Sensor-Based Safety Performance Assessment of Individual Construction Workers

Over the last decade, researchers have explored various technologies and methodologies to enhance worker safety at construction sites. The use of advanced sensing technologies mainly has focused on detecting and warning about safety issues by directly relying on the detection capabilities of these technologies. Until now, very little research has explored methods to quantitatively assess individual workers’ safety performance. For this, this study uses a tracking system to collect and use individuals’ location data in the proposed safety framework. A computational and analytical procedure/model was developed to quantify the safety performance of individual workers beyond detection and warning. The framework defines parameters for zone-based safety risks and establishes a zone-based safety risk model to quantify potential risks to workers. To demonstrate the model of safety analysis, the study conducted field tests at different construction sites, using various interaction scenarios. Probabilistic evaluation showed a slight underestimation and overestimation in certain cases; however, the model represented the overall safety performance of a subject quite well. Test results showed clear evidence of the model’s ability to capture safety conditions of workers in pre-identified hazard zones. The developed approach presents a way to provide visualized and quantified information as a form of safety index, which has not been available in the industry. In addition, such an automated method may present a suitable safety monitoring method that can eliminate human deployment that is expensive, error-prone, and time-consuming

Extra care housing: a paradigm shift

This paper sets out to investigate if and how a spatial typology for extra care housing (ECH) can be defined within the context of housing for older people in the UK. In particular, it focuses on the concept of domesticity in relation to the perception of public, semi-public and private domains. Four sheltered housing schemes that have been remodelled into ECH within the past four years, have been selected as case studies. The spatial distribution of various public, semi-public, and private domains of the pre-remodelled and remodelled schemes have been analyzed quantitatively and interpretively, to determine how their distribution might help bolster or undermine the ethos behind ECH. Likewise, the spatial layouts of the sheltered, as well as the extra care schemes have been analysed syntactically, to determine how different spatial morphologies and their probabilistic functions might begin to help define ECH as a new type of group housing for older people. The findings of the paper suggest that the extent to which the spatial configuration of a scheme affects one’s notions of self-containment and control, has a direct impact on whether the scheme performs as a building or as a settlement. It is furthermore argued that the more a scheme functions as a settlement, the less institutional it may feel. Thus, as a typology, a successful extra care scheme can be defined as a building that works as a settlement

Obstacle Avoidance and Proscriptive Bayesian Programming

Unexpected events and not modeled properties of the robot environment are some of the challenges presented by situated robotics research field. Collision avoidance is a basic security requirement and this paper proposes a probabilistic approach called Bayesian Programming, which aims to deal with the uncertainty, imprecision and incompleteness of the information handled to solve the obstacle avoidance problem. Some examples illustrate the process of embodying the programmer preliminary knowledge into a Bayesian program and experimental results of these examples implementation in an electrical vehicle are described and commented. A video illustration of the developed experiments can be found at http://www.inrialpes.fr/sharp/pub/laplac

Proscriptive Bayesian Programming Application for Collision Avoidance

Evolve safely in an unchanged environment and possibly following an optimal trajectory is one big challenge presented by situated robotics research field. Collision avoidance is a basic security requirement and this paper proposes a solution based on a probabilistic approach called Bayesian Programming. This approach aims to deal with the uncertainty, imprecision and incompleteness of the information handled. Some examples illustrate the process of embodying the programmer preliminary knowledge into a Bayesian program and experimental results of these examples implementation in an electrical vehicle are described and commented. Some videos illustrating these experiments can be found at http://www-laplace.imag.fr