As we look ahead to the coming year, it is a good opportunity to reflect on the learning moments of 2017 ― the areas where the security industry learned, grew and shifted thinking to better provide products and solutions for buildings of all types, across all industries.

Children's Geographies; 04/01/2023
(AN 163915536); ISSN: 14733285
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Children's Geographies; 12/01/2023
(AN 174964055); ISSN: 14733285
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Enhancing sustainability offerings via an alliance with Emerald Built Environments

There is a new term making its way into the commercial controls arena: digital twin.

The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding cannot detect and classify complex deformation signals reliably making providing usable information to a broad range of non-expert stakeholders a challenge. Here we explore the applicability of deep learning approaches by adapting a pre-trained convolutional neural network (CNN) to detect deformation in a national-scale velocity field. For our proof-of-concept, we focus on the UK where previously identified deformation is associated with coal-mining, ground water withdrawal, landslides and tunnelling. The sparsity of measurement points and the presence of spike noise make this a challenging application for deep learning networks, which involve calculations of the spatial convolution between images. Moreover, insufficient ground truth data exists to construct a balanced training data set, and the deformation signals are slower and more localised than in previous applications. We propose three enhancement methods to tackle these problems: i) spatial interpolation with modified matrix completion, ii) a synthetic training dataset based on the characteristics of real UK velocity map, and iii) enhanced over-wrapping techniques. Using velocity maps spanning 2015-2019, our framework detects several areas of coal mining subsidence, uplift due to dewatering, slate quarries, landslides and tunnel engineering works. The results demonstrate the potential applicability of the proposed framework to the development of automated ground motion analysis systems.

Many studies have demonstrated that the built environment is related to both collision risk and walking to school. However, little research examines the influence of the built environment on the relationship between walking to school and pedestrian collision risk.

Increased walking was not associated with increased pedestrian collision once the effects of the built environment and socioeconomic status were modeled. Safety was related primarily to the built environment and specifically features related to road crossing. (Read the full article)

The Ellen MacArthur Foundation shows how thinking circular could change the way we live for the better.

Bashirzadeh Tabrizi, Amir, author

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Rotch Library - HT168.C5 F53 2018

Rotch Library - NA2543.W65 S84 2020

Rotch Library - NA225.C36 2018