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Smart Prediction Models for Energy Efficiency in Smart Residential Buildings: A Deep Learning Approach

Smart Prediction Models for Energy Efficiency in Smart Resid...

2023 International Conference for Technological Engineering and its Applications in Sustainable Development, ICTEASD 2023

作者： Vasantharaj, A. Ahamed, M. Irshad Prema, K. Mudigonda, Aditya Sapaev, J.B. Thandapani, Kavitha Kalaignar Karunanidhi Institute of Technology Information Electronics and Communication Engineering India E.G.S. Pillay Engineering College Department of Electronics and Communication Engineerin Tamilnadu Nagapattinam India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India JNIAS School of Planning and Architecture Telangana Hyderabad500034 India National Research University Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Tashkent Uzbekistan Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Vgy Technology Avadi Department of Electronics and Communication Engineering Tamil Nadu Chennai600062 India

ISBN: (纸本)9798350336474

Using power in houses has given rise to several ecological issues, including air pollution. Predicting building energy use is essential for better regulating or reducing energy usage. Machine Learning (ML) techniques have been used to estimate the power use of operating buildings. However, there has been little research on using ML algorithms to anticipate the prospective energy usage of buildings during the initial design phase. When lowering energy-inefficient buildings, it is crucial to tackle the underlying issue: accurately anticipating energy consumption before construction. This is necessary to prevent the future development of environmentally detrimental buildings. This research introduces a new and innovative Hybrid Deep Learning Model for Predicting Energy Efficiency in Smart Residential Buildings (HDL-PEE-SRB). The suggested framework has two steps: cleaning the information and constructing the model. The information cleansing step utilizes pre-processing methods to manipulate the original information and incorporates lag values as supplementary characteristics. During model-building, the hybrid model undergoes training using the processed data. The HDL model combines fully linked layers, Unidirectional Long Short-Term Memory (Uni-LSTM), and bi-directional LSTMs (Bi-LSTM), which are stacked together. The suggested model is assessed using standard energy usage databases, demonstrating higher accuracy than commonly used HDL models. The proposed model surpasses other HDL models, demonstrating the most favorable performance with a MAPE of 1.94% and an accuracy of 98.06%. © 2023 IEEE.

关键词： Forecasting

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Buckling of a Viscoelastic Anisotropic Fiber Reinforced Plate Under Rapidly Increasing Shear Load

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SSRN 2023年

作者： Eshmatov, Bakhtiyor Mirsaidov, Mirziyod Abdikarimov, Rustamkhan Department of Mathematics Branch of University of Science and Technology "MISaA" Almalyk Uzbekistan Department of Mechanics and Computer Modeling National Research University "Tashkent Institute of Irrigation and Agricultural Mechanization Engineers" Tashkent Uzbekistan Department of Civil Engineering Tashkent University of Architecture and Civil Engineering Tashkent Uzbekistan

The paper investigates the dynamic deformation of a viscoelastic anisotropic reinforced plate caused by rapidly increasing shear load, taking into account geometric nonlinearity. This complex problem is formulated as the solution of systems of nonlinear integro-differential equations with singular relaxation kernels. To solve this problem, a combination of the Bubnov-Galerkin method and a numerical approach using quadrature formulas is used. To substantiate the correctness of the choice of this numerical method, a test case was solved, which showed a sufficiently high accuracy of the obtained results. The study is devoted to the dynamic response of the plate, covering extensive variations of its physical, mechanical and geometric characteristics. © 2023, The Authors. All rights reserved.

关键词： Anisotropy

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Sources of optical radiation based on ZnTe/ZnSe/ZnS heterostructures

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Materials Today: Proceedings 2022年 62卷 5763-5766页

作者： Slyotov, Mykhailo Mazur, Tetiana Prokopiv, Volodymyr Slyotov, Oleksii Mazur, Myroslav Department of Optics Physical Publishing and Printing/Technical and Computer Science Institute Yuriy Fedkovych Chernivtsi National University 2 Kotsubinsky Str. Chernivtsi 58012 Ukraine Department of General and Applied Physics/Institute of Architecture Construction and Power Engineering Ivano-Frankisvsk National Technical University of Oil and Gas 15 Karpatska Str. Ivano-Frankivsk 76019 Ukraine Department of Solid State Physics and Chemistry/Faculty of Physics and Technology Vasyl Stefanyk Precarpathian National University 57 Shevchenko Str. Ivano-Frankivsk 76019 Ukraine

The heterostructures of zinc chalcogenides β-ZnTe/ZnSe/ZnS were obtained by isovalent substitution. The regimes for obtaining materials that ensured the stability of the cubic lattice of heterolayers of zinc chalcogenides β-ZnSe and β-ZnS were determined. The isovalent elements Se and S determined the solid-phase substitution and determined the formation of heterolayers in the lattice of the surface of the base crystal. The optical transmission, reflection, and photoluminescence spectra of the heterolayers are studied. The analysis of the results of studies of the energy structure of the obtained heterolayers was carried out, which indicates the correspondence of these heterolayers to the compounds of zinc selenide and zinc sulfide obtained by classical technological processes. They are also confirmed by the results of studies of the optical transmission of β-ZnSe and β-ZnS films specially obtained on transparent substrates under the same growing conditions as compared to isovalent substitution. © 2022

关键词： Light transmission

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Inventory Management System based on IoT and Microservices architecture Design

Inventory Management System based on IoT and Microservices A...

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International Electrical Engineering Congress (iEECON)

作者： Paisan Sithiyopasakul Chavinkorn Piyatananugoon Vasutorn Chaowalittawin Woranidtha Krungseanmuang Posathip Sathaporn Isoon Kanjanasurat Boonchana Purahong Tunjai Archevapanich Attasit Lasakul Computer Engineering Department King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand College of Computing Khon Kean University KhonKean Thailand Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Nonthaburi Thailand

This paper presents the inventory management system based on IoT and microservices architecture that synced between IoT (Internet of Things) and web application. There are two main parts consisting of IoT forklift vehicle and data transmitted system by MQTT protocol. Microservice can utilize data to process business logic and provides API. Inventory area includes a zone, a subzone and parking area for forklifts to scan QR code on each subzone. Data of forklifts is published to back-end service. The results of system microservice publish information events and processes business data to the admin client with a delay under a second.

关键词： Productivity Industries Protocols Microservice architectures QR codes Inventory management Manufacturing

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Robotic additive construction of bar structures: unified sequence and motion planning

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Construction Robotics 2021年第2期5卷 115-130页

作者： Huang, Yijiang Garrett, Caelan R. Ting, Ian Parascho, Stefana Mueller, Caitlin T. Building Technology Program Department of Architecture Massachusetts Institute of Technology Cambridge USA Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge USA CREATE Laboratory School of Architecture Princeton University Princeton USA

Additive robotic construction of building-scale discrete bar structures, such as trusses and space frames, is increasingly attractive due to the potential improvements in efficiency, safety, and design possibilities. However, programming complex robots, such as manipulators with seven degrees of freedom, to successfully complete construction tasks can be tedious, challenging, or impossible for a human to do manually. Namely, the structure must be constructed in a sequence that preserves structural properties, such as stiffness, at each step. At the same time, this sequence must allow for the robot to precisely manipulate elements within the in-progress structure while respecting geometric constraints that, for example, ensure the robot does not collide with what it has built. In this work, we present an automated and newly generalized planning approach for jointly finding a construction sequence and robot motion plan for additive construction that satisfies these requirements. Our approach can be applied in a variety of additive construction processes, and we demonstrate it specifically on spatial extrusion and discrete bar assembly in this paper. We demonstrate the effectiveness of our approach on several simulated and real-world extrusion and assembly tasks, including a human-scale physical prototype, for which our algorithm is deployed for the first time to plan the assembly of a complicated double tangent bar system design.

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Growing Aspects of Cyber Security in E-Commerce 4

Growing Aspects of Cyber Security in E-Commerce

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4th International Conference on Communication, Information and Computing technology, ICCICT 2021

作者： Bhatia, Nishant Lalitkumar Shukla, Vinod Kumar Punhani, Ritu Dubey, Shish Kumar Bachelor of Information Technology Amity University Dubai United Arab Emirates Department of Engineering and Architecture Amity University Dubai United Arab Emirates Department of Information Technology ASET Amity University Sector – 125 Uttar Pradesh Noida India Department of Computer Science and Engineering Jaipur National University India

ISBN: (纸本)9781665404303

The world is witnessing a transition from in-store shopping to online shopping. E-commerce (Electronic commerce) giants such as Amazon, Alibaba, eBay etc. are leading the way towards this change. Much technological advancement are being made to ease the life of mankind with online shopping being the most notable. E-commerce is known to be a powerful instrument for transformation of business that gives companies the opportunity to upgrade their supply chain operations, improve their network, as well as provide better services to both customers and suppliers. Applying the techniques of online shopping that yield such advantages may not be possible without the presence of a well-organized approach to E-commerce security. Ecommerce organizations such as Amazon and Alibaba have also been using such techniques to ensure data protection. The most common of them all is the One Time Password (OTP), which is sent to a user when they make payments online for identity verification. On the other hand, Alibaba uses a unique Key Management System (KSM) which is a fully managed service that helps customers create, delete, and manage encryption keys to protect data. This system provides availability, reliability and elasticity alongside security and compliance. The paper also explore the importance of different security algorithms in Ecommerce domain. © 2021 IEEE.

关键词： Cryptography

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Analysis of Environmental Factors for Smart Farming: An Internet of Things Based Approach 10

Analysis of Environmental Factors for Smart Farming: An Inte...

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10th International Conference on System Modeling and Advancement in Research Trends, SMART 2021

作者： Agarwal, Ambuj Kumar Ather, Danish Astya, Rani Parygin, Danila Garg, Amit Raj, Dharm Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Sharda University Department of Computer Science and Engineering Greater Noida India Volgograd State Technical University Department of Digital Technologies in Urban Studies Architecture and Construction Volgograd Russia Chandigarh University AIT-Computer Science and Engineering Department Chandigarh India

ISBN: (纸本)9781665439701

The Internet of Things also referred to as IoT plays an important role in our everyday lives by allowing us to control electrical gadgets through networks. Controlling is accomplished by meticulously watching key parameters that produce critical information about the operation of this electrical equipment. At the same time, the critical information will transfer from the transmitting device and preserved on the cloud for apps and secondary processes to access. This investigation connects the results of environmental measures such as temperature and humidity taken by making use of sensors. The data acquired might be put to good use to create activities such as faraway dominating long-term statistics, cooling, or heating devices that can be utilised to govern the situation. The observed data is transferred to a cloud storage service through the internet and linked to an Android application. Arduino UNO and sensor devices, and ESP8266 Wi-Fi module are used in the system. Using Arduino UNO. The testing and findings will disclose the live temperature and humidity of the surroundings, as well as the soil moisture of sample soil.. The sensor element is used to check the humidity and temperature using the DHT 11 sensor. The sensors are used to take temperature readings from the environment and store the data on Thinkspeak Cloud. The ESP8266 Wi-Fi module was utilized to connect with the internet and store the data on the Thinkspeak cloud in this project. © 2021 IEEE.

关键词： Data transfer

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Deep Transfer Learning for 3d Point Cloud Understanding: A Comprehensive Survey

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SSRN 2023年

作者： Sohail, Shahab Saquib Himeur, Yassine Amira, Abbes Fadli, Fodil Mansoor, Wathiq Atalla, Shadi Copiaco, Abigail Department of Computer Science and Engineering School of Engineering Sciences and Technology Jamia Hamdard New Delhi110062 India College of Engineering and Information Technology University of Dubai Dubai United Arab Emirates Department of Computer Science University of Sharjah United Arab Emirates Institute of Artificial Intelligence De Montfort University Leicester United Kingdom Department of Architecture & Urban Planning Qatar University Doha2713 Qatar

3D point cloud (3DPC) has significantly evolved and benefited from the advance of deep learning. However, the latter faces various issues, including the lack of data or annotated data, the existence of a significant gap between training data and test data, and the requirement for high computational resources. To that end, deep transfer learning (DTL) has been widely investigated as it allows knowledge transfer from synthetic to real data and mitigates data annotation constraints. Additionally, it helps reduce the discrepancy between the source and target domains using domain adaptation. Despite that, a detailed survey on its contributions to 3DPC is still missing. To the best of the authors' knowledge, this paper presents the first study shedding light on this aspect. Typically, DTL's background is presented along with the datasets and evaluation metrics. Following, a well-defined taxonomy of existing frameworks is presented. Lastly, open challenges are identified before deriving future directions. © 2023, The Authors. All rights reserved.

关键词： Knowledge management

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Rolling Stock Shunt Operation Planning in Urban Rail Transit Depots

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SSRN 2024年

作者： Wang, Dian Yao, Ling D'Ariano, Andrea Zhan, Shuguang Wang, Lisha School of Automotive and Transportation Engineering Hefei University of Technology Anhui Hefei230009 China Department of Civil Computer Science and Aeronautical Technologies Engineering Roma Tre University Rome00146 Italy School of Architecture and Urban Planning Chongqing University Chongqing400030 China

This study investigates daily rolling stock shunt operation planning in an urban rail transit depot. Given the layout of a depot and the rolling stocks (that arrive at and depart from this depot within an operation day) with given maintenance schedule, the studied problem lies in determining: 1) the position where each rolling stock stops to be parked, outside washed, and/or maintained, and 2) the conflict-free shunting plan of rolling stocks to move within depot. We transform the studied depot into different multiple-layer directed graphs (to represent the infrastructures in a microscope perspective) based on depot’s layout and maintenance schedule of rolling stocks, to illustrate the specific shunting processes of each rolling stock. By means of these resulting graphs, we formulate the studied problem as a mixed integer linear programming model by incorporating several additional requirements (that are not or rarely considered in previous related works) and a specific situation of Chinese urban rail transit system, to increase the attractiveness of our solutions for rail dispatchers. We also introduce a logic-based Benders decomposition algorithm to efficiently solve real-life problem instances, where three groups of customized acceleration mechanisms (including strengthening the bounds of variables, reducing total numbers of variables and constraints involved, and designing additional feasibility cuts) are explored to improve solution performance of our algorithm. Finally, a set of realistic and realworld instances with different scales, derived from the largest depot of Chongqing Rail Transit Line 3 in China, are investigated to demonstrate the efficiency and effectiveness of our model and algorithm. Computational results reveal that our algorithm solves a real-life instance in approximately 8 seconds which is considerably shorter than the time of dispatchers to solve the studied problem manually, thus our approach can provide strong automatical computer-aided d

关键词： Integer programming

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An Improved Weighted Ensemble Clustering Based on Two-Tier Uncertainty Measurement

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SSRN 2022年

作者： Gu, Qinghua Wang, Peipei Li, Xuexian Chen, Lu Xiong, Neal N. School of Management Xi’an University of Architecture and Technology Xi’an China Xi’ an Key Laboratory for Intelligent Industrial Perception Calculation and Decision Xi'an University of Architecture and Technology Xi’an China Department of Mathematics and Computer Science Northeastern State University OK United States

Existing local weighted ensemble clustering algorithms strive to weight on each cluster, which take into account the differences among all clusters. However, the base clustering label on each cluster is ignored. The purpose of this paper is to combine the influence of cluster level and base clustering level in a unified ensemble clustering framework. A novel two-level weighted ensemble cluster method (TWEC) is proposed, which inserts global weighting strategy into a locally ensemble cluster learning framework. First, the cluster uncertainty based an entropy criterion is refined by considering the base clustering labels for each cluster. Then, two-level uncertainty is converted to cluster reliability via improved ensemble-driven cluster validity measure. Finally, two novel consensus functions are developed. The effectiveness of the proposed framework TWEC is verified against fourteen real-world datasets and ten comparison algorithms. The results demonstrate that the TWEC framework can improve the robustness and stability of the clustering. © 2022, The Authors. All rights reserved.

关键词： Clustering algorithms

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