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internet of things  \nand machine learning approach  \nLim Ke Yin, Sumendra Yogarayan, Siti Fatimah Abdul Razak, Umar Ali Bukar,  \nMd Shohel Sayeed  \nFaculty of Information Science and Technology, Multimedia University, Melaka, Malaysia  \n\n| Article history:\u003Cbr>Received Jul 22, 2023 Revised Feb 29, 2024 Accepted Mar 6, 2024 | With the increasing occurrence of heat-related illnesses due to rising temperatures worldwide, there is a need for effective detection and prediction systems to mitigate the risks. Heat stroke, a life-threatening condition occurs when the body’s temperature exceeds 104 °F (40 °C) . It can happen due to prolonged exposure to temperatures. When the body struggles to cool itself down adequately. The internet of things (IoT) and machine learning (ML) are two advancing technologies that have the potential to revolutionize industries and enhance our lives in numerous ways. Currently, monitoring devices are primarily used to diagnose when individuals suffering from heatstroke are at the location. This paper delves into the exploration of utilizing the IoT and ML algorithms to predict heat strokes. It reviews existing studies in this field, focusing on how IoT has been deployed and the application of machine learning techniques. The research aims to define the integration of IoT devices and ML algorithms that has a great potential to detect and predict heat-related illnesses such as heat stroke at an early stage.\u003Cbr>This is an open access article under the CC BY-SA license.\u003Cbr>|\n| --- | --- |\n| Keywords:\u003Cbr>Heat stroke Internet of things Machine learning Prediction Technique |  |\n\nCorresponding Author:  \nSumendra Yogarayan  \nFaculty of Information Science and Technology, Multimedia University Jalan Ayer Keroh Lama, 75450 Melaka, Malaysia  \nEmail: [sumendra@mmu.edu.my](sumendra@mmu.edu.my)  \nArticle Info ABSTRACT  \n1. INTRODUCTION  \nOne of the news from New Straits Times on 13 May 2023 have reported that number of hot weather-related cased is subject to increase because of the present heat season which is predicted to last till August mentioned by Lukanisman Awang Sauni, Malaysia Deputy Health Minister [1] . On 14 May 2023, one of the Philippine’s cities, Diplolog reported have reached 47 °C in the afternoon, which is the danger category and more likely to cause heat-related illness if continued sun exposure [2] . In Singapore, the number of cases related to heat injury has increased compared to past few months due to the high temperature in midMay [3] . As many countries have reported high environment temperature which can lead to high risk of getting heat-related illness. Internet of things (IoT) refers to a network of interconnected physical devices embedded with sensors, software, and connectivity capabilities to exchange data and interact with the environment. These devices can range from everyday objects like household appliances to complex systems such as industrial machinery or smart cities [4]–[7] . IoT enables the collection and sharing of real-time data, enabling remote monitoring, control, and automation of various processes [8], [9] . On the other hand, machine learning (ML), is a subset of artificial intelligence that focuses on algorithms and statistical models that allow computers to learn from data and make predictions or take actions without being explicitly programmed. ML algorithms analyze datasets to identify patterns, relationships, and insights, and use that knowledge to make accurate predictions or decisions [10], [11] .  \nIn the context of heat-related illness prediction, IoT and ML can significantly contribute to improving early detection and prevention. IoT devices equipped with sensors can continuously monitor environmental temperature, humidity, and individual health parameters such as body temperature, heart rate, or sweat levels. The collected data can be processed and analyzed using ML algorithms to identify patterns and correlations betw","cbCairOBodQPSUOT","https://ap.wps.com/l/cbCairOBodQPSUOT","pdf",287780,"English","# ABSTRACT\n# INTRODUCTION\n# RELATED WORKS","[{\"question\":\"Why is heat stroke prediction needed?\",\"answer\":\"Heat stroke is a life-threatening condition triggered by prolonged exposure to high temperatures, and rising heat-related cases increase the need for effective detection and prediction systems.\"},{\"question\":\"How do IoT and machine learning support heat stroke prediction?\",\"answer\":\"IoT sensors can continuously collect data such as environmental temperature, humidity, and body parameters, while ML analyzes these data to identify patterns and enable early alerts.\"},{\"question\":\"What does the paper do regarding existing research?\",\"answer\":\"It reviews existing studies, focusing on how IoT has been deployed and how machine learning techniques are applied for heat stroke prediction, and discusses research gaps before concluding.\"}]","Heat stroke prediction - a perspective from the internet of things and machine learning approach | PDF",18]