We observe fire hazards causing life loss and property loss frequently in domestic and industrial scenarios. In industries we usually have many blocks or buildings, and it is impossible to check every building every second of the day. So, the authors' model continuously checks for fire and gives a signal: either buzzer or light depending on the requirement. This is an embedded way of hardware application and software. They also used different machine learning models and algorithms to predict the future time of the fire, using regression. For prototype applications, they use linear regression, and for real-time applications, they use k-means clustering or any other model for better accuracy.
TopLiterature Review
The authors in the paper (Shi & Songlin, 2020) demonstrated the conventional smoke sensing structures have a few drawbacks as they are consisting of excessive implementation costs, problems in perceiving operating states, low precision, accuracy and many issues in management. To cope with those problems, a brand-new form of smart wi-fi heat or temperature tracking machine primarily based totally on NB- IoT generation is innovatively designed, which realizes real-time remote monitor.
The planned system (Benzekri et al., 2020) relies on grouping environmental wireless sensing element network knowledge from the forest and predicting the prevalence of a fire victimization artificial intelligence, a lot of significantly Deep Learning (DL) models. the mix of such a system supported the construct of the net of Things (IoT) is formed of an LPWAN network.
The implemented prototype (Putra & Nazaruddin, 2019) gives us the basic understanding and implementation of interaction Between the Virtual facet mistreating the Virtual automaton experimentation platform. It is often employed in hearth rescue operations to flee from blocked conditions and to possess a quicker response within the case of a U-turn.
We can say from the work of (Kshirsagar et al., 2020) that the Internet of Things is a platform where sensors can connect and exchange information over the Internet. This review paper presents the idea of solving health-related issues such as body temperature, blood pressure, heart rate using the latest technology, the Internet of Things. The health of a person is predicted using Mongo DB the data is stored from node MCU and given to the machine learning algorithm like ARMA algorithm where the health of the patient is plotted in a linear way. The usage of this health monitoring system in Android App for better development of health.
IoT has been an important and popular technological aspect for many years. We can see its rapid growth (Aziz, 2018) in every field like medical etc now it also entered into lifestyle controllability. Communication approaches between intelligent devices. This also gives us the privilege to access and control the devices anywhere and anytime, the trend of this aspect is communication between different devices regarding the ESP8266 Node MCU module.
The practical style and implementation of a system (Shinde & Patil, 2021), (Asvany et al., 2017; Bajrami & Murturi, 2018; Mannepalli et al., 2017; Rajakumar, 2017; Rajeswari et al., 2017) for watching environmental conditions through employing a WSN and Node MCU. The system is developed for web applications. The user will monitor measurement data from any place via the web with the aid of web and mobile applications. If the information measured by a device node exceeds the organized price range, an alert will be sent to improve the conditions.