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Digital Twin-driven approach to improving energy efficiency of indoor lighting based on computer vision and dynamic BIM
رویکرد دیجیتال دوقلو برای بهبود بهره وری انرژی در روشنایی داخلی بر اساس بینایی کامپیوتر و BIM پویا-2022 Intelligent lighting systems and surveillance systems have become an important part of intelligent buildings. However, the current intelligent lighting system generally adopts independent sensor control and
does not perform multi-source heterogeneous data fusion with other digital systems. This paper fully
considers the linkage between the lighting system and the surveillance system and proposes a digital
twin lighting (DTL) system that mainly consists of three parts. Firstly, a visualized operation and maintenance (VO&M) platform for a DTL system was established based on dynamic BIM. Secondly, the environment perception, key-frame similarity judgment, and multi-channel key-frame cut and merge
mechanism were utilized to preprocess the video stream of the surveillance system in real-time.
Lastly, pedestrians detected using YOLOv4 and the ambient brightness perceived by the environment
perception mechanism were transmitted to the cloud database and were continuously read by the
VO&M platform. The intent here was to aid timely adaptive adjustment of the digital twin and realistic
lighting through the internet. The effectiveness of the proposed method was verified by experimenting
with a surveillance video stream for 14 days. The key results of the experiments are as follows: (1) the
accuracy rate of intelligent decision control reached 95.15%; (2) energy consumption and electricity costs
were reduced by approximately 79%; and (3) the hardware cost and energy consumption of detection
equipment and the time and cost of operation and maintenance (O&M) were greatly reduced.
keywords: Computer vision | Digital Twin | Dynamic BIM | Energy-efficient buildings | Intelligent lighting control |
مقاله انگلیسی |
2 |
Prescriptive analytics: Literature review and research challenges
تجزیه و تحلیل تجربی: مرور ادبیات و چالش های تحقیقاتی-2020 Business analytics aims to enable organizations to make quicker, better, and more intelligent decisions with the
aim to create business value. To date, the major focus in the academic and industrial realms is on descriptive and
predictive analytics. Nevertheless, prescriptive analytics, which seeks to find the best course of action for the
future, has been increasingly gathering the research interest. Prescriptive analytics is often considered as the
next step towards increasing data analytics maturity and leading to optimized decision making ahead of time for
business performance improvement. This paper investigates the existing literature pertaining to prescriptive
analytics and prominent methods for its implementation, provides clarity on the research field of prescriptive
analytics, synthesizes the literature review in order to identify the existing research challenges, and outlines
directions for future research. Keywords: Analytics | Prescriptive analytics | Business analytics | Big data | Literature review |
مقاله انگلیسی |
3 |
Intelligent decision-making of online shopping behavior based on internet of things
تصمیم گیری هوشمندانه از رفتار خرید آنلاین مبتنی بر اینترنت اشیا-2020 The development of big data and Internet of things (IoT) have brought big changes to e-commerce. Different
kinds of information sources have improved the consumers’ online shopping performance and make it possible to
realize the business intelligence. Grip force and eye-tracking sensors are applied to consumers online reviews
search behavior by relating them to the research approaches in IoT. To begin with, public cognition of human
contact degrees of recycled water reuses with grip force test was measured. According to the human contact
degrees, 9 recycled water reuses presented by the experiment are classified into 4 categories. Based on the
conclusion drawn from grip force test, purified recycled water and fresh vegetable irrigated with recycled water
are regarded as the drinking for high-level human contact degree and the irrigation of food crops for low-level
human contact degree respectively. Several pictures are designed for eye-tracking test by simulating an on-line
shopping web page on Taobao (the most popular online shopping platform in China). By comparing the fixation
time participants spent on the areas of interest (AOIs), we justify that consumers online reviews search behavior
is substantially affected by human contact degrees of recycled products. It was found that consumers rely on
safety perception reviews when buying high contact goods. Keywords: Online reviews search behavior | Recycled products | Grip force sensor | Eye-tracking sensor | Internet of Things (IoT) |
مقاله انگلیسی |
4 |
Complete coverage path planning using reinforcement learning for Tetromino based cleaning and maintenance robot
برنامه ریزی کامل مسیر پوشش با استفاده از یادگیری تقویتی برای تمیز کاری و نگهداری ربات مبتنی بر Tetromino-2020 Tiling robotics have been deployed in autonomous complete area coverage tasks such as floor cleaning, building
inspection, and maintenance, surface painting. One class of tiling robotics, polyomino-based reconfigurable
robots, overcome the limitation of fixed-form robots in achieving high-efficiency area coverage by adopting
different morphologies to suit the needs of the current environment. Since the reconfigurable actions of these
robots are produced by real-time intelligent decisions during operations, an optimal path planning algorithm is
paramount to maximize the area coverage while minimizing the energy consumed by these robots. This paper
proposes a complete coverage path planning (CCPP) model trained using deep blackreinforcement learning (RL)
for the tetromino based reconfigurable robot platform called hTetro to simultaneously generate the optimal set
of shapes for any pretrained arbitrary environment shape with a trajectory that has the least overall cost. To this
end, a Convolutional Neural Network (CNN) with Long Short Term Memory (LSTM) layers is trained using Actor
Critic Experience Replay (ACER) reinforcement learning algorithm. The results are compared with existing
approaches which are based on the traditional tiling theory model, including zigzag, spiral, and greedy search
schemes. The model is also compared with the Travelling salesman problem (TSP) based Genetic Algorithm (GA)
and Ant Colony Optimization (ACO) schemes. The proposed scheme generates a path with lower cost while also
requiring lesser time to generate it. The model is also highly robust and can generate a path in any pretrained
arbitrary environments. Keywords: Tiling robotics | Cleaning and maintenance | Inspection | Path planing | Reinforcement learning |
مقاله انگلیسی |
5 |
Integration of Big Data analytics embedded smart city architecture with RESTful web of things for efficient service provision and energy management
ادغام تجزیه و تحلیل داده های بزرگ جاسازی شده معماری شهر هوشمند با وب سایت RESTful برای ارائه خدمات کارآمد و مدیریت انرژی-2020 Emergence of smart things has revolutionized the conventional internet into a connected network of
things, maturing the concept of Internet of Things (IoT). With the evolution of IoT, many attempts were
made to realize the notion of smart cities. However, demands for processing enormous amount of data
and platform incompatibilities of connected smart things hindered the actual implementation of smart
cities. Keeping it in view, we proposed a Big Data analytics embedded smart city architecture, which
is further integrated with the web via a smart gateway. Integration with the web provides a universal
communication platform to overcome the platform incompatibilities of smart things. We introduced Big
Data analytics to enhance data processing speed. Further, we evaluated authentic datasets to determine
the threshold values for intelligent decision-making and to present the performance improvement gained
in data processing. Finally, we presented a representational state transfer (RESTful) web of things (WoT)
integrated smart building architecture (smart home) to reveal the performance improvements of the
proposed smart city architecture in terms of network performance and energy management of smart
buildings. Keywords: Smart city | Big Data analytics | Smart home | Web of things | RESTful architecture |
مقاله انگلیسی |
6 |
A fuzzy decision system for money investment in stock markets based on fuzzy candlesticks pattern recognition
یک سیستم تصمیم گیری فازی برای سرمایه گذاری پول در بورس اوراق بهادار بر اساس تشخیص الگوی شمعدانهای فازی-2019 This article proposes a novel fuzzy recommendation system for stock market investors. This intelligent decision tool uses fuzzy Japanese candlesticks and includes the effect of currency devaluation on the forecasting. To do so, first the next market session is obtained by a new designed fuzzy forecasting trad- ing system. Then, it is compared to the one obtained by a non-parametric system based on the k-nearest neighbor technique. Finally, an amount of money to be invested is considered using a new capital man- agement fuzzy strategy. The results have been compared to an analogous fuzzy trading system that has the same all-or-nothing investment strategy with risk control, but where this capitalization is not in- cluded. Both intelligent decision systems have been applied to two very different stock markets, the American Nasdaq100 and the Spanish Ibex35 markets, using the Buy and Hold investment strategy as benchmark. Results prove that the proposed fuzzy system with capitalization is profitable and presents high stability, and could be a good support system for investors. Keywords: Japanese candlestick | Fuzzy trading | Stock market forecasting | Capital management | Investment strategy | Recommendation system |
مقاله انگلیسی |
7 |
Intelligent decisions to stop or mitigate lost circulation based on machine learning
تصمیمات هوشمند برای متوقف کردن یا کاهش گردش خون از دست رفته بر اساس یادگیری ماشین-2019 Lost circulation is one of the frequent challenges encountered during the drilling of oil and gas wells. It is
detrimental because it can not only increase non-productive time and operational cost but also lead to
other safety hazards such as wellbore instability, pipe sticking, and blow out. However, selecting the
most effective treatment may still be regarded as an ill-structured issue since it does not have a unique
solution. Therefore, the objective of this study is to develop an expert system that can screen drilling
operation parameters and drilling fluid characteristics required to diagnose the lost circulation problem
correctly and suggest the most appropriate solution for the issue at hand.
In the first step, field datasets were collected from 385 wells drilled in Southern Iraq from different
fields. Then, fscaret package in R environment was applied to detect the importance and ranking of the
input parameters that affect the lost circulation solution. The new models were developed to predict the
lost circulation solution for vertical and deviated wells using artificial neural networks (ANNs) and
support vector machine (SVM). The using of the machine learning methods could assist the drilling
engineer to make an intelligent decision with proper corrective lost circulation treatment. Keywords: Lost circulation | Intelligent decision | Artificial neural networks | Support vector machine |
مقاله انگلیسی |
8 |
Fuzzy control system for variable rate irrigation using remote sensing
سیستم کنترل فازی برای آبیاری با سرعت متغیر با استفاده از سنجش از دور-2019 Variable rate irrigation (VRI) is the capacity to spatially vary the depth of water application in a field to handle different types of soils, crops, and other conditions. Precise management zones must be devel- oped to efficiently apply variable rate technologies. However, there is no universal method to determine management zones. Using speed control maps for the central pivot is one option. Thus, this study aims to develop an intelligent fuzzy inference system based on precision irrigation knowledge, i.e., a system that can create prescriptive maps to control the rotation speed of the central pivot. Satellite images are used in this study because remote sensing offers quick measurements and easy access to information on crops for large irrigation areas. Based on the VRI-prescribed map created using the intelligent decision- making system, the pivot can increase or decrease its speed, reaching the desired depth of application in a certain irrigation zone. Therefore, considering the spatial variability in the crop has made the strategy of speed control more realistic than traditional methods for crop management. The intelligent irrigation system pointed out areas with lower leaf development, indicating that the pivot must reduce its speed, thus increasing the water layer applied to that area. The existence of well-divided zones could be ob- served; each zone provides a specific value for the speed that the pivot must develop for decreasing or increasing the application of the water layer to the crop area. Three quarters of the total crop area had spatial variations during water application. The set point built by the developed system pointed out zones with a decreased speed in the order of 50%. From the viewpoint of a traditional control, the relay from pivot percent timer should have been adjusted from 70% to 35% whenever the central pivot passed over that specific area. The proposed system obtained values of 37% and 47% to adjust the pivot percent timer. Therefore, it is possible to affirm that traditional control models used for central-pivot irrigators do not support the necessary precision to meet the demands of speed control determined by the developed VRI systems. Results indicate that data from the edaphoclimatic variables when well-fitted to the fuzzy logic can solve uncertainties and non-linearities of an irrigation system and establish a control model for high-precision irrigation. Keywords: Fuzzy control | Variable rate irrigation | Speed control | Remote sensing | Decision support system |
مقاله انگلیسی |
9 |
مدیریت ترافیک با استفاده از رگرسيون لجستيک به همراه منطق فازی
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 15 تراکم ترافیک یکی از مشکلات عمده در اکثر شهرهای سراسر جهان است و منجر به مشکلاتی مانند آلودگی، اتلاف وقت، ترافیک طولانی در جاده ها و حوادث می شود. بهبود زیرساخت های جاده، راه حل عملی برای حل مشکل نیست. در سناریو زندگی واقعی، مسیر کوتاهتر تا مقصد، منجر به جذب اکثریت مردم می شود و گاهی شرایط ترافیک را تشدید می¬کند. بنابراین، اطلاعات ترافیکی در لحظه برای تصمیم گیری هوشمندانه انتخاب مسیر حرکت ضروری است. علاوه بر این، سیستمی شامل فاکتور فاصله نسبت به مقصد با در نظر گرفتن وضعیت ترافیکی آن مسیر، به راه حل مشکل افزوده شد. پارامترهای خاصی نظیر فاصله، شرایط آب و هوایی، موقعیت جغرافیایی، روز هفته و زمان برای حل مشکل در نظر گرفته شد و راه حل هایی برای مشکلات پیدا شد. در این مقاله ترکیبی از رگرسيون لجستيک با منطق فازی مثل تصمیم گیری هوشمندان در انتخاب مسیر بهتر ارائه شد. این روش برای محاسبه احتمال هر مسیر، با در نظر گرفتن اطلاعات ترافیکی لحظه ای، فاصله و جاده استفاده شد و سپس برای تصمیم گیری بروی سناریوی نامطلوب استفاده گردید. روش پیشنهادی تعداد پارامترهایی مانند فاصله، شرایط آب و هوایی، موقعیت جاده، روز از هفته و زمان را در نظر می گیرد.
کلید واژه : رگرسيون لجستيک | مدیریت ترافیک | تراکم | منطق فازی | الگوریتم بهینه سازی | کنترل فازی |
مقاله ترجمه شده |
10 |
An enhanced framework for multimedia data: Green transmission and portrayal for smart traffic system
یک چارچوب پیشرفته برای داده های چند رسانه ای: انتقال و تصویر سبز برای سیستم ترافیک هوشمند-2018 The object tracking in video surveillance for intelligent traffic handling in smart cities re
quires an enormous amount of data called big data to be transmitted over the network
using the Internet of Things. Manual monitoring and surveillance are impossible because
traditional computer vision technologies are no more useful for massive processing and
intelligent decision making. In this paper, a framework is proposed which enables both on
spot data processing and intelligent decision making by using cloud computing. The de
veloped application is a trained on Artificial Neural Network, which can handle different
traffic techniques with congested traffic scenario and priorities traffic such as ambulance
handling. The Message Queue Telemetry Transport protocol is used for green transmission
with mobile access to traffic data. The results analyzed with thirty videos processed data
which handle real-time data prioritization for the people for smart surveillance to fastest
route and enhance the intelligent data transmission.
Keywords: Internet of thing ، Big data ، Cloud computing ، Green transmission ، Artificial Neural Network ، Object tracking |
مقاله انگلیسی |