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Arslan, M, Cruz, C, Roxin, A and Ginhac, D (2018) Spatio-temporal analysis of trajectories for safer construction sites. Smart and Sustainable Built Environment, 7(01), 80–100.

Bebelaar, N, Braggaar, R C, Kleijwegt, C M, Meulmeester, R W E, Michailidou, G, Salheb, N, van der Spek, S, Vaissier, N and Verbree, E (2018) Monitoring urban environmental phenomena through a wireless distributed sensor network. Smart and Sustainable Built Environment, 7(01), 68–79.

  • Type: Journal Article
  • Keywords: Internet of Things; Smart cities; LoRaWAN; Citizen interaction; Distributed sensor network; Environmental phenomena;
  • ISBN/ISSN: 2046-6099
  • URL: https://doi.org/10.1108/SASBE-10-2017-0046
  • Abstract:
    The purpose of this paper is to provide local environmental information to raise community’s environmental awareness, as a cornerstone to improve the quality of the built environment. Next to that, it provides environmental information to professionals and academia in the fields of urbanism and urban microclimate, making it available for reuse. Design/methodology/approach The wireless sensor network (WSN) consists of sensor platforms deployed at fixed locations in the urban environment, measuring temperature, humidity, noise and air quality. Measurements are transferred to a server via long range wide area network (LoRaWAN). Data are also processed and publicly disseminated via the server. The WSN is made interactive as to increase user involvement, i.e. people who pass by a physical sensor in the city can interact with the sensor platform and request specific environmental data in near real time. Findings Microclimate phenomena such as temperature, humidity and air quality can be successfully measured with a WSN. Noise measurements are less suitable to send over LoRaWAN due to high temporal variations. Research limitations/implications Further testing and development of the sensor modules is needed to ensure consistent measurements and data quality. Practical implications Due to time and budget limitations for the project group, it was not possible to gather reliable data for noise and air quality. Therefore, conclusions on the effect of the measurements on the built environment cannot currently be drawn. Originality/value An autonomously working low-cost low-energy WSN gathering near real-time environmental data is successfully deployed. Ensuring data quality of the measurement results is subject for upcoming research.

Brynskov, M, Heijnen, A, Balestrini, M and Raetzsch, C (2018) Experimentation at scale: challenges for making urban informatics work. Smart and Sustainable Built Environment, 7(01), 150–63.

Dritsa, D and Biloria, N (2018) Towards a multi-scalar framework for smart healthcare. Smart and Sustainable Built Environment, 7(01), 33–52.

Foth, M (2018) Participatory urban informatics: towards citizen-ability. Smart and Sustainable Built Environment, 7(01), 4–19.

Gholami, M, Mofidi Shemirani, M and Fayaz, R (2018) A modelling methodology for a solar energy-efficient neighbourhood. Smart and Sustainable Built Environment, 7(01), 117–32.

Haeusler, M H, Hespanhol, L and Hoggenmueller, M (2018) ParticipationPlus. Smart and Sustainable Built Environment, 7(01), 133–49.

Hussein, D, Sarkar, S and Armstrong, P (2018) Mapping preferences for the number of built elements. Smart and Sustainable Built Environment, 7(01), 53–67.

Muehlbauer, M (2018) Towards typogenetic tools for generative urban aesthetics. Smart and Sustainable Built Environment, 7(01), 20–32.

Nourian, P, Rezvani, S, Valeckaite, K and Sariyildiz, S (2018) Modelling walking and cycling accessibility and mobility. Smart and Sustainable Built Environment, 7(01), 101–16.