Low carbon non-domestic building design process. An ethnographic comparison of design in Wales and England

2014 ◽  
Vol 32 (2) ◽  
pp. 140-157 ◽  
Author(s):  
Gabriela Zapata-Lancaster
Keyword(s):  
Real Time ◽  
Design Process ◽  
Carbon Emissions ◽  
Energy Performance ◽  
Policy Agenda ◽  
Energy Regulation ◽  
Design Teams ◽  
England And Wales ◽  
Content Type ◽  
The Real

Purpose – The UK aims to reduce the carbon emissions in the building sector so as to achieve nearly zero-carbon new buildings by 2020. In 2010, a 25 per cent reduction of carbon emissions was mandated in England and Wales. The aim of this paper is to reveal how the design teams were coping with the energy regulation changes in 2010 in England and Wales. Design/methodology/approach – An ethnographic methodology was selected to investigate in-depth the real-time design process in four architecture practices. The study was analysed in detail and compared the design process of six non-domestic buildings in England and Wales. The data collection methods included interviews, non-participant observation and document analysis and were conducted for a period of 12-21 months per case study. Findings – The field findings suggest the disconnections between the project driver and the policy agenda and reveal what the design teams do to embed energy performance in routine project design. Research limitations/implications – Due to the in-depth nature of the data, no claims for generalisation or representativeness are made. However, the detailed analysis of the real-time design process reveals the designers’ enactment of the policy agenda, which is in essence a timeless phenomenon about policy intervention and performance-based regulations. Originality/value – The designers’ enactment of and responses to the policy changes become an analytical tool to infer lessons that can be learned from the process and lead to the achievement of expected carbon reductions and the success of the policy intentions.

The future of sustainable real estate investments in a post-COVID-19 world

2020 ◽  
Vol 13 (3) ◽  
pp. 455-460 ◽  
Author(s):  
John Pike
Keyword(s):  
Real Estate ◽  
Energy Performance ◽  
Green Energy ◽  
Mandatory Reporting ◽  
Energy Regulation ◽  
Real Estate Investment ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Personal Viewpoint

Purpose The purpose of this paper is to suggest that property investors should engage with governments to influence outcomes. Global collaboration is required from the real estate investment community, working closely with governments and legislators, to provide a clear road map to zero carbon emissions. Covid-19 has shown how quickly governments around the world can react with draconian responses, including widespread lockdowns, when faced with an existential threat. What bigger existential threat is there than climate change? Design/methodology/approach Personal viewpoint from general research. Findings Three pillars of likely government and legislative interventions are identified; namely, increased and enhanced energy regulation and carbon pricing to force a rapid switch to green energy sources for buildings; an enhanced role for Energy Performance Certificates, standardised methodologies and strict enforcement; and mandatory reporting of financial and physical climate risks based on the Financial Stability Board’s Task Force on Climate-related Financial Disclosures. It is suggested that property investors should now engage with governments to influence outcomes. Originality/value Personal viewpoint to encourage greater involvement of the real estate investment community in governmental and regulatory decision making.

Hardware-in-the-loop simulation for real-time software verification of an autonomous underwater robot

2016 ◽  
Vol 4 (3) ◽  
pp. 163-181
Author(s):  
Pouria Sarhadi ◽  
Reza Nad Ali Niachari ◽  
Morteza Pouyan Rad ◽  
Javad Enayati
Keyword(s):  
Software Engineering ◽  
Real Time ◽  
Autonomous Systems ◽  
Systems Design ◽  
Development Stage ◽  
Underwater Robot ◽  
Real Time System ◽  
Content Type ◽  
The Real ◽  
Time Performance

Purpose The purpose of this paper is to propose a software engineering procedure for real-time software development and verification of an autonomous underwater robotic system. High performance and robust software are one of the requirements of autonomous systems design. A simple error in the software can easily lead to a catastrophic failure in a complex system. Then, a systematic procedure is presented for this purpose. Design/methodology/approach This paper utilizes software engineering tools and hardware-inthe-loop (HIL) simulations for real-time system design of an autonomous underwater robot. Findings In this paper, the architecture of the system is extracted. Then, using software engineering techniques a suitable structure for control software is presented. Considering the desirable targets of the robot, suitable algorithms and functions are developed. After the development stage, proving the real-time performance of the software is disclosed. Originality/value A suitable approach for analyzing the real-time performance is presented. This approach is implemented using HIL simulations. The developed structure is applicable to other autonomous systems.

Customer behavior analysis using real-time data processing

2019 ◽  
Vol 31 (1) ◽  
pp. 265-290 ◽  
Author(s):  
Ganjar Alfian ◽  
Muhammad Fazal Ijaz ◽  
Muhammad Syafrudin ◽  
M. Alex Syaekhoni ◽  
Norma Latif Fitriyani ◽  
...  
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Association Rule ◽  
Customer Behavior ◽  
Time Data ◽  
Content Type ◽  
The Real ◽  
Real Time Data ◽  
Real Time Data Processing ◽  
Big Data Technology

PurposeThe purpose of this paper is to propose customer behavior analysis based on real-time data processing and association rule for digital signage-based online store (DSOS). The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is utilized to handle the vast amount of customer behavior data.Design/methodology/approachIn order to extract customer behavior patterns, customers’ browsing history and transactional data from digital signage (DS) could be used as the input for decision making. First, the authors developed a DSOS and installed it in different locations, so that customers could have the experience of browsing and buying a product. Second, the real-time data processing system gathered customers’ browsing history and transaction data as it occurred. In addition, the authors utilized the association rule to extract useful information from customer behavior, so it may be used by the managers to efficiently enhance the service quality.FindingsFirst, as the number of customers and DS increases, the proposed system was capable of processing a gigantic amount of input data conveniently. Second, the data set showed that as the number of visit and shopping duration increases, the chance of products being purchased also increased. Third, by combining purchasing and browsing data from customers, the association rules from the frequent transaction pattern were achieved. Thus, the products will have a high possibility to be purchased if they are used as recommendations.Research limitations/implicationsThis research empirically supports the theory of association rule that frequent patterns, correlations or causal relationship found in various kinds of databases. The scope of the present study is limited to DSOS, although the findings can be interpreted and generalized in a global business scenario.Practical implicationsThe proposed system is expected to help management in taking decisions such as improving the layout of the DS and providing better product suggestions to the customer.Social implicationsThe proposed system may be utilized to promote green products to the customer, having a positive impact on sustainability.Originality/valueThe key novelty of the present study lies in system development based on big data technology to handle the enormous amounts of data as well as analyzing the customer behavior in real time in the DSOS. The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is used to handle the vast amount of customer behavior data. In addition, the present study proposed association rule to extract useful information from customer behavior. These results can be used for promotion as well as relevant product recommendations to DSOS customers. Besides in today’s changing retail environment, analyzing the customer behavior in real time in DSOS helps to attract and retain customers more efficiently and effectively, and retailers can get a competitive advantage over their competitors.

Cassandra-based data repository design for food supply chain traceability

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sandeep Kumar Singh ◽  
Mamata Jenamani
Keyword(s):  
Supply Chain ◽  
Real Time ◽  
Radio Frequency Identification ◽  
Query Language ◽  
Data Repository ◽  
Time Data ◽  
Content Type ◽  
The Real ◽  
Traceability System ◽  
Real Time Data

Purpose The purpose of this paper is to design a supply chain database schema for Cassandra to store real-time data generated by Radio Frequency IDentification technology in a traceability system. Design/methodology/approach The real-time data generated in such traceability systems are of high frequency and volume, making it difficult to handle by traditional relational database technologies. To overcome this difficulty, a NoSQL database repository based on Casandra is proposed. The efficacy of the proposed schema is compared with two such databases, document-based MongoDB and column family-based Cassandra, which are suitable for storing traceability data. Findings The proposed Cassandra-based data repository outperforms the traditional Structured Query Language-based and MongoDB system from the literature in terms of concurrent reading, and works at par with respect to writing and updating of tracing queries. Originality/value The proposed schema is able to store the real-time data generated in a supply chain with low latency. To test the performance of the Cassandra-based data repository, a test-bed is designed in the lab and supply chain operations of Indian Public Distribution System are simulated to generate data.

Informing sustainable building design

2019 ◽  
Vol 13 (1) ◽  
pp. 194-203 ◽  
Author(s):  
Mathilde Landgren ◽  
Signe Skovmand Jakobsen ◽  
Birthe Wohlenberg ◽  
Lotte Bjerregaard Jensen
Keyword(s):  
Built Environment ◽  
Case Studies ◽  
Design Process ◽  
Integrated Design ◽  
Building Design ◽  
Design Teams ◽  
Design Decisions ◽  
Sustainable Building ◽  
Content Type ◽  
Interdisciplinary Design

Purpose In recent decades there has been a focus on reducing the overall emissions from the built environment, which increases the complexity of the building design process. More specialized knowledge, a greater common understanding and more cooperation between the stakeholders are required. Interdisciplinary design teams need simple and intuitive means of communication. Architects and engineers are starting to increase their focus on improving interdisciplinary communication, but it is often unclear how to do so. The purpose of this paper is to define the impact of visually communicating engineering knowledge to architects in an interdisciplinary design team and to define how quantifying architectural design decisions have an impact during the early phases of sustainable building design. Design/methodology/approach This work is based on a study of extensive project materials consisting of presentations, reports, simulation results and case studies. The material is made available by one of the largest European Engineering Consultancies and by a large architectural office in the field of sustainable architecture in Denmark. The project material is used for mapping communication concepts from practice. Findings It is demonstrated that visual communication by engineers increases the level of technical knowledge in the design decisions made by architects. This is essential in order to reach the goal of designing buildings with low environmental impact. Conversely, quantification of architectural quality improved the engineer’s acceptance of the architects’ proposals. Originality/value This paper produces new knowledge through the case study processes performed. The main points are presented as clearly as possible; however, it should be stressed that it is only the top of the iceberg. In all, 17 extensive case studies design processes were performed with various design teams by the 3 authors of the paper Mathilde, Birthe and Signe. The companies that provided the framework for the cases are leading in Europe within sustainability in the built environment, and in the case of Sweco also in regards to size (number of employees). Data are thus first hand and developed by the researchers and authors of this paper, with explicit consent from the industry partners involved as well as assoc. Professor Lotte B. Jensen Technical University of Denmark (DTU). This material is in the DTU servers and is in the PhD dissertation by Mathilde Landgren (successful defence was in January 2019). The observations and reflection is presented in selected significant case examples. The methods are descriped in detail, and if further information on method is required a more in depth description is found in Mathilde Landgrens PhD Dissertation. There is a lack in existing literature of the effect of visualisation in interdisciplinary design teams and though the literature (e.g. guidelines) of integrated design is extensive, there is not much published on this essential part of an integrated design process.

scholarly journals Development of a user-friendly regression model to evaluate carbon emissions of office buildings design in the subtropics

Facilities ◽  
2019 ◽  
Vol 37 (11/12) ◽  
pp. 860-878
Author(s):  
Pan Lee ◽  
Edwin H.W. Chan ◽  
Queena K. Qian ◽  
Patrick T.I. Lam
Keyword(s):  
Regression Model ◽  
Carbon Emissions ◽  
Building Design ◽  
Office Buildings ◽  
Design Parameters ◽  
Design Teams ◽  
Content Type ◽  
High Rise ◽  
User Friendly ◽  
Influential Parameters

Purpose Design teams have difficulties in assessing building carbon emissions at an early stage, as most building energy simulation tools require a detailed input of building design for estimation. The purpose of this paper is to develop a user-friendly regression model to estimate carbon emissions of the preliminary design of office buildings in the subtropics by way of example. Five sets of building design parameters, including building configuration, building envelope, design space conditions, building system configuration and occupant behaviour, are considered in this study. Design/methodology/approach Both EnergyPlus and Monte Carlo simulation were used to predict carbon emissions for different combinations of the design parameters. A total of 100,000 simulations were conducted to ensure a full range of simulation results. Based on the simulation results, a regression model was developed to estimate carbon emissions of office buildings based on preliminary design information. Findings The results show that occupant density, annual mean occupancy rate, equipment load, lighting load and chiller coefficient of performance are the top five influential parameters affecting building carbon emissions under the subtropics. Besides, the design parameters of ten office buildings were input into this user-friendly regression model for validation. The results show that the ranking of its simulated carbon emissions for these ten buildings is consistent with the original carbon emissions ranking. Practical implications With the use of this developed regression model, design teams can not only have a simple and quick estimation of carbon emissions based on the building design information at the conceptual stage but also explore design options by understanding the level of reduction in carbon emissions if a certain building design parameter is changed. The study also provides recommendations on building design to reduce carbon emissions of office buildings. Originality/value Limited research has been conducted to date to investigate how the change of building design affects carbon emissions in the subtropics where four distinct seasons lead to significant variations of outdoor temperature and relative humidity. Previous research also did not emphasise on the impact of high-rise office building designs (e.g. small building footprint, high window-to-wall ratio) on carbon emissions. This paper adds value by identifying the influential parameters affecting carbon emissions for a high-rise office building design and allows a handy estimate of building carbon emissions under the subtropical conditions. The same approach may be used for other meteorological conditions.

scholarly journals Using BIM capabilities to improve existing building energy modelling practices

2017 ◽  
Vol 24 (2) ◽  
pp. 190-208 ◽  
Author(s):  
Tristan Gerrish ◽  
Kirti Ruikar ◽  
Malcolm Cook ◽  
Mark Johnson ◽  
Mark Phillip
Keyword(s):  
Design Process ◽  
Building Energy ◽  
Energy Performance ◽  
Information Storage ◽  
Successful Implementation ◽  
Design Development ◽  
Content Type ◽  
Design Procedures ◽  
Energy Modelling ◽  
Building Project

Purpose The purpose of this paper is to present a review of the implications building information modelling (BIM) is having on the building energy modelling (BEM) and design of buildings. It addresses the issues surrounding exchange of information throughout the design process, and where BIM may be useful in contributing to effective design progression and information availability. Design/methodology/approach Through review of current design procedures and examination of the concurrency between architectural and thermophysical design modelling, a procedure for information generation relevant to design stakeholders is created, and applied to a high-performance building project currently under development. Findings The extents of information key to the successful design of a buildings energy performance in relation to its architectural objectives are given, with indication of the level of development required at each stage of the design process. Practical implications BIM offers an extensible medium for parametric information storage, and its implementation in design development offers the capability to include BEM parameter-integrated construction information. The extent of information required for accurate BEM at stages of a building’s design is key to understanding how best to record performance information in a BIM environment. Originality/value This paper contributes to the discussion around the integration of concurrent design procedures and a common data environment. It presents a framework for the creation and dissemination of information during design, exemplifies this on a real building project and evaluates the barriers experienced in successful implementation.

scholarly journals Modeling of an IoT-enabled supply chain for perishable food with two-echelon supply hubs

2017 ◽  
Vol 117 (9) ◽  
pp. 1890-1905 ◽  
Author(s):  
Yingfeng Zhang ◽  
Lin Zhao ◽  
Cheng Qian
Keyword(s):  
Supply Chain ◽  
Real Time ◽  
Food Supply ◽  
Time Data ◽  
Food Supply Chain ◽  
Content Type ◽  
The Real ◽  
Industrial Parks ◽  
Iot Devices ◽  
Real Time Information

Purpose The huge demand for fresh goods has stimulated lots of research on the perishable food supply chain. The characteristics of perishable food and the cross-regional transportation have brought many challenges to the operation models of perishable food supply chain. The purpose of this paper is to address these challenges based on the real-time data acquired by the Internet of Things (IoT) devices. Design/methodology/approach IoT and the modeling of the Supply Hub in Industrial Parks were adopted in the perishable food supply chain. Findings A conceptual model was established for the IoT-enabled perishable food supply chain with two-echelon supply hubs. The performance of supply chain has improved when implementing the proposed model, as is demonstrated by a case study. Originality/value By our model, the supply hubs which act as the dominators of the supply chain can respond to the real-time information captured from the operation processes of an IoT-enabled supply chain, thus to provide public warehousing and logistic services.

Real-time optimization using gradient adaptive selection and classification from infrared sensors measurement for esterification oleic acid with glycerol

2017 ◽  
Vol 10 (2) ◽  
pp. 130-144 ◽  
Author(s):  
Iwan Aang Soenandi ◽  
Taufik Djatna ◽  
Ani Suryani ◽  
Irzaman Irzaman
Keyword(s):  
Real Time ◽  
Sensor Data ◽  
Necessary Condition ◽  
Support Vector ◽  
Adaptive Selection ◽  
Content Type ◽  
The Real ◽  
Time Optimization ◽  
Starting Point ◽  
Real Time Optimization

Purpose The production of glycerol derivatives by the esterification process is subject to many constraints related to the yield of the production target and the lack of process efficiency. An accurate monitoring and controlling of the process can improve production yield and efficiency. The purpose of this paper is to propose a real-time optimization (RTO) using gradient adaptive selection and classification from infrared sensor measurement to cover various disturbances and uncertainties in the reactor. Design/methodology/approach The integration of the esterification process optimization using self-optimization (SO) was developed with classification process was combined with necessary condition optimum (NCO) as gradient adaptive selection, supported with laboratory scaled medium wavelength infrared (mid-IR) sensors, and measured the proposed optimization system indicator in the batch process. Business Process Modeling and Notation (BPMN 2.0) was built to describe the tasks of SO workflow in collaboration with NCO as an abstraction for the conceptual phase. Next, Stateflow modeling was deployed to simulate the three states of gradient-based adaptive control combined with support vector machine (SVM) classification and Arduino microcontroller for implementation. Findings This new method shows that the real-time optimization responsiveness of control increased product yield up to 13 percent, lower error measurement with percentage error 1.11 percent, reduced the process duration up to 22 minutes, with an effective range of stirrer rotation set between 300 and 400 rpm and final temperature between 200 and 210°C which was more efficient, as it consumed less energy. Research limitations/implications In this research the authors just have an experiment for the esterification process using glycerol, but as a development concept of RTO, it would be possible to apply for another chemical reaction or system. Practical implications This research introduces new development of an RTO approach to optimal control and as such marks the starting point for more research of its properties. As the methodology is generic, it can be applied to different optimization problems for a batch system in chemical industries. Originality/value The paper presented is original as it presents the first application of adaptive selection based on the gradient value of mid-IR sensor data, applied to the real-time determining control state by classification with the SVM algorithm for esterification process control to increase the efficiency.

Understanding the effects of environmental factors on building energy efficiency designs and credits

2017 ◽  
Vol 15 (03) ◽  
pp. 270-285 ◽  
Author(s):  
Jonghoon Kim ◽  
Jin-Young Hyun ◽  
Wai K. Chong ◽  
Samuel Ariaratnam
Keyword(s):  
Energy Consumption ◽  
Environmental Factors ◽  
Real Time ◽  
Building Energy ◽  
Energy Performance ◽  
Building Energy Efficiency ◽  
Time Data ◽  
Chi Square ◽  
Content Type ◽  
Real Time Data

Purpose The purpose of this study was to explore the relationship between environmental factors and building energy consumption of three Leadership in Energy and Environmental Design (LEED)-certified buildings at the Arizona State University, by establishing the relationships of the outside atmospheric temperature and the energy consumed in the building using real-time data generated from different sources. Design/methodology/approach K-means clustering analysis is used to calibrate and eliminate unwanted influences or factors from a set of building consumption real-time data. For further statistical analysis, the chi-square is used to verify if the results are ample to prove the findings. Findings Few studies have addressed building energy consumption real-time data versus LEED Energy and Atmosphere (EA) credits with the data mining technique (k-means clustering) on most of building performance analyses. This study highlighted that the calibrating energy data are a better approach to analyze energy use in buildings and that there is a relationship between LEED credits’ (EA) Optimize Energy Performance scores and building energy efficiency. However, the energy consumption data alone do not yield useful results to establish the cause and effect relationships. Originality/value Although there are several previous research studies regarding LEED building energy performance, this research study focused on the LEED building energy performance versus LEED EA credits versus environmental factors using real-time building energy data and various statistical methods (e.g. K-means clustering and chi-square). The findings provide researchers, engineers and architects with valuable references for building energy analysis methods and supplements in LEED standards.

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