University-Based Smart Cities: from collective intelligence to smart crowd-conscience

Main Article Content

Mohamed Makkaoui
Fadwa Lachhab
Mohamed Bakhouya

Abstract

Quality of life, economic, knowledge and human capitals "˜development are the main challenges of the new wave of smart cities. Hybrid strategies of cost leadership and innovation need to be aligned mostly by highly deliberate university creative services.  Physical, intellectual and social capitals are loosely coupled to better understanding of the urban fabric and norms of behavior. It requires the creation ofapplications enabling data collection and processing, web-based collaboration, and "real-time" mining of the collective intelligence of citizens. The Internet of Things (IoT) has been viewed as a promising technology with great potential for addressing many societal challenges, filling the gap in terms of citizen's sensitivity measurement. At the physical level of its ecosystem, buildings are responsible for about 40% of energy consumption in cities and more than 40% of greenhouse gas emissions. With recent products available today, energy consumption in buildings could be cut by up to 70 percent, but it requires an integrated and collective adaptive framework to show how buildings are operated, maintained and controlled with the support of IoT-based innovation and solutions. The number of new IoT protocols and applications has grown exponentially in recent years. However, IoT for smart cities needs accessible open data and open systems, so that industries and universities can develop new services and applications. The main aim is to develop energy efficient frameworks to improve energy efficiency by using innovative integrated IoT techniques. These techniques could integrate technologies from context-aware computing, context-dependent user expectation and profile and occupants' actions and behaviors. This paper tend to present in what extent a case of university-based smart city would invest in IoT as both strategy and process in order to enhance efficiency, innovative education and attractiveness for its current and future citizens.

Article Details

How to Cite
Makkaoui, M., Lachhab, F., & Bakhouya, M. (2017). University-Based Smart Cities: from collective intelligence to smart crowd-conscience. The Journal of Quality in Education, 7(9), 14. https://doi.org/10.37870/joqie.v7i9.10
Section
Articles

References

[1] Berkes F., Colding, J., Folke, C. (eds) (2002). Navigating Social-Ecological Systems: Building Resilience for Complexity and Change. Cambridge University Press, Cambridge.
[2] Caragliu A., Del Bo C., Nijkamp P. (2009), « Smart Cities in Europe », Creating Smarter Cities Conference, Edinburgh Napier University, March 2009.
[3] W. Bogard, 1996. The simulation of surveillance: Hypercontrol in telematic societies. New York: Cambridge University Press.
[4] R.G. Hollands, 2015. "Critical interventions into the corporate smart city," Cambridge Journal of Regions, Economy and Society volume 8, number 1, pp. 61"“77. http://dx.doi.org/10.1093/cjres/rsu011.
[5] D. Harvey, 1989. "From managerialism to entrepreneurialism: The transformation in urban governance in late capitalism," Geografiska Annaler. Series B, Human Geography, volume 71, number 1, pp. 3"“17. http://dx.doi.org/10.2307/490503.
[6] R.G. Hollands, 2008. "Will the real smart city please stand up? Intelligent, progressive or entrepreneurial?" City, volume 12, number 3, pp. 303"“320. http://dx.doi.org/10.1080/13604810802479126.
[7] Komninos N., Pallot M., Schaffers H. (2013), Special Issue on Smart Cities and the Future Internet in Europe, Journal of the Knowledge Economy, June, Volume 4, Issue 2.
[8] Stockholm, (2006), Stockholmforsoket, Facts and Results from the Stockholm Trial, see http://www.stockholmsforsoket.se/upload/Hushall_eng.pdf .
[9] Leydesdorff L., Deakin M. (2011), The triple-helix model of smart cities: a neo-evolutionary perspective. Journal of urban technology, 18(2), p.53-63.
[10] Deakin M. (2011), ed. Creating smart-er cities. Journal of Urban Technology, 18(2), special issue guest edited by M.Deakin.
[11] T.F. Gieryn, 2006. "City as truth-spot: Laboratories and field-sites in urban studies," Social Studies of Science, volume 36, number 1, pp. 5"“38. http://dx.doi.org/10.1177/0306312705054526.
[12] O. Halpern, J. LeCavalier, N. Calvillo, and W. Pietsch, 2013. "Test-bed urbanism," Public Culture, volume 25, number 2, pp. 273"“306.http://dx.doi.org/10.1215/08992363-2020602.
[13] Rio, (2011), In anticipation of Olympics, Rio de Janeiro bolsters emergency response, http://www.smartplanet.com/blog/smart-takes/in-anticipation-of-olympics-rio-de-janeiro-bolsters-emergency-response/13266
[14] T. Shelton, M. Zook, and A. Wiig, 2014. "The "˜actually existing smart city'," Cambridge Journal of Regions, Economy and Society, volume 8, number 1, 13"“25. http://dx.doi.org/10.1093/cjres/rsu026.
[15] Siemens, (2004), StadtderZukunft,http://www.siemens.com/innovation/de/publikationen/zeitschriften_pictures_of_th e_future/PoF_Fruehjahr_2004/SmartCity.htm
[16] Singapore, (2010), Singapore Government Info-communications Development Authority, http://www.ida.gov.sg/home/index.aspx
[17] J. Sadowski and E. Selinger, 2014. "Creating a taxonomic tool for technocracy and applying it to Silicon Valley," Technology in Society, volume 38, pp. 161"“168. http://dx.doi.org/10.1016/j.techsoc.2014.05.001.
[18] L. Coetzee, J. Eksteen, The Internet of Things-promise for the future? An introduction. In IST-Africa Conference Proceedings, IEEE, p. 1-9, 2011.
[19] V. De Florio, M. Bakhouya, A. Coronato and G. Di Marzo, Models and Concepts for Socio-technical Complex Systems: Towards Fractal Social Organizations, Systems Research & Behavioral Science, Vol. 30, No. 6, p. 750-772, 2013.
[20] Hardin, Garrett, The tragedy of the commons. Science, Vol. 162, No.3859, p.1243-1248, 1968.
[21] P. Zhao, An Energy Management System for Building Structures Using a Multi-Agent Decision-Making Control Methodology, IEEE transactions on industry applications, Vol. 49, No. 1, 2013.
[22] ISO 7730: 2005 ergonomics of thermal environment, Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal discomfort criteria, Geneve: International Standardization Organization, 2005.
[23] R. Yao, A theoretical adaptive model of thermal comfort "“ Adaptive Predicted Mean Vote (aPMV) Running, Building and Environment, Vol. 44, p. 2089"“2096, 2009.
[24] C. F. Reinhart, J. Wienold, The daylighting dashboard-A simulation-based design analysis for daylight spaces. Building and environment, Vol. 46, No. 2, p. 386-396, 2011.
[25] C. F. Reinhart, Lightswitch-2002: a model for manual and automated control of electric lighting and blinds. Solar Energy 77, p. 15-28, 2004.
[26] J. A. Jakubiec, C. F. Reinhart, The "˜adaptive zone'"“A concept for assessing discomfort glare throughout daylit spaces. Lighting Research and Technology, Vol. 44, No. 2, p. 149-170, 2012.
[27] D. àœrge-Vorsatz, L. D; Danny Harvey, S. Mirasgedis, M. D. Levine, Mitigating CO2 emissions from energy use in the world's buildings. Building Research & Information, Vol. 35, No. 4, p. 379-398, 2007.
[28] S. Salat, Energy loads, CO2 emissions and building stocks: morphologies, typologies, energy systems and behaviour. Building Research & Information, Vol. 37, No. 5-6, p. 598-609, 2009.
[29] O. A. Seppà¤nen, W. J. Fisk, M. J. Mendell, Association of ventilation rates and CO2 concentrations with health andother responses in commercial and institutional buildings. Indoor air, Vol. 9, No. 4, p. 226-252, 1999.
[30] B. Berg-Munch, G. Clausen, and R O. Fanger, ventilation requirements for the control of body odor in spaces occupied by woman. Environment international, Vol. 12, p. 195-199, 1986.
[31] M. El Mankibi, Indoor air quality control in case of scheduled or intermittent occupancy based building: Development of a scale model. Building and Environment, Vol. 44, p. 1356-1361, 2009.
[32] S. Atthajariyakul, Real-time determination of optimal indoor-air condition for thermal comfort, air quality and efficient energy usage. Energy and Buildings, Vol. 36, p. 720-733, 2004.
[33] D. àœrge-Vorsatz, L. D; Danny Harvey, S. Mirasgedis, M. D. Levine, Mitigating CO2 emissions from energy use in the world's buildings. Building Research & Information, Vol. 35, No. 4, p. 379-398, 2007.