An IoT-aware smart system to detect thermal comfort in industrial environments

Sergi, Ilaria; Catarinucci, Luca; Montanaro, Teodoro; Colella, Riccardo; Shumba, Angela Tafadzwa; Ferraro, Simona Del; Lenzuni, Paolo; Patrono, Luigi

doi:10.23919/splitech52315.2021.9566378

Cited by 8 publications

(7 citation statements)

References 27 publications

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“…This aids in assessing the risk of heat-related illnesses using temperature and humidity data. It has been demonstrated that heat stress prediction using the Heat Index app, is beneficial for preventing heat exhaustion in outdoor jobs (Moohialdin et al ., 2020; Sergi et al ., 2021; Folkerts et al ., 2021).…”

Section: Findings and Discussionmentioning

confidence: 99%

Apps as partial replacement for robotics and automation systems in construction health and safety management

Yankah,

Adjei,

Tieru

2024

FEBE

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PurposeRobotics and automation are successful in construction, health and safety, but costs and expertise hinder their use in developing nations. This study examined mobile apps as a more accessible and affordable alternative.Design/methodology/approachThis descriptive study explored the use of mobile apps in construction, health and safety management. It used a literature review to identify their availability, accessibility, and capabilities. The study consisted of four five stages: searching for relevant apps, selecting them based on versatility, examining their specific functions, removing untested apps and discussing their functions based on empirical studies.FindingsA comprehensive literature review identified 35 mobile apps that are relevant to health and safety management during construction. After rigorous analysis, eight apps were selected for further study based on their relevance, user friendliness and compliance with safety standards. These apps collectively serve 28 distinct functions, including first-aid training and administration, safety compliance and danger awareness, safety education and training, hazard detection and warnings.Practical implicationsThis study suggests that mobile apps can provide a cost-effective and readily accessible alternative to robotics and automation in health and safety management in construction. Further research is needed to accurately assess the efficacy of these apps in real-world conditions.Originality/valueThis study explored the use of apps in health and safety management, highlighting their diverse capabilities and providing a framework for project managers, contractors and safety officers to select suitable apps.

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Section: Findings and Discussionmentioning

confidence: 99%

Apps as partial replacement for robotics and automation systems in construction health and safety management

Yankah,

Adjei,

Tieru

2024

FEBE

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“…For the development of this article, big data solutions were considered to support the continuous transmission of data and the use of AutoML to streamline and simplify the analysis, processing and predictions of the environment parameters, according to the suggestions of future works by Sergi I, Catarinucci L, Montanaro T, et al 20 ; Ray PP 21 ; and Katsarou K, Ounoughi C, Mouakher A, et al 28…”

Section: Methodsmentioning

confidence: 99%

“…The system determines environmental conditions without using user feedback on environmental conditions. 27 For the development of this article, big data solutions were considered to support the continuous transmission of data and the use of AutoML to streamline and simplify the analysis, processing and predictions of the environment parameters, according to the suggestions of future works by Sergi I, Catarinucci L, Montanaro T, et al 20 ; Ray PP 21 ; and Katsarou K, Ounoughi C, Mouakher A, et al 28 For data collection regarding air temperature (°C) and relative air humidity (%), IoT motes were used. Each one, illustrated in Figure 1, is composed of a DOIT ESP32 -ESP-WROOM-32 board connected to a Wi-Fi network, a DHT11 temperature and humidity sensor.…”

Section: Methodsmentioning

confidence: 99%

“…Sergi I, Catarinucci L, Montanaro T, et al 20 and Ray PP 21 suggested that to make monitoring more secure, security, privacy and authentication issues should be considered. The apiKeyValue parameter is defined in the prototype code, which is a string used to authenticate each prototype before publishing the information in the database.…”

Section: Methodsmentioning

confidence: 99%

“…Work environments that expose employees to strenuous work under conditions of high thermal stress can lead to rapid increases in body temperature that increase the risk of heat-related illnesses and even death rates. Sergi I, Catarinucci L, Montanaro T, et al 20 developed a continuous monitoring system for skin temperature and heart rate to prevent injury, illness and identify real-time heat stress conditions for workers in the workplace. Ray PP 21 used the Missenard index to measure and monitor the thermal comfort of the environment in real-time.…”

Section: Introductionmentioning

confidence: 99%

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Internet of things and machine learning applied to the thermal comfort of internal environments

Nascimento

Lopes

2022

Indoor and Built Environment

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The internet of things connects objects to the internet, enabling the dialogue between devices and users, providing new opportunities for applications, such as thermal comfort. In the research, adequate sensors were used to measure the heat index, the thermal discomfort index and the temperature and humidity index based on the temperature and relative humidity of a remote indoor environment. This research evaluated the level of thermal comfort in real-time using tools of storage, processing and analysis of big data information from the collection of IoT devices. With the analysis of the environment, it is possible to intelligently monitor the level of comfort and alert possible hazards to the people present. Machine learning algorithms were also used to analyse the history of stored data and formulate models capable of making predictions of the parameters of the environment. Health researchers, for example, have the necessary knowledge to evaluate clinical data, but they are not used to using data analysis resources and machine learning algorithms. The platform was developed to reduce dependence on data experts and encourage healthcare researchers to develop their own models by automating the steps required for model development, using automated machine learning (AutoML).

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