Development of an Acoustically Adaptive Modular System for Near Real-Time Clarity-Enhancement

  • Alexander Liu ChengEmail author
  • Patricio Cruz
  • Nestor Llorca Vega
  • Andrés Mena
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11912)


This paper details the development of an acoustically adaptive modular system capable of enhancing Speech Clarity (C50 Clarity Index) in specific locations within a space in near real-time. The mechanical component of the system consists of quadrilateral, truncated pyramidal modules that extend or retract perpendicularly to their base. This enables said modules (1) to change in the steepness of the sides of their frustum, which changes the way incoming sound waves are deflected/reflected/diffused by the surfaces of the pyramid; and (2) to reveal or to hide the absorbent material under each module, which enables a portion of incoming sound waves to be absorbed/dissipated in a controlled manner. The present setup considers a fragmentary implementation of six modules. The behavior of these modules is determined by two steps in the computational component of the system. First, the initial position of the modules is set via a model previously generated by an evolutionary solver, which identifies the optimal extension/retraction extent of each of the six modules to select for individual configurations that collectively ascertain the highest clarity in said specific locations. Second, a simulated receiver at the location in question measures the actual clarity attained and updates the model’s database with respect to the configuration’s corresponding clarity-value. Since the nature of acoustics is not exact, if the attained measurement is lower than the model’s prediction for said location under the best module-configuration, but higher than the second-best configuration for the same location, the modules remain at the initial configuration. However, if the attained values are lower, this step reconfigures the modules to instantiate the second—or third-, fourth-, etc.—best configuration and updates the model’s database with respect to the new optimal module-configuration value. These steps repeat each time the user moves to another specific location. The objective of the system is to contribute to the intelligent and intuitive Speech Clarity regulation of an inhabited space. This contributes to its Interior Environmental Quality, which promotes well-being and quality of life.


Cyber-physical systems Adaptive acoustics Internet of Things 



The authors wish to acknowledge Cristian Amaguaña, Juan Balseca, and Dario Cabascango, students of the Faculty of Electrical & Electronic Engineering at Escuela Politécnica Nacional, for their assistance in the assembly of the physical implementation. Part of the present implementation was made possible by funding from Universidad Internacional SEK’s Project No. P111819.


  1. 1.
    Kameas, A., Stathis, K. (eds.): AmI 2018. LNCS, vol. 11249. Springer, Cham (2018). Scholar
  2. 2.
    De Paz, J.F., Julián, V., Villarrubia, G., Marreiros, G., Novais, P. (eds.): ISAmI 2017. AISC, vol. 615. Springer, Cham (2017). Scholar
  3. 3.
    Calvaresi, D., Cesarini, D., Sernani, P., Marinoni, M., Dragoni, A.F., Sturm, A.: Exploring the ambient assisted living domain. A systematic review. J. Ambient Intell. Hum. Comput. 8, 239–257 (2017)CrossRefGoogle Scholar
  4. 4.
    Grzegorzek, M., Gertych, A., Aumayr, G., Piętka, E.: Trends in Active and Assisted Living - Open hardware architecture, Human Data Interpretation, intervention and assistance. Comput. Biol. Med. 95, 234–235 (2018)CrossRefGoogle Scholar
  5. 5.
    Flórez-Revuelta, F., Chaaraoui, A.A. (eds.): Active and Assisted Living: Technologies and Applications. The Institution of Engineering and Technology, Stevenage (2016)Google Scholar
  6. 6.
    Fox, M.: Interactive Architecture: Adaptive World. Princeton Architectural Press, New York (2016)Google Scholar
  7. 7.
    Green, K.E.: Architectural Robotics. Ecosystems of Bits, Bytes, and Biology. The MIT Press, Cambridge (2016)Google Scholar
  8. 8.
    Edelstein, E.A., Macagno, E.: Form follows function: bridging neuroscience and architecture. In: Rassia, S.T., Pardalos, P.M. (eds.) Sustainable Environmental Design in Architecture. Impacts on Health, pp. 27–42. Springer, New York (2012). Scholar
  9. 9.
    Roulet, C.-A., Bluyssen, P.M., Müller, B., de Oliveira Fernandes, E.: Design of healthy, comfortable, and energy-efficient buildings. In: Rassia, S.T., Pardalos, P.M. (eds.) Sustainable Environmental Design in Architecture. Impacts on Health, vol. 56, pp. 83–108. Springer, New York (2012). Scholar
  10. 10.
    Bluyssen, P.M.: The Healthy Indoor Environment. How to Assess Occupants’ Wellbeing in Buildings. Routledge/Taylor & Francis Group, London (2014)Google Scholar
  11. 11.
    Puglisi, G.E., Prato, A., Sacco, T., Astolfi, A.: Influence of classroom acoustics on the reading speed. A case study on Italian second-graders. J. Acoust. Soc. Am. 144, EL144 (2018)CrossRefGoogle Scholar
  12. 12.
    Shimizu, T., Onaga, H.: Study on acoustic improvements by sound-absorbing panels and acoustical quality assessment of teleconference systems. Appl. Acoust. 139, 101–112 (2018)CrossRefGoogle Scholar
  13. 13.
    Serpanos, D.: The cyber-physical systems revolution. Computer 51, 70–73 (2018)CrossRefGoogle Scholar
  14. 14.
    Ochoa, S., Fortino, G., Di Fatta, G.: Cyber-physical systems, internet of things and big data. Future Gen. Comput. Syst. 75, 82–84 (2017)CrossRefGoogle Scholar
  15. 15.
    Rutten, D.: Galapagos. On the logic and limitations of generic solvers. Archit. Des. 83, 132–135 (2013)CrossRefGoogle Scholar
  16. 16.
    van der Harten, A.: Pachyderm acoustical simulation towards open-source sound analysis. Archit. Des. 83, 138–139 (2013)Google Scholar
  17. 17.
    Grasshopper®: About Grasshopper.
  18. 18.
    Rutten, D.: Evolutionary Principles Applied to Problem Solving. Austria, Vienna (2010)Google Scholar
  19. 19.
    European Association of Research and Technology Organisations (EARTO): The TRL Scale as a Research & Innovation Policy TOOL. EARTO Recommendations.
  20. 20.
    Bier, H., Liu Cheng, A., Mostafavi, S., Anton, A., Bodea, S.: Robotic building as integration of design-to-robotic-production and -operation. In: Bier, H. (ed.) Robotic Building, 1. Springer International Publishing AG (2018). Scholar
  21. 21.
    Oosterhuis, K.: Caught in the act. In: Kretzer, M., Hovestadt, L. (eds.) ALIVE. Advancements in Adaptive Architecture, vol. 8, pp. 114–119. Birkhäuser, Basel/Berlin/Boston (2014)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of ArchitectureDelft University of TechnologyDelftThe Netherlands
  2. 2.Faculty of Architecture and EngineeringsUniversidad Internacional SEKQuitoEcuador
  3. 3.Faculty of Electrical and Electronic EngineeringEscuela Politécnica NacionalQuitoEcuador
  4. 4.School of ArchitectureUniversidad de AlcaláMadridSpain

Personalised recommendations