| 研究生: |
陳柏均 Chen, Po-Chun |
|---|---|
| 論文名稱: |
綠色信用:永續生活的行動能源感知服務 Green Credit: Mobile Energy Awareness for Sustainable Living |
| 指導教授: |
鄭泰昇
Jeng, Tay-Sheng 劉世南 Liou, Shyh-Nan |
| 學位類別: |
碩士 Master |
| 系所名稱: |
規劃與設計學院 - 創意產業設計研究所 Institute of Creative Industries Design |
| 論文出版年: | 2011 |
| 畢業學年度: | 99 |
| 語文別: | 英文 |
| 論文頁數: | 114 |
| 中文關鍵詞: | 永續人機互動 、社群網路 、資訊視覺化 、能源感知 、永續生活 、說服科技 |
| 外文關鍵詞: | Sustainable Human-Computer Interaction, Social Network, Information Visualization, Energy Awareness, Sustainable Living, Persuasive Computing |
| 相關次數: | 點閱:110 下載:5 |
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永續生活已經成為世界的趨勢,透過減少能源的使用與提高能源使用效率是達成一個永續生活重要的因素。然而能源對於民眾是抽象的資訊、無法看見和觸及的,因此即使有意願減少能源使用卻常因缺乏資訊判斷做出節能的行動選擇。以台灣為例,2009年居家用電所佔的比例約為整體用電的21%,且仍在逐年增長。將能源使用狀態以視覺呈現並設計於增加察覺的感知工具將有助使用者作出節能的判斷與行為,永續人機互動即是針對此目的所產生。能源感知工具在近年來有許多面向的發展與研究,然而節省能源有其極限,必須降低使用者持續使用能源的動機,採取新的生活態度,改變日常生活耗能的行為,才能達到永續節能的目標。
因應以上永續節能的目標,本研究提出「綠色信用」的永續人機互動概念。綠色信用本身有兩個意涵:(1)一個可以呈現使用者節省碳排放或金錢的單位,(2)對於生活環境的承諾、責任與貢獻,也就是綠色智能。本研究試圖建立以社群互動與資訊視覺化的互動模式,藉由手機作為感知工具與平台,探討節能動機的產生與行為的改變,並且建立系統原型投入到真實生活中,透過實驗觀察、問卷及訪談參與者的過程來驗證綠色信用的運作概念,以符合最終目標:建構「綠色信用」- 以視覺化的人機互動達成永續生活的目標模式的永續人機互動。本研究的具體貢獻包括:(1) 提出建構於手機上的「綠色信用」永續人機互動概念,(2) 建構資料蒐集與運算的方式,視覺化室內與室外的永續行為,(3) 建構社群互動的模式,以社群的力量,促使耗能行為的改變,(4) 以生活場域實驗,評估參與者對於永續行為的感知與改變。
In the context of sustainability, reducing energy and enhancing energy efficiency are becoming the fundamental requirement to promote sustainable living. However, the energy is abstract, invisible and untouchable. The lack of energy consumption information becomes the barrier for users who are willing to save the energy. In Taiwan, the residential sector accounts for approximately 21% in 2009, and still increasing. Thus, developing energy information and personal awareness tools for supporting decision-making are needed. The Sustainable Human-Computer Interaction is a research fields that are emerging into HCI for this purpose. Currently, a number of energy awareness tools have been developed, but energy-saving threshold did not decrease users’ energy-saving motivation. However, fostering sustainable behavior is the key for promoting the balance between resource usage and environmental impact.
This thesis aims to propose a Sustainable Human-Computer Interaction concept – “Green Credit”. The Green Credit has two implications: 1) representation of the carbon emission or money been saved by users; 2) the commitment, responsibility and contribution to sustainable environment, which could also called as Ecological intelligence. The Green Credit concept uses an interaction method coupled with social interaction and information visualization. Mobile phones are used as an awareness tool and a platform for provoking Green Credit to explore the reasons of energy-saving motivation and behavior change. In addition, a system prototype has been implement in real-life environment and conduct experiment observation, questionnaire and focus group for validating the concept of Green Credit. The contribution of this research includes: 1) Green Credit - a Sustainable Human-Computer Interaction concept, 2) the method of data collection and computation, which can visualize the in-door and outdoor sustainable behavior, 3) persuasive computing to motivate the sustainable behavior, and 4) Living Labs experiment to evaluate participants’ sustainable awareness and changing behavior.
Bang, M., Torstensson, C., & Katzeff, C. (2006). The PowerHouse: A persuasive computer game designed to raise awareness of domestic energy consumption. Persuasive Technology, 3962, 123–132.
Bang, M., Gustafsson, A., & Katzeff, C. (2007). Promoting new patterns in household energy consumption with pervasive learning games. Proceedings of the 2nd international conference on Persuasive technology, 55–63.
Boyd, D.M. and Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship, Journal of Computer-Mediated Communication, 13, 11.
Common Wealth (2010). Green Consumer Behavior Survey http://english.cw.com.tw/article.do?action=show&id=12072&offset=0
Consolvo, S., & McDonald, D. (2009). Theory-driven design strategies for technologies that support behavior change in everyday life. In Proceedings of the 27th international conference on Human factors in computing systems
Chen, P. C., & Cheng, T. S. (2010). Livindex : Situational Energy Awareness for Sustainable Living. ArS, 1–10.
Deci, E.L., Ryan, R.M. (2000). Intrinsic and extrinsic motivations: classic definitions and new directions. Cont. Ed. Psyc., 25.
De Young, R. (1993). Changing behavior and making it stick: the conceptualization and management of conservation behavior. Environment and Behavior, 25(3), 485-505.
DiSalvo, C., Sengers, P., & Brynjarsdóttir, H. (2010). Navigating the terrain of sustainable HCI. interactions, 17(4). ACM Request Permissions.
DiSalvo, C., Sengers, P., & Brynjarsdóttir, H. (2010). Mapping the landscape of sustainable HCI. Proceedings of the 28th international conference on Human factors in computing systems, 1975–1984.
Ferebee, S. (2010). Successful Persuasive Technology for Behavior Reduction: Mapping to Fogg’s Gray Behavior Grid. Persuasive Technology, 70–81.
Fogg, B.J. (2009). A Behavior Model for Persuasive Design, Persuasive ’09.
Fogg, B.J. (2009). The behavior grid: 35 ways behavior can change. Proceedings of the 4th International Conference on Persuasive Technology, 1–5.
Fogg, B. (2009). Creating persuasive technologies: an eight-step design process. Proceedings of the 4th International Conference on Persuasive Technology, 1–6.
Fischer, C. (2008). Feedback on household electricity consumption: a tool for saving energy? Energy Efficiency, 1:79-104.
Froehlich, J. (2009). Promoting Energy Efficient Behavior in the Home through Feedback: The Role of Human-Computer Interaction, HCIC ’09 Workshop.
Froehlich, J., Findlater, L., & Landay, J. (2010). The design of eco-feedback technology. CHI '10: Proceedings of the 28th international conference on Human factors in computing systems.
Gustafsson, A., & Gyllenswärd, M. (2005). The poweraware cord: energy awareness through ambient information display. In Ext. Abs. CHI '05, ACM Press, 1423-1426.
Goleman, D. (2009). Ecological intelligence: How knowing the hidden impacts of what we buy can change everything. how knowing the hidden impacts of what we buy can change everything (p. 276). Crown Business.
Ham, J. (2010). A Persuasive Robotic Agent to Save Energy: The Influence of Social Feedback, Feedback Valence and Task Similarity on Energy Conservation Behavior. Social Robotics.
He, H. A., Greenberg, S., and Huang, E. M. (2010). One size does not fit all: Applying the transtheoretical model to energy feedback technology design. Proc. CHI 2010.
Holmes, T. G. (2007) Eco-visualization: combining art and technology to reduce energy consumption. In Proc. of the 6th ACM SIGCHI Conference on Creativity & Cognition, ACM Press, 153-162.
Jacucci, G. , Spagnolli, A. , Gamberini, L. , Chalambalakis, A. , Björksog, C. , Bertoncini, M. , Torstensson, C. and Monti, P (2009). Designing Effective feedback of Electricity Consumption for Mobile User Interfaces, PsychNology Journal, 7(3), 265-289.
Kim, T., & Hong, H. (2010). Designing for Persuasion: Toward Ambient Eco-Visualization for Awareness. Persuasive Technology.
Luciano, G., Giulio, J., Anna, S., Christoffer, B., Daniel, K., Alessandro, C., Luca, Z., et al. (2009). Technologies to improve energy conservation in households: The users’ perspective. In Proc. of EEDAL 2009. Retrieved from http://www.energyawareness.eu/beaware/uploads/0911_EEB_Gamberini_et_al.pdf
McCalley, L. T., & Midden, C. J. H. (2002). Energy conservation through product-integrated feedback: The roles of goal-setting and social orientation. Journal of Economic Psychology, 23(5), 589–603.
McClelland, L., and S.W. Cook. (1979). Energy conservation effects of continuous in-home feedback in all-electric homes. Journal of Environmental Systems 9 (2): 169-173.
Nielsen, J. (1994). Heuristic evaluation. Usability inspection methods.
Ozaki, R. (2010). Adopting sustainable innovation: what makes consumers sign up to green electricity Business Strategy and the Environment, 20(1), 1–17.
Pierce, J., Odom, W., & Blevis, E. (2008). Energy aware dwelling: a critical survey of interaction design for eco-visualizations. Proceedings of the 20th Australasian Conference on Computer-Human Interaction: Designing for Habitus and Habitat, 1–8.
Pierce, J., Schiano, D., & Paulos, E. (2010). Home, habits, and energy: examining domestic interactions and energy consumption. Proceedings of the 28th international conference on Human factors in computing systems, 1985–1994.
Predrag Klasnja, S. C. D. W. M. J. A. L., & Pratt, W. (2009). Using Mobile & Personal Sensing Technologies to Support Health Behavior Change in Everyday Life: Lessons Learned. AMIA Annual Symposium Proceedings, 2009, 338. American Medical Informatics Association.
Riche, Y., Dodge, J., & Metoyer, R. (2010). Studying always-on electricity feedback in the home. Proceedings of the 28th international conference on Human factors in computing systems, 1995–1998.
Spagnolli, A., Corradi, N., Gamberini, L., Hoggan, E., Jacucci, G., Katzeff, C., Broms, L., et al. (2011). Eco-Feedback on the Go: Motivating Energy Awareness. Computer, 44(5), 38–45.
Taiwan Bureau of Energy (2009). Electricity Consumption Statistic http://www.moeaboe.gov.tw/Download/opengovinfo/Plan/all/energy_year/main/files/03/table-2-34.xls
US Department of Energy (2006). Residential New Construction: An Overview of Energy Use and Energy Efficiency Opportunities, http://www.energystar.gov/ia/business/challenge/learn_more/ResidentialNewConstruction.pdf
Wilhite, H., & Ling, R. (1995). Measured energy savings from a more informative energy bill. Energy and Buildings, 22(2), 145–155.
Wood, W. (2000). Attitude change: Persuasion and social influence. Annual review of psychology, 51(1), 539–570.
堅明, 李. (2010). 實踐低碳經濟與社會之動力與作法, 1–5.