work proposes a workflow monitoring sensor observations over time to identify and predict relevant changes or anomalies in the cure cycle (CC) industrial process. CC is a procedure developed in an autoclave consisting of applying high temperatures to provide composite materials. Knowing anomalies in advance could improve efficiency and avoid product discard due to poor quality, benefiting sustainability and the environment.Methods: The proposed workflow exploits machine learning techniques for monitoring and early validating the CC process according to the time-temperature constraints in a real industrial case study. It uses CC's data produced by the thermocouples in the autoclave along the cycle to train an LSTM model. Fast Low-cost Online Semantic Segmentation algorithm is used for better characterizing the time series of temperature. The final objective is predicting future temperatures minute by minute to forecast if the cure will satisfy the constraints of quality control or raise the alerts for eventually recovering the process.Results: Experimentation, conducted on 142 time series (of 550 measurements, on average), shows that the framework identifies invalid CCs with significant precision and recall values after the first 2 hours of the process.Conclusion: By acting as an early-alerting system for the quality control office, the proposal aims to reduce defect rates and resource usage, bringing positive environmental impacts. Moreover, the framework could be adapted to other manufacturing targets by adopting specific datasets and tuning thresholds. LESS      Full article
    Original Article|Published on: 22 Jul 2022
    Full-Text | PDF-2.2M

  • Adaptive multi-criteria group decision-making model based on consistency and consensus with intuitionistic reciprocal preference relations: a case study in energy storage technology selection

    Francisco Javier Cabrerizo, ... Juan Antonio Morente-Molinera
    J Smart Environ Green Comput 2022;2:58-75. DOI: 10.20517/jsegc.2022.15
    Abstract
    Aim: This study aims to present a multi-criteria group decision-making model with intuitionistic reciprocal preference ... MORE
    Aim: This study aims to present a multi-criteria group decision-making model with intuitionistic reciprocal preference relations that incorporates a new feedback mechanims adapting its operation to the decision-makers' consistency.Methods: A new adaptive feedback mechanism is developed within a multi-criteria group decision-making model. Assuming different kinds of decision-makers classified according to their consistency, this feedback mechanism customizes the recommendations given by adopting three strategies to identify the problematic assessments that the decision-makers should change if they want to collaborate to increase the consensus.Results: The performance of the proposed model is shown in a case study for the selection of an energy storage technology. It shows that the decision-makers providing assessments with low consistency must modify more assessments, allowing the most consistent decision-makers to be the leaders of the negotiation and persuade the others to adjust their assessments to improve the agreement achieved.Conclusion: In this study, a novel multi-criteria group decision-making model is developed. It includes an adaptive feedback mechanism adjusting the advice provided by considering the decision-makers' consistency. It allows that the assessments of the most consistent decision-makers never be strongly modified during the decision process. LESS      Full article
    Original Article|Published on: 30 Jun 2022
    Full-Text | PDF-464K
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About The Journal

  • ISSN

    2767-6595 (Online)

    Publisher

    OAE Publishing Inc.

    Article Processing Charges

    $600, waives APC from 2021 to 2023

  • Editor-in-Chief

    Witold Pedrycz

    Publishing Model

    Gold Open Access

    Copyright

    Copyright is retained by author(s)

  • Publication Frequency

    Quarterly

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    Total publications: 28

    Total article views: 40,212

    Total article downloads: 8,598

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