Song 7512


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  • Good afternoon. My name is Ji-Young. I am a second year of PhD student at the Martin Centre. I would like to thank you for giving me a chance to present my study “Environmental implications of campus buildings equipped with wireless internet”. / Before going through all these, I would like to talk about briefly what I am doing now at the Martin Centre.- My main research question is that “What environmental implications could buildings have if people’s lifestyle is changed due to ICT, so that they use buildings differently?” Now I am trying to develop a theoretical model which will tell us environmental impact of building with behavioural change due to ICT. This survey was a starting point as a pilot study for current research.
  • Song 7512

    1. 1. T he Impact of ICT on Space Use and Environmental Issues Ji Young Song PhD Student The Martin Centre for Architectural and Urban Studies Department of Architecture, University of Cambridge
    2. 2. CONTENTS <ul><li>Introduction </li></ul><ul><ul><li>Background to the study </li></ul></ul><ul><ul><li>Objective of the study </li></ul></ul><ul><li>Behavioural factor in building use </li></ul><ul><li>A model </li></ul><ul><ul><li>Conceptual framework </li></ul></ul><ul><ul><li>Computational model </li></ul></ul><ul><li>A plan for the further study </li></ul><ul><li>Conclusions </li></ul>
    3. 3. <ul><li>Introduction </li></ul><ul><ul><li>Background to the study </li></ul></ul><ul><ul><li>Objective of the study </li></ul></ul><ul><li>Behavioural factor in building use </li></ul><ul><li>A model </li></ul><ul><ul><li>Conceptual framework </li></ul></ul><ul><ul><li>Computational model </li></ul></ul><ul><li>A plan for the further study </li></ul><ul><li>Conclusions </li></ul>
    4. 4. Common Room, St. Edmund’s College, Cambeidge 29 Jan 2008, 9.00pm
    5. 5. Reading Room, St. Edmund’s College, Cambridge 29 Jan 2008, 9.20pm
    6. 6. University Centre, Cambridge Mill Lane Library, Cambridge
    7. 7. Energy use in buildings <ul><li>According to UK national statistics (2006), the building sector (42%) is a major energy consumer with transport (34%). </li></ul>(
    8. 8. Objective of the study <ul><li>The purpose of this study is </li></ul><ul><ul><li>firstly, to investigate the effect of ICT on the choice of working place by developing an agent-based model, </li></ul></ul><ul><ul><li>secondly, to examine environmental impacts such as energy consumption of buildings resulting from transformed space use patterns. </li></ul></ul>
    9. 9. <ul><li>Introduction </li></ul><ul><ul><li>Background to the study </li></ul></ul><ul><ul><li>Objective of the study </li></ul></ul><ul><li>Behavioural factor in building use </li></ul><ul><li>A model </li></ul><ul><ul><li>Conceptual framework </li></ul></ul><ul><ul><li>Computational model </li></ul></ul><ul><li>A plan for the further study </li></ul><ul><li>Conclusions </li></ul>
    10. 10. Behavioural Factor in Building Use Building Occupants Systems Energy Use x 2.5 from modelling x 2 from modelling x 2 by deduction x 10 from monitoring
    11. 11. Modelling Human Behaviour <ul><li>Since 1990s, computer simulations have been actively used for behavioural studies in social science. </li></ul><ul><li>To model complex human behaviour, we need a suitable framework which can accommodate their multifaceted interactions between environment and individual and also between individuals, and can simulate them in various different conditions. </li></ul><ul><li>An agent-based modelling method allows us to experiment with multi-agents in social world and contain the interactions between them. </li></ul><ul><ul><li>Agent-based models useful especially when applied to human-related system which its theory has not well established yet. </li></ul></ul>
    12. 12. Modelling Human Behaviour <ul><li>Simulation methods used in social science (Gilbert and Troitzsch, 1999) </li></ul>
    13. 13. <ul><li>Introduction </li></ul><ul><ul><li>Background to the study </li></ul></ul><ul><ul><li>Objective of the study </li></ul></ul><ul><li>Behavioural factor in building use </li></ul><ul><li>A model </li></ul><ul><ul><li>Conceptual framework </li></ul></ul><ul><ul><li>Computational model </li></ul></ul><ul><li>A plan for the further study </li></ul><ul><li>Conclusions </li></ul>
    14. 14. Conceptual framework of the model <ul><li>In order to answer two main questions; </li></ul><ul><ul><li>first, how ICT affordance of space changes individual’s decision-making for space use </li></ul></ul><ul><ul><li>second, how different environmental impacts will result from transformed space use pattern </li></ul></ul><ul><li>we develop an agent-based model providing the simulation environment. </li></ul><ul><ul><li>For this, we first develop a simple rule of decision-making for working place. </li></ul></ul><ul><ul><li>To begin with, we use the rule by Fawcett and Song (2008) and expand it including ICT and distance factors, and interactions between individuals. </li></ul></ul>
    15. 15. Decision-making <ul><li>Each individual ( i ) is supposed to be able to choose a number of alternative spaces ( j ) – employer’s private workspace, employer’s touchdown workspace, home work and non-work. </li></ul><ul><li>Each choice has the attractiveness ( A ij ) scores consisting of performance ( P ij ) and convenience ( C ij ) scores. </li></ul><ul><li>If we assume that there are five time-periods in a day – dawn, morning, afternoon, evening, night – and five days in a week, making 25 time-periods. Each individual ( i ) has a work life index ( W i ) which comprises 25 values, one for each of the 25 time-periods, W i = { w it , t = 1, …, 25}. </li></ul><ul><li>The work-life index for each time period is a value between 0 and 1 and expresses the relative weight of performance (work) compared to convenience (life) – high values mean that work is given priority. </li></ul><ul><li>A weighted average attractiveness score ( A ijt ) is calculated for individual ( i ), for each alternative ( j ) and each time-period ( t ). This is done by combining the work and life scores, using the ratio specified by the employee’s work-life index: A ijt = P ij w it + C ij (1 - w it ) </li></ul>
    16. 16. Decision-making <ul><li>We here consider distance and ICT factors which affect decision-making for workplace. </li></ul><ul><li>A distance factor ( d ij ) tells the distance from home to workplace, which bigger distance factor decrease attractiveness of a space for working. </li></ul><ul><li>An ICT level ( I j ) describes supporting capability for ICT use of a space. Higher ICT level indicates higher ICT affordance of a space. </li></ul><ul><li>The probability that an individual ( i ) chooses a space ( j ) for working at a certain time ( K ijt ) can be expressed in the equation; </li></ul><ul><li>Then, the probability ( K ijt ) is intervened by ICT dependency ( i c ) representing the degree of dependency on ICT of an agent and the interaction factor ( i m ) representing the need of communication between agents. </li></ul><ul><li>The interaction factor will be defined as a Markov chain matrix. </li></ul>
    17. 17. Environmental Impact <ul><li>We estimate the energy consumption for buildings and transport resulting from changed space use pattern. </li></ul><ul><li>Let us assume that the total energy consumption ( E t ) consists of the energy use for building of employer’s premises ( E o ) and for individual’s home ( E h ) and transportation for commuting ( E c ). </li></ul><ul><li>E t = E o + E h + E c </li></ul><ul><li>The transformed space use pattern may lead to different total energy consumption ( E t ) resulting from different energy use for office building ( E o ), home ( E h ) and commuting ( E c ). </li></ul>
    18. 18. Computational model <ul><li>The environment </li></ul><ul><ul><li>Physical attractiveness ( A j ) is a measurement of the physical quality for working and ICT level ( I j ) indicates a degree of the supporting capability of ICT use. </li></ul></ul><ul><ul><li>Distance ( d ij ) represents Euclidean distance between home and an alternative workplace where individual choose. </li></ul></ul><ul><ul><li>There are three types of environment – traditional, intermediate and modern environment. </li></ul></ul><ul><ul><li>Each space has physical attractiveness score ( A j ) i.e., performance and convenience scores, ICT scores ( I j ), and x-, y-coordination. </li></ul></ul><ul><ul><ul><li>Physical attractiveness ( A j ) of each space ( j , j = { 0, 1, …, J }), </li></ul></ul></ul><ul><ul><ul><li>ICT level ( I j ) of each space ( j ), </li></ul></ul></ul><ul><ul><ul><li>Distance ( d ij ) between individual’s home ( i) and chosen space ( j ). </li></ul></ul></ul>
    19. 19. Computational model <ul><li>The agents </li></ul><ul><ul><li>Agents are randomly located at the grid in the Netlogo interface environment. </li></ul></ul><ul><ul><li>The total number of agents is ten and this will be extended later. </li></ul></ul><ul><ul><li>There are two agent types – traditional and flexible employees. </li></ul></ul><ul><ul><li>Each agent has following three kinds of attributes; </li></ul></ul><ul><ul><ul><li>Work preference ( i w ) at each time-period, </li></ul></ul></ul><ul><ul><ul><li>ICT dependency ( i c ), </li></ul></ul></ul><ul><ul><ul><li>Communication needs ( i m ). </li></ul></ul></ul>
    20. 20. Computational model <ul><li>The rule </li></ul><ul><ul><li>Each agent behaves based on the rule (equation (1)) that describes his/her decision. </li></ul></ul><ul><ul><li>Decision is dynamic which has five different choices in a day. </li></ul></ul><ul><ul><li>Decision is interfered by ICT dependency ( i c ) and the interaction between agents such as communication needs ( i m ). </li></ul></ul>
    21. 21. <ul><li>Environment-Agent types </li></ul>Type 6 (Mod-Flex) Type 3 (Mod-Trad) Modern Environment Type 5 (Inter-Flex) Type 4 (Trad-Flex) Flexible Agents Type 2 (Inter-Trad) Type 1 (Trad-Trad) Traditional Agents Intermediate Environment Traditional Environment
    22. 22. A Prototype Model
    23. 23. A Prototype Model
    24. 24. A Prototype Model
    25. 25. <ul><li>Introduction </li></ul><ul><ul><li>Background to the study </li></ul></ul><ul><ul><li>Objective of the study </li></ul></ul><ul><li>Behavioural factor in building use </li></ul><ul><li>A model </li></ul><ul><ul><li>Conceptual framework </li></ul></ul><ul><ul><li>Computational model </li></ul></ul><ul><li>A plan for the further study </li></ul><ul><li>Conclusions </li></ul>
    26. 26. Plan for the Further Study <ul><li>The development of the agent-based model for space use is currently on-going and will include following points soon. </li></ul><ul><li>To investigate the interaction between agents we will develop an interaction rule represented by a Markov Chain Matrix. </li></ul><ul><li>The number of agent and types will be expanded and statistically adjusted considering the survey results. </li></ul><ul><li>For the calculation of energy consumption of buildings we use benchmarking data and typical office building typologies for UK offices to compare energy consumption in different scenarios with different occupancy pattern. </li></ul>
    27. 27. Plan for the Further Study <ul><li>For the verification of the model, we will undertake a number of repeated simulations with initial conditions but with different random numbers. </li></ul><ul><li>It is desirable to conduct sensitivity analysis to estimate whether the variation in the assumptions of the model produces differences in the output. </li></ul><ul><li>For the validation, questionnaire survey will be conducted to two organisations with approximately 100 employees and thereafter output from the simulation will be statistically compared with survey results. </li></ul><ul><li>The model is expected to achieve its robustness and plausibility through this process. </li></ul>
    28. 28. <ul><li>Introduction </li></ul><ul><ul><li>Background to the study </li></ul></ul><ul><ul><li>Objective of the study </li></ul></ul><ul><li>Behavioural factor in building use </li></ul><ul><li>A model </li></ul><ul><ul><li>Conceptual framework </li></ul></ul><ul><ul><li>Computational model </li></ul></ul><ul><li>A plan for the further study </li></ul><ul><li>Conclusions </li></ul>
    29. 29. Conclusions & Discussion <ul><li>It is believed that behavioural factors in building energy performance has a substantial implication however, up to now we have not had much knowledge on how people use building differently regarding ICT and thus how different environmental impact there will be resulting from changed behaviour (if any). </li></ul><ul><li>Through the study, we expect to have a better understanding on how ICT affect people’s behaviour with regard to space use in buildings. </li></ul><ul><li>In particular, the agent-based model is anticipated to provide an effective tool in order to see space use patterns in changing environment by allowing us to experiment various future conditions, which is difficult to try it out in reality. </li></ul><ul><li>In practice, this study could give architects, building managers and urban planners a foresight how to plan and design toward sustainable built environment accommodating people’s needs which are changing rapidly with technology. </li></ul>
    30. 30. <ul><li>“ We will characterize cities of the twenty-first century as systems of interlinked, interacting, silicon- and software-saturated smart, attentive, and responsive places. We will encounter them at the scales of clothing, rooms, buildings, campuses and neighbourhood, metropolitan regions, and global infrastructure (Mitchell, 1999).” </li></ul>Ji Young Song (e-mail: