A review of smart building sensing system for better indoor environment control

Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons

Deep learning and transfer learning models of energy consumption forecasting for a building with poor information data

The role of sensitivity analysis in the building performance analysis: A critical review

The construction industry has traditionally been characterised by the high diversity of its agents and processes, high resistance to change and low incorporation of technology compared to manufacturing industries However, the construction sector is experiencing now a strong renovation process in methodology and tools due to the incorporation of the Building Information Modelling, Lean Construction and Integrated Project Delivery Meanwhile, in production systems, “Industry 40” is a new paradigm that proposes automation, monitoring, sensorisation, robotisation, and digitalisation to improve production and distribution processes In this context, some authors have proposed the concept of “Construction 40” as the counterpart of Industry 40 for the construction sector, although the methodological-technological implications are not clear This research shows a methodological-technological framework adapted to the Architecture, Engineering, Construction, and Operations industry This papers includes a detailed proposal for a reference frameworks and related technologies that could impact on this sector, responding to its complexities and specific challenges, such as the unique spaces for each work, which are difficult to standardise, arbitrary cost overruns and a productivity far below the average for other industries, increasing competitiveness and globalisation, as opposed to its traditionally local deployment, and an increasing demand to reduce the carbon footprint for all its activities

Methodological-Technological Framework for Construction 4.0

Application of mobile positioning occupancy data for building energy simulation: An engineering case study

While GPS-based outdoor localization has become a norm, very few indoor localization systems have been deployed and used. In this paper, we share our 5-year experience on the design, development and evaluation of a large-scale WiFi indoor localization system. We address practical challenges encountered to bridge the gap between indoor localization research in the laboratory and system deployment in the wild. The system is currently used in 1469 shopping malls, 393 office buildings and 35 hospitals across 35 cities to provide location service to millions of users on a daily basis. We hope the shared experience can benefit the design of real-world indoor localization systems and the practical problems identified can change the focus of indoor localization research. We released our dataset that contains fingerprints collected from 1469 shopping malls and one office building.

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Xin Li

Papers

Application of mobile positioning occupancy data for building energy simulation: An engineering case study

Experience: pushing indoor localization from laboratory to the wild