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Multi-Level Gray Evaluation Method for Assessing Health Risks in Indoor Environments
Recently, health risk assessment and early warning systems for high-temperature events have become critical concerns. However, current high-temperature warning systems primarily focus on temperature alone, which fails to accurately reflect the actual heat exposure levels and associated health risks. Therefore, this paper proposes an improved AHP (analytic hierarchy process) combined with a multi-level gray evaluation method for assessing human health risks during high-temperature conditions. A comprehensive early warning system is developed, incorporating various indicators, including human status, building conditions, and weather forecasts, making it more holistic than traditional temperature-based warning systems. A case study shows that the highest evaluation score for young individuals is 3.41, while elderly males receive the highest score of 2.5. Furthermore, the highest evaluation score for males is 3.41, while for females the highest score of 3.1. The warning results indicate that for young individuals, no alert is issued; for the elderly, a red alert is triggered; and for middle-aged individuals, the system issues orange and yellow alerts based on varying levels of risk. This study can be used to monitor health risk and provide alert message to humans. Based on the proposed early warning system, people can be able to predict health risk in time.
Multi-Level Gray Evaluation Method for Assessing Health Risks in Indoor Environments
Recently, health risk assessment and early warning systems for high-temperature events have become critical concerns. However, current high-temperature warning systems primarily focus on temperature alone, which fails to accurately reflect the actual heat exposure levels and associated health risks. Therefore, this paper proposes an improved AHP (analytic hierarchy process) combined with a multi-level gray evaluation method for assessing human health risks during high-temperature conditions. A comprehensive early warning system is developed, incorporating various indicators, including human status, building conditions, and weather forecasts, making it more holistic than traditional temperature-based warning systems. A case study shows that the highest evaluation score for young individuals is 3.41, while elderly males receive the highest score of 2.5. Furthermore, the highest evaluation score for males is 3.41, while for females the highest score of 3.1. The warning results indicate that for young individuals, no alert is issued; for the elderly, a red alert is triggered; and for middle-aged individuals, the system issues orange and yellow alerts based on varying levels of risk. This study can be used to monitor health risk and provide alert message to humans. Based on the proposed early warning system, people can be able to predict health risk in time.
Multi-Level Gray Evaluation Method for Assessing Health Risks in Indoor Environments
Yajing Wang (author) / Yan Ding (author) / Chunhua Liu (author) / Kuixing Liu (author)
2025
Article (Journal)
Electronic Resource
Unknown
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