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This study investigates the performance of Internet of Things (IoT)-based monitoring systems using a mobile hotspot and IoT sensors for temperature and humidity data transmission. The research is based on the IoT concept, which enables electronic devices to communicate and exchange data through internet networks without direct human intervention. System performance was evaluated using standard Quality of Service (QoS) parameters, including throughput, packet loss, delay, and jitter. The experimental setup utilized a NodeMCU ESP32 microcontroller and a DHT22 sensor, with measurements conducted at various transmission distances through wireless communication media. The objective was to determine the reliability of hotspot connectivity and sensor communication in supporting IoT applications. The results indicate that the optimal performance was achieved at a distance of 20 meters using a 40-lambda variation. Furthermore, the communication signal between the ESP32 device and the mobile hotspot remained detectable up to a maximum distance of 32 meters. These findings demonstrate the effectiveness of the proposed IoT system for environmental monitoring applications within specific transmission ranges.

Early detection of a potential heart attack is a crucial step in preventing sudden death from heart disease. This research aims to develop an Internet of Things (IoT)-based health monitoring system capable of measuring vital body data in real time and predicting the likelihood of a heart attack from CSV data obtained from sensors, integrated through RapidMiner as learning data using a machine learning algorithm, the Support Vector Machine (SVM). The system was built using an ESP32 microcontroller connected to a MAX30102 sensor to measure heart rate and finger oxygen levels (SpO₂), as well as a DHT22 sensor to measure temperature and humidity. The resulting data is sent to the Blynk application to display real-time data according to its parameters. The initial prediction logic was developed using a rule-based method based on medical thresholds for four vital parameters. The data was then used to train an SVM model as a classification system to detect potential heart attacks. Test results showed that the system can identify abnormal conditions with a good level of accuracy and provide early warnings based on changes in vital parameters in real time. This system is expected to be an initial solution for personal health monitoring, especially for individuals at risk of heart disease. It can be further developed with cloud integration and automatic notifications to users' devices.

This study aims to design and develop a functionally efficient and operationally effective Internet of Things (IoT)-based air quality monitoring system for radiology departments. The system utilises a DHT22 sensor integrated with an ESP32 microcontroller to monitor the temperature and humidity of diagnostic rooms in real time, and to display the data via the UdaraKu mobile application. The research method employed a quantitative experimental approach focused on measuring system performance, specifically the accuracy of the temperature and humidity sensors. The research model used was the Research and Development (R&D) method, aimed at transforming conventional air quality monitoring in radiology into a real-time digital system based on IoT. The research results indicate that the IoT-based monitoring system is capable of maintaining room temperature and humidity stability within the ideal range, namely 22–24°C and 50–60% RH, in accordance with international standards. This improvement in environmental stability has a direct impact on reducing noise in digital radiography images, as evidenced by an increase in the Signal-to-Noise Ratio (SNR). Instrument validation demonstrated a high level of reliability with a Cronbach’s Alpha value of 0.848, reinforcing the reliability of the data and the system. Overall, the IoT-based air quality monitoring system has proven effective in controlling noise in digital radiography images, improving the quality of diagnostic services, and supporting patient safety principles and operational efficiency within radiology departments.

Manual post-harvest paddy stirring requires significant time and labor and often results in uneven mixing, which can affect grain quality. To address this issue, this study designed and implemented a prototype of an Internet of Things (IoT)-based paddy stirring robot to simplify the process and improve efficiency. The system utilizes an ESP32 microcontroller as the main controller, DC motors as the stirring mechanism, and an IoT module for wireless connectivity to a mobile application. The research stages included hardware design, control system programming, IoT platform integration, and performance testing. Testing was conducted to evaluate response time, mixing uniformity, and power consumption. The results showed that the system could be operated remotely via a local Wi-Fi network with an average delay of less than 1 second, enabling real-time control. The prototype successfully stirred 0.3 kg of paddy with a mixing uniformity rate of 92% and an average power consumption of 12 watts. The application of IoT in the paddy stirring mechanism significantly improved time efficiency, reduced manual labor requirements, and maintained grain quality compared to traditional methods. These findings indicate the potential for further development into a large-scale automated paddy processing system with integrated humidity and temperature sensors for real-time quality monitoring, supporting the modernization of post-harvest processing through digital technology.

The DH Building of the Electrical Engineering Study Program at Udayana University faces significant challenges in energy efficiency, as it still relies on conventional electrical systems. User negligence, such as forgetting to switch off lights and air conditioners (AC) after use, often results in unnecessary energy waste and increased operational costs. This issue highlights the urgent need for smart solutions capable of automating energy management, reducing waste caused by human error, and supporting the creation of a more efficient and sustainable campus environment. To address this problem, this study designs and implements a smart building system based on the Internet of Things (IoT). The system employs a NodeMCU ESP32 microcontroller as the main processing unit, integrated with a series of sensors including a DHT22 sensor for monitoring temperature and humidity, an MQ2 sensor for smoke detection, a PIR sensor for motion detection, and a PZEM-004T sensor for monitoring energy consumption. Control of electronic devices such as lights and AC units is carried out both automatically and manually through relay modules connected to the system. All sensor data and control functions are accessed via a web interface developed using the Laravel framework and a MySQL database. The testing results indicate that the designed system was successfully implemented and functions as expected. Sensor testing demonstrated high accuracy compared to standard measuring instruments, while the electronic device control system achieved an average response time of approximately 3.6 seconds, proving its reliability. Overall, the system provides a comprehensive solution for energy consumption monitoring and control, while also enhancing comfort and safety in the DH Building, in line with the goals of energy efficiency and facility modernization.

Maintaining optimal temperature in server rooms is critical to ensure the reliability and longevity of IT equipment. Overheating can lead to system failure, data loss, and increased maintenance costs. This study presents the design and implementation of an IoT-based temperature monitoring application tailored for server room environments. The system utilizes a DHT22 temperature and humidity sensor connected to an ESP32 microcontroller, which transmits real-time data to a cloud-based dashboard via Wi-Fi. The data is visualized through a web interface that allows administrators to monitor room conditions remotely and receive alerts when temperature thresholds are exceeded. The application was tested in a simulated server room environment over a two-week period. Results demonstrated stable performance with accurate temperature readings and reliable alert delivery. The system's scalability, low cost, and ease of deployment make it a practical solution for data centers, schools, or small businesses. This IoT-based approach offers an efficient and automated method to enhance server room monitoring and improve response time in managing thermal risks.

The need for urban communities to consume vegetables is increasing. This has caused people to start cultivating vegetables using hydroponic techniques. However, due to their busy activities, they do not have enough time to monitor and control hydroponics, which must always be in ideal conditions. This paper designs and implements an Internet of Things-based monitoring system to help hydroponic owners monitor their hydroponics anywhere and anytime. The built system requires a monitoring device assembled using a NodeMCU ESP8266 microcontroller, a pH detection detector sensor, and a DHT22 temperature and humidity sensor. This system uses the Mamdani Fuzzy Logic algorithm to determine warnings to be displayed on the application interface when the water pH, temperature, and humidity are in certain conditions. The Mamdani Fuzzy Logic algorithm can interpret environmental data into a warning that humans can easily understand, even if they lack technical expertise. In addition to being able to help monitor, this system also allows owners to find out what elements need to be added or changed for their hydroponic place. Our evaluation results show that the defuzzification stage in the application has high accuracy, which is 99.92%, compared to Matlab’s results.

Socks are essential daily wear that require special care, including an effective drying process to prevent unpleasant odors and the growth of bacteria and fungi. Conventional drying methods often face challenges, especially in high-humidity environments or during unfavorable weather conditions. This study aims to design and develop a prototype sock dryer that is more efficient and hygienic. The prototype utilizes a combination of a heater, UV lamp, and humidity and temperature sensors to ensure optimal drying without damaging fabric fibers. A microcontroller-based control system using Arduino Uno is implemented to regulate device operation and monitor sock conditions during drying. Testing results indicate that the device effectively dries cotton socks in damp conditions faster than conventional methods. Additionally, the sterilization feature with a UV lamp helps reduce the risk of microbial growth. This innovation is expected to provide users with a practical, hygienic, and efficient way to dry socks without depending on weather conditions. Further development can be carried out to enhance drying capacity and energy efficiency.

This research aims to design and build a system for stirring and monitoring temperature and humidity for ESP32-based compost fertilizer. This system uses an ESP32 microcontroller to control compost mixing and monitor temperature and humidity conditions in real- time. Data obtained from sensors will be sent to the server for monitoring via Blynk. The implementation of this system is expected to increase the efficiency of the composting process and produce high quality compost through optimal monitoring and mixing.

Closed house chicken coop is an innovation from the development of technology in the livestock sector. In closed house chicken coops, many arrangements and adjustments to environmental conditions in the chicken coop are carried out which are expected to increase broiler chicken production. In this study, researchers created a centralized control system on 2 closed house chicken coops to make it easier for broiler chicken entrepreneurs to monitor and control the closed house chicken coops owned by the entrepreneur through one place, without having to go directly to the closed house chicken coop to monitor and control the chicken coop which of course will be quite draining time and energy. This study uses Haiwell Cloud Scada as an interface device connected to the Arduino Nano microcontroller, DHT-22 sensor as a humidity and temperature detector sensor, MQ-135 sensor as an Ammonia gas detector, water level sensor as a reader of the remaining chicken drinking water level, IR sensor as a reader of the remaining chicken food level, DC fan which has 2 functions, namely inlet and exhaust in the chicken coop. Servo motor as a silo damper controller to fill chicken food from the silo to the chicken feeder located in the chicken coop.

Durian is one of the leading fruit commodities with high economic value in various tropical regions, including Indonesia. However, the durian cultivation process often faces challenges related to unstable environmental conditions, such as temperature fluctuations, soil moisture, and nutritional deficiencies which can affect the level of plant fertility and the quality of the fruit produced. Therefore, an effective and efficient monitoring system is needed to optimize durian plant care. This research aims to develop a fertility monitoring system for durian trees using Internet of Things (IoT) technology which can help farmers manage the environmental conditions of plants in real-time. The designed system uses various sensors, such as soil moisture sensors, air temperature and humidity sensors, light intensity sensors, and soil nutrient sensors, to collect relevant environmental data. The data obtained from these sensors is then processed by a microcontroller and sent via the IoT network to a cloud-based storage platform. The trial results show that this system can monitor environmental conditions with high accuracy and provide appropriate maintenance recommendations, thereby increasing efficiency in managing durian plants.

As time goes by, the rapid development of technology has brought various conveniences to people's daily activities.  An example of the continuation of technology is microcontrollers and electronic devices that can be connected to the network. One of them is the industrial sector in the PLTS plant at the 7 Mwp On-Grid PLTS Pt. Infrastructure Terbarukan Cemerlang Sengkol which has PV Box generating equipment that requires temperature and humidity control to determine the cause of corrosion that occurs in the PV Box.This study is intended as a solution in monitoring PV Box generating equipment. This technology development uses the Internet of Things (IoT) which combines the physical and virtual worlds. In this research, the method used is the experimental measurement method, making the system created more real and detailed. In research using DHT11 equipment which has the advantage of being able to estimate temperature and humidity. NodeMCU ESP32 as a microcontroller connected to the blynk platform via the internet functions to manage hardware, show evidence of sensors, secure data, depict data, and others. The results of the research on designing a temperature and humidity monitoring system at the 7 Mwp On-Grid PLTS Pt. Infrastructure Terbarukan Cemerlang Sengkol were successfully created and produced positive effects by being monitored using the blynk platform. This research was carried out in real time using a cell phone wherever you are. This research shows that temperature measurements from the DHT11 sensor obtained an average temperature of 31.78%, while the average humidity value was 85.96%, which indicates that the room being measured had high humidity. By considering these two findings, it can be concluded that the cause of corrosion in the room is high humidity and redox reactions from various substances in the environment.

Broiler chickens are livestock whose growth is influenced by environmental temperature. The temperature of the chicken coop that is not suitable can affect the decrease in productivity and cause death in broiler chickens, so that the temperature setting of the cage must be considered. The design of this temperature and humidity monitoring system uses a nodemcu ESP8266 microcontroller and an arduino uno. If the measured temperature exceeds the set temperature limit, the system will send an SMS to the smartphone so that the cage officer can take appropriate action.

Honey is a natural liquid that contains a lot of sugar produced by bees (genus Apis) from flower nectar and has a sweet taste. Honey contains a multitude of benefits that are good for the body, including being a source of nutrients, improving body metabolism, anti-bacterial, and others. The purpose of designing the Honey Harvest Monitoring System with ARDUINO-based IOT is to help breeders maximize honey harvesting results. This study aims to design an intelligent system for controlling the temperature in bee hives, humidity in bee hives, and monitoring honey yields, measuring the temperature and humidity of the storage room using DHT 11 sensors, and monitoring honey harvest time using Load Cell sensors. The temperature and humidity controller in the cage uses a blower/fan. Sensor data will be processed using the Wemos D1 R1 microcontroller and then sent to an Android application via the internet network using a real-time Firebase database so that it can be accessed anywhere and anytime. The way this system works is that if the room temperature is >38 degrees Celsius, the blower/fan will turn on, and will turn off if the temperature is 40%, the artificial window will open and will close if the humidity is