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Improving the accuracy of emission monitoring in the Continuous Emission Monitoring System (CEMS) is crucial to support compliance with environmental regulations, especially in gas and steam-based power plants (PLTGU). At PT Jawa Satu Power's PLTGU, the purging system on the CEMS sample probe is still performed manually and limited to scheduled preventive maintenance, potentially reducing emission data reliability due to particle contamination. This study aims to design and simulate an automatic purging system based on a Programmable Logic Controller (PLC), taking into account technical parameters such as timer, gas pressure, temperature, and sample flow rate. The system design was carried out through the modeling of automatic control logic using CX-Programmer software, with a protection approach based on real-time conditions and timing. The design results show that the automatic purging system can improve cleaning consistency, reduce the risk of contamination, and enhance the integrity of emission monitoring data. This study is expected to serve as a foundation for developing a more applicable and integrated automated purging system for CEMS in the future.

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring.

The coffee farming sector in Gunungmanik Village, Indonesia, plays a significant role in the local economy. However, the monitoring and management of coffee crops remain largely manual and conventional, making it difficult for farmers to respond quickly to environmental threats such as drought, pests, or sudden temperature shifts. This research presents the development of iotgm.id, a web-based monitoring system integrated with Internet of Things (IoT) devices designed to provide real-time environmental data for coffee plantations. The system measures key parameters including temperature, soil moisture, and motion detection (as a proxy for pest activity), and delivers this data via a user-friendly web interface. It also features digital farm record management, real-time alerts for abnormal conditions, and data visualization through interactive dashboards. Field testing with local farmers showed that the system improves decision-making, speeds up responses to environmental changes, and reduces the need for direct field visits. Unlike earlier systems that often required technical expertise or focused on single parameters, this system offers multi-parameter monitoring and is accessible to farmers without advanced digital literacy. The system bridges the gap between sophisticated agricultural technologies and practical field-level application. It contributes to the adoption of precision agriculture in rural areas, offering a scalable model for broader implementation in similar contexts

The food security program involving chili cultivation in Pentur Village is hindered by inefficiencies in water use and suboptimal plant growth, primarily due to traditional irrigation methods that fail to consistently maintain ideal soil moisture and temperature. This issue is exacerbated by unpredictable environmental shifts, such as fluctuating weather patterns, and a lack of precise irrigation control stemming from technological limitations. To address this, a system for monitoring and regulating chili plant irrigation using IoT technology was developed. This system employs humidity and temperature sensors connected to an IoT platform like Blynk, enabling real-time observation of plant and environmental conditions. Data on soil moisture, air temperature, and humidity are stored in a database, and irrigation is automated based on soil moisture levels. The goal is to enhance water efficiency, minimize risks associated with over or under-watering due to environmental variations, and improve both yield and quality of the chili crop. This IoT-based system aims to simplify chili plant management for Pentur Village farmers and significantly boost agricultural output.

Proses budidaya jamur tiram sangat tergantung dengan kestabilan pada kondisi lingkungan, terutama suhu ruangan dan kelembapan yang harus di perhatikan oleh para petani.  Hal ini menjadi permasalahan ketika proses pemantauan dan pengendalian lingkungan secara manual dilakukan, membutuhkan tenaga yang kuat dan waktu yang cukup besar. Penelitian ini bertujuan Mendesain rancangan sistem monitoring dan kendali suhu ruangan budidaya jamur tiram secara otomatis dan jarak jauh berbasis teknologi Internet of Things (IoT) untuk para petani. Dalam proses sistem ini penelitian ini memanfaatkan sensor suhu dan kelembapan DHT11 sebagai input, mikrokontroler Arduino Uno sebagai pemroses data, dan modul ESP8266 sebagai pengirim data nirkabel ke aplikasi Android berbasis Blynk.  Adapun metode dalam penelitia ini digunakan pengembangan yang digunakan adalah Software Development Life Cycle (SDLC) model waterfall, dan menganalisis kebutuhan, perancangan sistem, implementasi, pengujian, hingga pemeliharaan. Hasil pengujian menunjukkan bahwa sistem mampu membaca suhu dan mengaktifkan blower (kipas) secara otomatis ketika suhu melebihi ambang batas, serta menampilkan data suhu dan status kipas secara real-time melalui aplikasi Blynk. Dengan adanya sistem ini, pemantauan dan pengendalian lingkungan budidaya jamur dapat dilakukan lebih efisien dan fleksibel dan mendukung produktivitas budidaya secara optimal.

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.

This paper presents the design and implementation of an automatic Virgin Coconut Oil (VCO) making device using an Arduino Uno microcontroller. Virgin Coconut Oil has gained popularity due to its health benefits and versatile uses in various industries. The traditional process of making VCO involves manual effort and precise timing, which can be tedious and inconsistent. The proposed automated system aims to streamline the VCO production process by integrating sensors, actuators, and a microcontroller to achieve precise control and monitoring of the process variables. The Arduino Uno microcontroller serves as the central unit for data acquisition, processing, and control, facilitating automation through programmed logic. Key components of the automated VCO maker include temperature sensors for monitoring heating stages, a motor for stirring, and relays for controlling heating elements. The system utilizes feedback loops to maintain optimal conditions during each phase of VCO production, ensuring reproducibility and quality. The design also emphasizes user-friendly operation, with an interface that provides real-time feedback on process parameters and allows manual intervention if necessary. Safety features are incorporated to prevent overheating and ensure operational reliability. Overall, the developed automatic VCO maker offers a practical solution to enhance the efficiency and consistency of VCO production, catering to both small-scale producers and commercial enterprises in the food and cosmetic industries

Accurate rainfall prediction is needed to improve the performance of land that always uses rainfall data. Data mining or often called knowledge discovery in databases (KDD) is an activity that includes collecting, using historical data to find regularities, patterns or relationships in large data. In predicting rainfall, there are several conditions that can be observed as reference data to predict rainfall, namely wind speed, temperature, and air humidity. In this research, a backpropagation artificial neural network prediction method is developed that can be used in predicting future rainfall. The backpropogation artificial neural network method that was built produced an accuracy value of 95.36%, a precision value of 90.50%, a recall value of 97.50% and an f-measure value of 92.00%

Fresh or rotten meat is a different matter. Damage to the meat will produce a distorted odor, mucus, discoloration in certain areas and an undesirable taste due to the formation of metabolism. The odor is described as fishy, ​​rotten, containing sulfur and like ammonia. In this research, the author discusses a system for identifying the condition of meat based on the odor that arises from meat in three states, namely odorless odor, fresh odor and rotten odor. Fresh odor is taken from meat odor that is within 1 (one) day after being cut and rotten odor is taken from meat odor that is on the 2nd day. In this study, the test sample meat was placed in a closed container at room temperature for 2 days. Data was taken for 2 days from meat odors of known type. The sensor array consists of eight sensors made of conducting polymer material. The polymer materials used are silicon DC-200, PEG-20M, 0V-101, 0V-17, DEGA, PEG-200, PEG-1540, and PEG-6000 mixed with Carbon black. A two-layer artificial neural net consisting of eight input nodes and three output neurons, was trained using the Kohonen algorithm with a training process that was completed in 4 iterations. From 20 tests, 10 times exposure to steam from fresh odor and 10 times exposure to steam from rotten odor, carried out alternately, it was found that the system failed twice. Thus, the system success percentage reached 95 percent.

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

In this final project the author discusses the problem entitled "Design of Smoke Detector and Room Temperature of SAP ERP Server at PT Apac Inti Corpora". This design aims to support the improvement of the security system in the server room with smoke and temperature detectors and microcontroller-based automatic countermeasures. Against the background of problems with sensors and countermeasures systems in the server room and lack of insight into sensor installation. This tool uses a gas sensor MQ-2 as a smoke detector, a DHT-11 sensor as a temperature detector, Arduino as a microcontroller that controls I/O, buzzer and LED as an alarm, a fan as a temperature controller, and an LCD to display conditions in the room. The output of the MQ-2 and DHT-11 sensors will be processed in a programmed microcontroller so that it can display conditions on the LCD. This tool will turn on the alarm and fan if smoke and high temperature are detected at the specified conditions.

Water is very important for all aspects of life on earth, agriculture is one of the fields that really need large amounts of water because of the use of water in the process of plant photosynthesis. Water that has good quality is if the water is not excessively polluted by harmful chemicals or minerals. One indicator that water is polluted is a change in temperature and pH (acidity) of the water. Temperatures that are too hot in the water will interfere with the growth of plants and other microorganisms. While the normal pH of water has a pH that ranges from 6.5 to 7.5. The quality of water and soil is very important in agriculture. The level of acidity (pH) and soil temperature are one of the things that affect plant fertility. Therefore, the quality of water and soil on agricultural land is one of the important things that needs special attention in its management. One solution so that water and soil quality can be monitored and managed efficiently is to utilize a Wireless Sensor Network based on the Internet of Things (IoT). The use of the ESP8266 Module as a WIFI module, is widely used by Internet of Things-based applications because the price is cheap so it reduces a lot of costs and has a fairly good speed of 80 MHz. This study aims to develop the concept of a Wireless Sensor Network by utilizing the ESP8266 module to monitor pH values using a pH Meter Analog Kit sensor and temperature from agricultural land using a DS18B20 Waterproof sensor and can be monitored at any time using a smartphone.

By looking at current technological developments that already use automatic sensors, the application of the concept to this system can be a solution for dealing with ornamental fish farming owners. In this research, a tool is made that can perform feeding, checking temperature, water turbidity, feed level, water level and water pump control, from this information will be sent to android by firebase automatically monitored and controlled anywhere via android. This tool is designed with ease of maintenance and is an extension of the existing tools. IoT technology is used to monitor online, based on Firebase and Nodemcu Esp8266. In this study, researchers used the research method of the Borg and Gall (1987) model from 10 steps to 6 steps. The results of this study were carried out by an expert validation test to get a value of 30 which means "Very Good (Valid)". While the effectiveness test by 10 users plus by experts and employee users get a total score of 35.16 which means the effectiveness test is classified as "Very Good (Valid)" it can be said that the new system is more effective than the old system.

Fires doesn’t know the place and time, they can happen anywhere and anytime. Some of the causes of fires are human error, electrical short circuit, cigarettes, stoves, etc. As a result, many parties suffered losses, both property, business entities, and casualties. Based on these problems, we need a system that is able to detect fires and take preventive action, namely notifications via the internet using the Blynk application. In this study, the parameters used are the temperature sensor, the MQ-2 smoke sensor and the flame sensor. The output of the system is a buzzer, LED, LCD, and Blynk app as notifications. The Fuzzy Logic method is applied to the system to control the Buzzer, LED, LCD and notification determinants to the Blynk application.

This research was carried out by comparing the DS18B20 sensor and the MLX 90614 sensor to detect the accuracy of detecting human body temperature which is used to detect Covid 19 symptoms. In this experiment, 10 trials were carried out with different human segments detected using the sensor. In the experiment, it was found that the MLX90614 sensor is more suitable to be used for development with an IoT-based system because it does not need to come into contact with the skin of the human body. The MLX90614 sensor will detect the temperature and change it to one Celsius unit then send it to the firebase database which will then be picked up by the android application which is held by the security officer so that the temperature can be known remotely. When the temperature is more than 38.5 Celsius it will turn on the buzzer sound which can be heard from a distance which indicates the temperature is above 38.5 Celsius and on android will also display a danger sign

The infrared detector (or IR detector) is an optoelectronic component and represents the core element of gas analyzers, flame sensors, devices of spectral analysis, as well as non-contact temperature measurement. pyroelectric infrared detectors work with  stabilization time  in a wide operating temperature range (-55 ... 85) °C, capable of measuring the slightest amounts of infrared radiation (as little as a fraction of a nW) with wavelengths between 1 µm and > 25 µm. The difference of the good pyroelectric or No good (NG) devices shown by graph of voltage offset operating that can check by manual using Digital Multi Meter or semi auto by using microcontroller One of importance measuring of IRD sensors  is Offset Voltage, stabilization of offset voltage indicate the sensor is stable with certain level value. Stabilization value measurement during measuring time means the average value not so much different with fluctuation value.  10 bit ADC on Atmega 328 that main microcontroller on Arduino Uno is capable to measure the Offset Voltage of IRD sensor and check the measurement values is within specification of IRD sensor.

The climatic chamber is a calibration medium for the thermohygrometer. This simple climatic chamber was built using the Arduino uno, DHT22 sensor, heater, and peltier. The climatic chamber was designed and manufactured well and cheaply. Climatic chamber testing of the design results is carried out to determine the success rate of the tool. Tests are carried out using the Madgetech data logger tool through monitoring or monitoring of temperature within a certain period of time. The results of temperature monitoring at two observed values, namely temperatures of 250C to 300C and temperatures of 300C to 350C, showed good results with the corresponding rhythm of temperature increase and temperature decrease. It's just that the decrease in temperature still takes longer than the increase in temperature. This shows that the heater can be said to be working optimally and the peltier is not fully working. So it is necessary to do further studies related to the peltier for the climatic chamber both in terms of number and characteristics.

This paper determines by simulation the temperature profiles of a thick carbon fiber/epoxy laminate during its cure process. The one-dimensional model of heat transfer is solved by using a finite difference numerical scheme. In the process, the same physical and thermal properties of materials used by ZhanSheng et al. are employed. The temperature is calculated through a judicious formulation and application of the Alternating Group Explicit (AGE) iterative method developed by Evans and Sahimi. A fourthorder Runge Kutta method is applied for the cure. The AGE scheme proves to be a viable iterative method with respect to stability, efficiency and rate of convergence.

Security aspects is needed in various fields of life today. Safety is becoming a concern for everyone. One of the important concerns is the security of the room. The indoor security system uses Raspberry Pi and RFID based Firebase Cloud Messaging and Motion Detection Camera, is a room security system that includes expensive equipment, so this device is designed for protection or robbery and also provides assistance in advance. . The security system in this room consists of several parts, namely Raspberry Pi as a brain system, selenoid door lock as an electric lock on the door, RFID system and CCTV camera as a detector of the amount of human movement, PIR sensor as a detector of human temperature, alarm as an indicator of intruders which transfers rooms, and database applications as user storage databases for security recorders