FACULTAD DE INGENIERÍA Escuela Académico Profesional de Ingeniería de Sistemas e Informática Tesis Monitoring a web page and Implementation of an Autonomous Smart IoT Device with ESP32 for Automatic Detection and Regulation of Thermal Comfort in closed environments Ingrid Melany Cordova Yangali Giuliana Stephany Makeva Guillermo Vilcapoma Luis Daniel Lazo Tapia Alan Miguel Infante Vidalon Para optar el Título Profesional de Ingeniero de Sistemas e Informática Huancayo, 2025 Esta obra está bajo una Licencia "Creative Commons Atribución 4.0 Internacional" . INFORME DE CONFORMIDAD DE ORIGINALIDAD DE TRABAJO DE INVESTIGACIÓN A : Decano de la Facultad de Ingeniería DE : Alan Miguel Infante Vidalon Asesor de trabajo de investigación ASUNTO : Remito resultado de evaluación de originalidad de trabajo de investigación FECHA : 12 de Agosto de 2025 Con sumo agrado me dirijo a vuestro despacho para informar que, en mi condición de asesor del trabajo de investigación: Título: MONITORING A WEB PAGE AND IMPLEMENTATION OF AN AUTONOMOUS SMART IOT DEVICE WITH ESP32 FOR AUTOMATIC DETECTION AND REGULATION OF THERMAL COMFORT IN CLOSED ENVIRONMENTS URL / DOI: https://doi.org/10.1145/3701100.3701163 Autores: 1. INGRID MELANY CORDOVA YANGALI - EAP. INGENIERÍA DE SISTEMAS E INFORMÁTICA 2. GIULIANA STEPHANY MAKEVA GUILLERMO VILCAPOMA - EAP. INGENIERÍA DE SISTEMAS E INFORMÁTICA 3. LUIS DANIEL LAZO TAPIA - EAP. INGENIERÍA DE SISTEMAS E INFORMÁTICA 4. ALAN MIGUEL INFANTE VIDALON – EAP. INGENIERÍA DE SISTEMAS E INFORMÁTICA Se procedió con la carga del documento a la plataforma “Turnitin” y se realizó la verificación completa de las coincidencias resaltadas por el software dando por resultado 17 % de similitud sin encontrarse hallazgos relacionados a plagio. Se utilizaron los siguientes filtros: • Filtro de exclusión de bibliografía SI NO X • Filtro de exclusión de grupos de palabras menores SI X NO Nº de palabras excluidas (en caso de elegir “SI”): 20 • Exclusión de fuente por trabajo anterior del mismo estudiante SI NO X En consecuencia, se determina que el trabajo de investigación constituye un documento original al presentar similitud de otros autores (citas) por debajo del porcentaje establecido por la Universidad Continental. Recae toda responsabilidad del contenido del trabajo de investigación sobre el autor y asesor, en concordancia a los principios expresados en el Reglamento del Registro Nacional de Trabajos conducentes a Grados y Títulos – RENATI y en la normativa de la Universidad Continental. Atentamente, La firma del asesor obra en el archivo original __________________________________ Monitoring a web page and Implementation of an Autonomous Smart IoT Device with ESP32 for Automatic Detection and Regulation of Thermal Comfort in closed environments Ingrid Melany Cordova Yangali* Continental University, 71695983@continental.edu.pe Giuliana Stephany Makeva Guillermo Vilcapoma Continental University, 72042426@continental.edu.pe Luis Daniel Lazo Tapia Continental University,73215336@continental.edu.pe Alan Miguel Infante Vidalon Continental University,ainfante@continental.edu.pe Nowadays, it is essential to harness the potential of the Internet of Things (IoT) to improve people's well-being. In this context, a project was carried out to achieve autonomous thermal comfort in closed environments, using a web page and a mobile application for data entry and monitoring of thermal comfort. These systems are connected to a REST API, created under a single database for greater control and efficiency in automation. The database is linked to an ESP32-S3, which in turn connects to sensors that collect data every minute and enter it into the database. Thermal comfort indices are then calculated using mathematical formulas. A significant advantage is that the ESP32-S3-WROOM allows monitoring from anywhere in the world via the Internet. By analyzing the data according to ASHRAE 55 standards and the PMV, PPD, SET and TCI indices, it was possible to demonstrate that the system contributes to thermal comfort in closed environments. Through statistics such as ANOVA, comparison of thermal comfort indices, linear regression and distribution, the effectiveness of the system was evidenced. While there are other IoT systems and similar projects, most have been limited to monitoring and have not addressed automation in the context of thermal comfort. In conclusion, this project presents a model and system suitable for use in closed environments, with the aim of achieving community and tranquility in terms of thermal comfort during daily activities. Keywords: IoT, Thermal comfort, ESP32, smart device, website, programming. 1 INTRODUCTION As we know, the field of technology has been advancing over the years, which is why today we have the IoT (Internet of Things), this refers to the network of devices in which each one has a chip with which it can communicate to the Internet where we can collect, exchange and act on this data [1] Today, as programmers, it is easier for us to incorporate a code into a smart device or the (IoT) Internet of Things and thus it can work in a more technological way so that people can receive information through it and with a simple click you can do several functions. [1] The approach based on this project was mostly that people have good thermal comfort in closed environments since it is a crucial aspect for the well-being and productivity of people in closed environments and through it we can measure the level in which the environment is [1]. Our Intelligent IoT-based system integrates multiple sensor and actuator subsystems, designed to manage and optimize thermal comfort autonomously. The ability to control and manage a Remote systems and equipment can be an advantage of the Internet of Things, as it can increase personal comfort, convenience and efficiency.[2] By developing technological solutions tailored to local needs, the ability of communities to respond effectively and sustainably to specific challenges is strengthened.In this project, the systems engineering approach is highlighted by the integration of the ESP32, an advanced microcontroller that allows efficient and customized automation of thermal comfort detection and regulation, with successful applications in smart homes and monitoring systems.[3] With these devices it is possible to transform a local data acquisition system into an IoT system that constantly feeds a database in the cloud.[4] In the search for a greater integration of these, the development mailto:73215336@continental.edu.pe mailto:ainfante@continental.edu.pe of integrated hardware and software solutions for students and professionals in these areas is becoming more viable every day[4]. That is why we chose programming through the Arduino Ide program where we will use a programming code so that it works in a more optimal way. For the programming of Arduino boards, the open source programming framework for microcontrollers Wiring is used, which is based on the Processing programming language that was developed in Java with syntax and semantics similar to C and C++.[5]To achieve a more comfortable and personalized environment, we developed a system that runs sensors and stores the data obtained in a database for monitoring. At this point we took the PHP programming to be able to create a web page where through it we can monitor the thermal comfort of our closed environments. This language has proven to be a great complement in the development of software with fail-safe and extensible code [6]. We created a system that collects data from sensors, monitors it and displays it on a web page, allowing the environment to be personalized according to each person's preferences. It was also easier for us to be able to use PHP since another use it has is that it has a very good interaction with HyperText Markup Language (HTML) to be able to create web sites in a simple way. [7] The system works on a web server that facilitates the connection to databases such as MySQL and allows you to configure PHP environments in a simpler and more efficient way, we also use a mobile application so that we can see the data in a more portable way. The Flutter framework with Dart programming allows developers to effortlessly create an application since a single code base is used for both the web and mobile devices [8]. Its "hot reload" function allows us rapid iteration and experimentation, making it more suitable for educational purposes as well as offering an efficient design, model and language for application development. [8]. The widgets they offer are pre-built interface solutions where you do not have the need to write them from scratch since these allow you to build interfaces very quickly in addition to being highly customizable [9] From the perspective of the Sustainable Development Goals (SDG), these tell us that these factors that we have investigated become more evident when trying to use sustainability and in this situation and apply it to the goals and through activities that must be carried out to achieve them due to the amount of [10] This is why this project contributes to the following objectives. Thermal comfort is crucial for health and well-being, as extreme temperatures, whether hot or cold, can increase the risk of respiratory diseases, heat stress, and other health problems. [11] That is why adequate thermal comfort has a type of solution and has a great economic and environmental impact. [12] Mental health can be promoted by maintaining an adequate thermal environment, since prolonged exposure to uncomfortable temperatures can cause stress and affect people's mood and productivity according to the thermal environment standard. [13] Therefore, the system is aligned with SDG 3,whose objective is to ensure healthy lives and promote well-being for all at all ages. It consists of ensuring healthy lives and promoting well-being for all at all ages.[14] The project incorporates the Internet of Things (IoT) into thermal comfort solutions, representing an important advance in technological innovation. Technology and innovation are now key in Latin American public policies to drive development and improve general well-being.[15]Using advanced technologies such as ESP32, we support the development of the technology industry in Huancayo, aligning with SDG 9 to promote innovation-based industrialization, making the industry more competitive and less polluting, while strengthening support to developing countries in the technological and financial fields.[12] Sustainable development is a complex issue; it involves various dimensions and trends in science today; It conditions various scenarios and paradigms that interact in search of better living conditions[16]. The seventh MDG spoke of guaranteeing sustainability and is linked to this wildcard that appears in SDG 11 where it expands more on infrastructure, cities and communities[12] Where it is intended to make cities and towns inclusive, resilient and sustainable. The automation of the process of detection and regulation of thermal comfort based on ESP32 presents several advantages: The system adapts to the individual preferences and needs of each user, providing a personalized thermal environment. Energy efficiency: By activating the actuators only when necessary, a more efficient use of energy is achieved, reducing consumption and associated costs. Comfort and well- being: By automatically maintaining optimal thermal comfort, the quality of life is improved and the stress caused by uncomfortable environments is reduced. Applicability: The device is easily adaptable to different types of spaces, from residential rooms to offices and classrooms, thanks to its compact and modular design.while strengthening support to developing countries in the technological and financial fields[12] Sustainable development is a complex issue; it involves various dimensions and trends in science today; it conditions various scenarios and paradigms that interact in search of better living conditions[16]. The seventh MDG spoke of guaranteeing sustainability and is linked to this wildcard that appears in SDG 11 where it expands more on infrastructure, cities and communities[12] Where it is intended to make cities and towns inclusive, resilient and sustainable. The automation of the process of detection and regulation of thermal comfort based on ESP32 presents several advantages:The system adapts to the individual preferences and needs of each user, providing a personalized thermal environment. Energy efficiency: By activating the actuators only when necessary, a more efficient use of energy is achieved, reducing consumption and associated costs. Comfort and well-being: By automatically maintaining optimal thermal comfort, the quality of life is improved and the stress caused by uncomfortable environments is reduced. Applicability: The device is easily adaptable to different types of spaces, from residential rooms to offices and classrooms, thanks to its compact and modular design.while strengthening support to developing countries in the technological and financial fields[12] Sustainable development is a complex issue; it involves various dimensions and trends in science today; it conditions various scenarios and paradigms that interact in search of better living conditions[16]. The seventh MDG spoke of guaranteeing sustainability and is linked to this wildcard that appears in SDG 11 where it expands more on infrastructure, cities and communities[12] Where it is intended to make cities and towns inclusive, resilient and sustainable. The automation of the process of detection and regulation of thermal comfort based on ESP32 presents several advantages:The system adapts to the individual preferences and needs of each user, providing a personalized thermal environment. Energy efficiency: By activating the actuators only when necessary, a more efficient use of energy is achieved, reducing consumption and associated costs. Comfort and well-being: By automatically maintaining optimal thermal comfort, the quality of life is improved and the stress caused by uncomfortable environments is reduced. Applicability: The device is easily adaptable to different types of spaces, from residential rooms to offices and classrooms, thanks to its compact and modular design. 2 METHODOLOGY Figure 1. Prototype diagram in fritzing Figure 2. 3D prototype design made in AUTOCAD Figure 1 shows the diagram of the entire project physically carried out to find thermal comfort by automating with sensors and programming, its connections are visualized below each part used in this project is shown: A) ESP32-S3-WROOM-1: An ESP32 microcontroller, type WROOM-32 manages the raw environmental data and sends the data to the middleware layer at regular intervals via Wi-Fi, using the HTTP protocol [17]. It is a low-cost and energy-efficient integrated dual-mode WiFi/Bluetooth development board. B) DHT11 temperature and humidity sensor: the component uses a capacitive humidity sensor and a transmitter to perform these measurements. It can measure the temperature between 0° to 50°C with a margin of error of 2℃. In addition, with the DHT11, values ranging from 20 to 90% for humidity measurement are detected with a margin of error of 5%. [18]. Like the ESP32, it is a low-cost component, in addition to being a digital sensor that measures temperature and relative humidity, it measures the surrounding air. C) BMP180 Barometer: It is a sensor module for measuring pressure and altitude, with extremely low consumption and very small dimensions [19]. It measures the temperature with respect to sea level, it works in relation between air pressure and altitude. This type of sensor can be used to calculate height with high precision. D) MLX90614 Infrared Temperature Sensor: It is a low-cost thermal infrared (TIR) sensor that has received special attention due to its accuracy (± 0.5 ◦ C), robustness, affordable prices compared to conventional sensors [20]. It is a microcomponent that allows the temperature of an object that is at a distance to be measured without the need for contact. E) Led: it is an electrical component with two electrodes that emit light. F) Push button: it is a type of switch that allows or interrupts the passage of electric current permanently but only works when it is held down. G) 2 CH relay module: it electrically activates switches that can turn on or off some elements [21]. It is used to control high voltage and high current loads in this project, for example the fan and theheater. H) SWITCH: is a device that allows the opening and closing of the passage of electric current. Figure 2 shows a design made in AutoCAD used by engineering professionals to create and manipulate architectural projects and designs in a practical and efficient way [24]. Figure 2. Project Flow Figure 3 details the architecture that was created to find thermal comfort through the programming carried out and the sensors configured to the ESP32. 2.1 Process For this project we made a web page, a mobile application and both connected to a rest api and it is connected to a single database, this database connected to the esp32 through a php file that was the connection bridge between the database and the ESP32, this in turn connected to the MLX90614 infrared sensor, BMP180 barometric sensor, DHT11 humidity sensor, with which we can monitor the operation of our system. The Php programming language, Javascript and the Html hypertext language were used and for the CSS design, to create the web page and connect the Mysql database to Esp32, a bridge made in php was used. The Dart language was also used with the flutter framework with packages and libraries for its connection to the database through apirest. In order to find the thermal comfort, the indices and standards PMV (Predicted Mean Vote), PPD (Predicted Percentage Dissatisfied), SET (Standard Effective Temperature), TCI (Thermal Comfort Index) and thermal sensation of the ASHRAE 55 standard were used. Mathematical formulas were used that were entered into the system in order to have an automatic response and thus be able to turn the heater and fan on or off depending on these mathematical formulas. The original PMV formula, proposed by PO Fanger, is: 𝑃𝑀𝑉 = 0.303 ∗ 𝑒−0.036 ∗𝑀 + 0.028 ∗ (𝑀 − 𝑊 − 𝐿) (1) Where: • M is the metabolic rate in W/m². • W is the external work in W/m² . • L is the total thermal load of the body in W/m². The formula for calculating PPD, also introduced by PO Fanger, is: 𝑃𝐷𝐷 = 100 − 95 ∗ 𝑒−0.03353 ∗ 𝑃𝑀𝑉4 − 0.2179 ∗ 𝑃𝑀𝑉2 (2) This index estimates the percentage of people who would feel dissatisfied in a given environment, derived directly from the MVP. The SET index was developed by Gagge, Stolwijk and Saltin. The basic formula for calculating the SET is: 𝑆𝐸𝑇 = 𝑡0 + 𝐻𝑠𝑘− 𝐻𝑑 ℎ𝑐+ ℎ𝑟∗ 𝑖𝑚 (3) Where: • to is the operating temperature in °C. • Hsk is the total body heat loss in W/m². • Hd is the heat loss by diffusion through the skin in W/m². • Hc is the convection heat transfer coefficient in W/m²·°C. • Hr is the radiation heat transfer coefficient in W/m²·°C. • Im is the permeability of clothing to water vapor. The TCI does not have a single original formula attributed to a single scientist, as it has been influenced by several thermal comfort models. However, a common way of calculating it is: 𝑇𝐶𝐼 = 06215 ∗ 𝑡𝑎 − 0.4873 ∗ 𝑣0.16 + (0.6215 ∗ 𝑡𝑎 − 11.37) ∗ 𝑣0.16 (4) Where: • ta is the air temperature in °C. • v is the air velocity in m/s. Under these formulas, the programming that automates our systems to make the decision to turn on or off devices such as the heater and fan was carried out. Figure 5. Design of the mobile application for thermal comfort assessment Figure 5. Design of a web page Figure 4 shows the web page created with user security and registration only under the authorization of the super administrator, also on the web we added more data such as (age, altitude of the city, CLO, MET) this makes our formula and result exact, in addition the data obtained in real time is shown (PMV, PPD, SET and TCI), in addition to a comfort report per minute, hour and days that helps us monitor and analyze the data and how many times the thermal comfort was stabilized. Figure 5 shows the creation of the mobile application, which is connected to a REST API and this in turn to the database, with which the data can be viewed in real time, and, as can also be seen through a graph, it also manages the sending of data for updating data such as age, altitude of the city, Clo (Clothing Insulation), Met (Metabolic Equivalent of Task), these last two data are entered under the standard data of ASHRAE 55. Figure 6. Database design for the thermal comfort control system. Figure 7. Analysis of thermal comfort in a closed environment Figure 8. OLS regression results for the PMV model Figure 6 shows the database used in this project. It contains tables and fields connected to each other. In order to have a solid and stable project, the data obtained from the sensor and the extra data obtained from the website and mobile app were stored. So that the mathematical formulas extract the data from the database and the automation for thermal comfort can be carried out. 3 RESULTS The data was extracted by minute, but for this research the data was taken by hour in a period of 30 days, being able to obtain good results in our project. The results were as follows: The thermal comfort control system uses ESP32 to receive data from the MLX90614, BMP180 and DHT11 sensors that measure the temperature, pressure and humidity in a closed environment. Using this information, the ESP32 will decide to activate the heater or fan through the relay depending on the environmental conditions. In addition, the data is transferred to a MySQL database for storage and query. Users can monitor and manage the system in real time using a laptop or Android phone, providing a convenient environment in an automated way. Figure 7 shows a graph representing an analysis of thermal comfort over a month (30 days). Three variables are shown: Temperature (°C), Humidity (%) and Comfort Index. Temperature shows an irregular pattern with peaks and valleys, showing significant variations over the month. Humidity also shows variations, but seems to have a more stable pattern. The Comfort Index, which is probably calculated using the other two variables, shows considerable variability, but generally remains above a comfort threshold indicated at the bottom of the graph. The graph suggests that thermal comfort conditions are not uniform over the month, with some days being more comfortable than others. The horizontal line representing the comfort threshold tells us that, despite the fluctuations, comfort conditions generally remain within an acceptable range. Figure 9. Anova statistics Figure 10. Distribution of the Thermal Comfort Index (PMV) Figure 8 shows the result of a linear regression. The linear regression attempts to explain the dependent variable “pmv” (represents the Predicted Mean Vote, an index of thermal comfort) using one independent variable, group T. Weekend. This means that it is being investigated whether the fact that it is a weekend or not affects the level of thermal comfort. The results show:R-squared: The model explains 0% of the variability in PMV, which is extremely low.Adj. R-squared: Similarly, the Adjusted R-squared is negative, indicating that the model has no predictive power. F-statistic: The F-statistic has a value of 0.25, with a probability (P) of 0.616. This suggests that there is no evidence to reject the null hypothesis that the model has no predictive power. Coefficients: The coefficient of the intercept is 1.459e+09, while the coefficient of the group [T. Weekend] is -1.511e+08. These values represent the influence of each variable on PMV. T-statistics: The statistics for the intercept and the group [T. Weekend] are 8.407 and -0.501, respectively, with P-values of 0.000 and 0.616. This indicates that the intercept is statistically significant, while the group [T. Weekend] is not. The results of the linear regression suggest that there is no evidence that whether it is a weekend or not has a significant impact on PMV. The model has no predictive power and the only significant coefficient is the intercept, indicating that PMV remains constant regardless of whether it is a weekday or weekend. Figure 9 shows a graph showing a comparison of the PMV (Predicted Mean Vote) index between weekdays and weekends. It can be seen that the PMV distribution is similar in both cases. However, it can be seen that the interquartile range (IQR) is higher for weekdays, indicating greater variability in thermal comfort during those days. In addition, the outlier on weekdays suggests that exceptionally low PMV values have been recorded in some cases. The graph suggests that thermal comfort conditions are slightly more variable during weekdays compared to weekends. This could be due to factors such as higher foot traffic on weekdays, which can increase temperature and humidity, or differences in the use of heating or ventilation. Figure 11. Relationship between PPD and thermal comfort indices PMV, SET and TCI Figure 12. Regression graphs for the TLC value Figure 10 shows the distribution graph of the PMV thermal comfort index. The horizontal axis represents the PMV index, which ranges from -8e9 to 8e9. The vertical axis represents the frequency, which ranges from 0 to 120. The graph shows that most of the PMV index values are between 0e9 and 2e9, with a peak at around 1.2e9. There are fewer values at the extremes of the range, with a slight increase in negative values around -4e9. This pattern suggests that most of the data are within the thermal comfort zone, but that there are some situations where the temperature is uncomfortable. In Figure 11 the image contains three scatter plots depicting the relationship between independent variables and the PPD (Percentage of People Dissatisfied) value. In the PPD vs PMV (Predicted Mean Vote) graph, the X-axis shows the PMV, a metric that predicts how people perceive thermal conditions, while the Y-axis represents the PPD. It is observed that a significant number of high PPD values are concentrated in a central PMV range (around 0), suggesting that even in near-neutral conditions, many people may still be dissatisfied. In the PPD vs SET_value graph, the X-axis shows the SET (Standard Effective Temperature), which measures how perceived conditions affect human comfort, and the Y-axis is again the PPD. A high concentration of points is observed in a SET range close to 0.4, indicating that many people are dissatisfied with the thermal conditions in that range. In the PPD vs TCI_value graph, the X-axis shows the TCI (Thermal Comfort Index) and the Y-axis the PPD, and again a concentration of points is seen in a TCI range close to 0.4, suggesting thermal dissatisfaction in that interval. Overall, the graphs show that even in conditions that seem reasonably comfortable (such as PMV or SET at medium values), many people are still dissatisfied with the thermal environment. Chart 1: "Y and Fitted vs. X" - This chart shows the response variable (Y) as a function of the predictor variable (X). The blue dots represent the actual values of Y, while the red dots represent the values predicted by the regression model. The error bars show the uncertainty in the predicted values. Subplot 2: "Residuals versus TLC_value" - This subplot shows the residuals from the regression model, which are the differences between the actual values of Y and the predicted values. The residuals are plotted against the "TLC_value" values. Ideally, the residuals should be randomly distributed around the zero horizontal line, indicating that the model fits the data well. Subplot 3: "Partial regression plot" - This subplot shows the partial relationship between the response variable (Y) and the predictor variable ("TLC_value"), after accounting for the other variables in the model. The black line represents the linear relationship between Y and "TLC_value". Subplot 4: "CCPR Plot" —This subplot shows the relationship between the regression model residuals and the predicted values. The red line represents the linear relationship between the residuals and the predicted values. Subplot 5: "QQ Plot" - This subplot is a quantile plot that compares the distribution of the residuals to a normal distribution. If the residuals are normally distributed, the points on the plot should be close to the diagonal line. 4 DISCUSSION In the article about temperature monitoring and automatic fan control based on IoT with ESP32, the use of ESP32-DevKitC stands out for its flexibility and low cost[27]. In the project that was carried out, it is stated how efficient it is to carry out a project with Esp32 and Arduino sensors since it has a low cost. In the project carried out, sensors such as the DHT11, MLX90614, BMP180 are integrated. These devices automatically adjust the environmental conditions. In addition, the mobile application, database and connections through REST API allowed a strong stability in the project, making it better than other projects carried out. The autonomy of the system, by continuously adapting to factors such as temperature, humidity and other environmental parameters, makes it an effective tool to maintain thermal comfort without human intervention, especially in variable climates or environments where comfort is crucial. 5 CONCLUSION In conclusion, it was possible to have an improvement in the user's ability to maintain constant thermal comfort throughout the day thanks to the created system, granting automatic comfort stability. Demonstrating that the masters of Arduino and autonomous programming allow for providing well-being and community in people's daily lives. This project demonstrates the viability and effectiveness of the design and implementation of an IoT-based ESP32 autonomous smart device for thermal comfort detection and automatic regulation in Huancayo, Peru. The integration of advanced technologies such as temperature and humidity sensors with the processing and connectivity capabilities of the ESP32 allows the development of systems that not only improve thermal comfort in indoor environments, but also optimize energy consumption, thus promoting sustainability and user well-being. Tests carried out in different climatic conditions in Huancayo demonstrated that the device is able to effectively adapt to temperature changes and automatically adjust environmental conditions to maintain optimal comfort. In addition, the ability to remotely monitor and control through IoT connectivity opens up new possibilities for effective management of indoor environments, especially in areas with severe climates such as the mountains of Peru. The device can be deployed on a large scale, providing an effective and easy-to-use solution to improve the quality of life in homes, offices and other enclosed spaces. As the technology develops and improves, the system can be adapted to a wider range of environmental needs, positioning itself as a key tool for intelligent thermal comfort management. By adding the mobile application and website with the REST API of a single database to the project, it allowed us to have stability in the results and allow good data collection for subsequent analysis and results. Overall, the project not only achieved its initial objectives, but also opened the door to future innovations in the field of thermal comfort and home automation, marking an important step towards the development of smart technologies that meet the specific needs of different environments. REFERENCES 1. [1] Luis Vicente Colorado Franco and Narcisa Pilar Colorado Franco. 2020. 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