Design-to-Robotic-Operation Principles and Strategies as Drivers of Interior Environmental Quality

Alexander Liu Cheng

Abstract


This paper presents a high-resolution intelligence implementation based on Design-to-Robotic-Operation (D2RO) principles and strategies specifically employed to attain and to sustain Interior Environmental Quality (IEQ) within a dynamic built-environment. This implementation focuses on two IEQ-parameters, namely illumination and ventilation; and is developed in three main steps. In the first step, a formal design-criteria based on D2RO principles is developed in order to imbue considerations of intelligence into the early stages of the design process. In the second step, illumination and ventilation systems are developed as IEQ-regulating mechanisms whose behavior is determined by machine-learning models that continuously learn from the occupants and their preferences with respect to interior environmental comfort. In the third and final step, the resulting implementation is tested with probands in order to demonstrate continuous intelligent adaptation with respect to illumination and ventilation, which in turn demonstrates that a D2RO approach to IEQ yields a more intelligent adaptive mechanism that promotes occupant well-being in an invisible, unobtrusive, intuitive manner. 

Keywords


Adaptive Architecture, Cyber-Physical Systems, Robotic Building, Ambient Intelligence, Interior Environmental Quality.

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References


Acampora, G., Cook, D. J., Rashidi, P., & Vasilakos, A. V. (2013). A Survey on Ambient Intelligence in Healthcare. Proceedings of the IEEE, 101(12), 2470–2494.

Al Horr, Y., Arif, M., Katafygiotou, M., Mazroei, A., Kaushik, A., & Elsarrag, E. (2016). Impact of indoor environmental quality on occupant well-being and comfort: A review of the literature. International Journal of Sustainable Built Environment, 5(1), 1–11.

Bier, H. H. (2016). Robotic Building as Integration of Design-to-Robotic-Production & Operation. Next Generation Building, (3).

Bluyssen, P. M. (2014). The healthy indoor environment: How to assess occupants' wellbeing in buildings. London, New York: Routledge/Taylor & Francis Group.

Bluyssen, P. M., Aries, M., & van Dommelen, P. (2011). Comfort of workers in office buildings: The European HOPE project. Building and Environment, 46(1), 280–288.

Chatzidiakou, L., Pathan, A., Summerfield, A., & Mumovic, D. (2012). Environmental and Behavioral Factors Affecting Residential Air Conditioning Use in Athens and London. In S. T. Rassia & P. M. Pardalos (Eds.), Springer optimization and its applications: v. 56. Sustainable environmental design in architecture. Impacts on health (pp. 109–141). New York, NY: Springer.

Liu Cheng, A. (2016). Towards embedding high-resolution intelligence into the built-environment. Archidoct, 4(1), 29–40. Retrieved September 15, 2016, from http://www.enhsa.net/archidoct/Issues/ArchiDoct_vol4_iss1.pdf.

Liu Cheng, A., & Bier, H. H. (2016a). An Extended Ambient Intelligence Implementation for Enhanced Human-Space Interaction. In Proceedings of the 33rd International Symposium on Automation and Robotics in Construction and Mining (ISARC 2016) .

Liu Cheng, A., & Bier, H. H. (2016b). Adaptive Building-Skin Components as Context-Aware Nodes in an Extended Cyber-Physical Network. In Proceedings of the 3rd IEEE World Forum on Internet of Things (pp. 257–262). IEEE.

Mohamed, A., Novais, P., Pereira, A., González, G. V., & Fernández-Caballero, A. (2015). Ambient intelligence -- software and applications: 6th International Symposium on Ambient Intelligence (ISAmI 2015). Advances in intelligent systems and computing: volume 376. Cham: Springer.

Nakaso, S., Güttler, J., Mita, A., & Bock, T. (2016). Human state estimation system implemented in an Office Deployable Getaway based on multiple bio information. In Proceedings of the 33rd International Symposium on Automation and Robotics in Construction and Mining (ISARC 2016) .

Roulet, C.-A., Bluyssen, P. M., Müller, B., & Oliveira Fernandes, E. de (2012). Design of Healthy, Comfortable, and Energy-Efficient Buildings. In S. T. Rassia & P. M. Pardalos (Eds.), Springer optimization and its applications: v. 56. Sustainable environmental design in architecture. Impacts on health (pp. 83–108). New York, NY: Springer.

Sakhare, V. V., & Ralegaonkar, R. V. (2014). Indoor environmental quality: Review of parameters and assessment models. Architectural Science Review, 57(2), 147–154.

Sheng, Q. Z., Shakshuki, E. M., & Ma, J. (2014). Advances in ambient intelligence technologies. Journal of Ambient Intelligence and Humanized Computing, 5(3), 341–342.




DOI: http://dx.doi.org/10.7480/ngb.3.1.1559