Development of an IoT-Based Construction Worker Physiological Data Monitoring Platform at High Temperatures

Abstract

This study presents an IoT-based construction worker physiological data monitoring platform using an off-the-shelf wearable smart band. The developed platform is designed for construction workers performing under high temperatures, and the platform is composed of two parts: an overall heat assessment (OHS) and a personal management system (PMS). OHS manages the breaktimes for groups of workers based using a thermal comfort index (TCI), as provided by the Korea Meteorological Administration (KMA), while PMS assesses the individual health risk level based on fuzzy theory using data acquired from a commercially available smart band. The device contains three sensors (PPG, Acc, and skin temperature), two modules (LoRa and GPS), and a power supply, which are embedded into a microcontroller (MCU). Thus, approved personnel can monitor the status as well as the current position of a construction worker via a PC or smartphone, and can make necessary decisions remotely. The platform was tested in both indoor and outdoor environment for reliability, achieved less than 1% of error, and received satisfactory feedback from on-site users.

Individual Environmental Risk Assessment and Management in Industry 4.0: An IoT-Based Model

“…The device exchanges data with a central monitoring station. In [23], the authors presented an IoT-based construction worker physiological data-monitoring platform using an off-the-shelf wearable smart band that collects a worker's physiological data through heart rate, temperature, and accelerometer sensors. Data regarding workers' current physiological status are sent to the web and a smartphone app.…”

“…Smart PPE and other monitoring systems for OSH have been proposed by various authors, such as [23][24][25][26][27][28][29]. All these works presented solutions that can help to reduce accidents and/or work-related diseases significantly.…”

Deterrents to the IoT for smart buildings and infrastructure development: A partial least square modeling approach

“…[ 22 , 23 ]. However, the emphasis studies currently place on developing IoT application solutions for the building sector could be increased [ 24 , 25 ]. This is because most efforts are presently focused on developing IoT technology, i.e., in computer science and electrical engineering.…”

“…This is because most efforts are presently focused on developing IoT technology, i.e., in computer science and electrical engineering. However, collaboration with other fields of study, such as civil engineering or construction technology, is also necessary to determine the issues and difficulties that would be resolved or improved by using IoT and thus promote the adaptability of IoT in smart buildings [ 24 , 25 ].…”

A Classification Method for Workers’ Physical Risk

“…In particular, Heart Rate (HR) is significantly impacted by environmental conditions [ 19 ]. Indeed, physiological parameters exhibit responses not only according to what the users are doing, i.e., their level of physical workload [ 20 , 21 ], and the environment they are in, i.e., exposure to heat stress, but also reveal information about the responses of the autonomic nervous system, related with risk awareness. When people face significant risk, the sympathetic system of the autonomic nervous system generates responses measurable from vital and non-vital parameters.…”