An Automated Wireless System for Monitoring Concrete Structures Based on Embedded Electrical Resistivity Sensors: Data Transmission and Effects on Concrete Properties

Modern infrastructure heavily relies on robust concrete structures, underscoring the critical need for effective monitoring to ensure their safety and durability. This paper addresses this imperative issue by introducing an innovative automated and wireless system for continuous structural monitoring. By employing embedded electrical resistivity sensors coupled with a wireless-based data transmission mechanism, real-time data collection becomes feasible. We provide a general description of the system's architecture and its application in a pilot study covering the effects of the devices on concrete properties and data transmission. The dielectric properties of concrete specimens were investigated under natural and accelerated curing/degradation and the results were used in the final design of the antenna device. Furthermore, a pilot test comprising four reinforced concrete columns was used to investigate the range of data transmission from inside to outside of the concrete, the effects of the hardware device on the compressive strength and concrete distribution in the columns, and the data transmission quality in real time under realistic exposure conditions.

Application of Cost Effective and Real-Time Resistivity Sensor to Study Early Age Concrete

Concrete is a widely used construction material, demanding strict quality control to maintain its integrity. The durability and lifespan of concrete structures rely heavily, amongst other factors, on the characteristics of fresh and early age concrete, which are strongly dependent on the curing process. To ensure long-term durability, it is crucial to assess concrete properties throughout construction and verify compliance with design specifications. Currently, electrical resistivity-based sensors are available and used for quality control and monitoring, however, these sensors tend to be costly or only measure at a single location within the concrete cover. This study introduces a printed circuit board (PCB)-based array of electrodes capable of measuring concrete resistivity profiles across the concrete cover, from its fresh state to early age development. In this work, the feasibility of such resistivity PCB-sensors, novel for concrete, is evaluated under laboratory conditions. The sensors exhibit a promising performance in monitoring the efficiency of concrete curing under various conditions. Additionally, they successfully evaluate the effectiveness of internal curing (in our study, promoted by superabsorbent polymers) during the initial stages of hardening. This sensor array provides a valuable tool for monitoring the curing of concrete at early age, and showcases a preliminary solution that could be further developed to ensure long-term performance of concrete infrastructure.

Ambulatory Smoking Habits Investigation based on Physiology and Context (ASSIST) using wearable sensors and mobile phones: protocol for an observational study

INTRODUCTION

Smoking prevalence continues to be high over the world and smoking-induced diseases impose a heavy burden on the medical care system. As believed by many researchers, a promising way to promote healthcare and well-being at low cost for the large vulnerable smoking population is through eHealth solutions by providing self-help information about smoking cessation. But in the absence of first-hand knowledge about smoking habits in daily life settings, systems built on these methods often fail to deliver proactive and tailored interventions for different users and situations over time, thus resulting in low efficacy. To fill the gap, an observational study has been developed on the theme of objective and non-biased monitoring of smoking habits in a longitudinal and ambulatory mode. This paper presents the study protocol. The primary objective of the study is to reveal the contextual and physiological pattern of different smoking behaviours using wearable sensors and mobile phones. The secondary objectives are to (1) analyse cue factors and contextual situations of smoking events; (2) describe smoking types with regard to users' characteristics and (3) compare smoking types between and within subjects.

METHODS AND ANALYSES

This is an observational study aimed at reaching 100 participants. Inclusion criteria are adults aged between 18 and 65 years, current smoker and office worker. The primary outcome is a collection of a diverse and inclusive data set representing the daily smoking habits of the general smoking population from similar social context. Data analysation will revolve around our primary and secondary objectives. First, linear regression and linear mixed model will be used to estimate whether a factor or pattern have consistent (p value<0.05) correlation with smoking. Furthermore, multivariate multilevel analysis will be used to examine the influence of smokers' characteristics (sex, age, education, socioeconomic status, nicotine dependence, attitudes towards smoking, quit attempts, etc), contextual factors, and physical and emotional statuses on their smoking habits. Most recent machine learning techniques will also be explored to combine heterogeneous data for classification of smoking events and prediction of craving.

ETHICS AND DISSEMINATION

The study was designed together by an interdisciplinary group of researchers, including psychologist, psychiatrist, engineer and user involvement coordinator. The protocol was reviewed and approved by the ethical review board of UZ Leuven on 18 April 2016, with an approval number S60078. The study will allow us to characterise the types of smokers and triggering events. These findings will be disseminated through peer-reviewed articles.