DHT11 Sensor Research Articles

Enhancing IoT Data Analysis with Machine Learning: A Comprehensive Overview

Machine learning techniques are essential for processing the vast volume of IoT data efficiently, improving performance, and managing IoT applications effectively. Machine learning algorithms play a crucial role in detecting malicious attacks and anomalies in real-time IoT data analysis, thereby enhancing the security of IoT devices. The integration of big data analytics methods with machine learning techniques can further enhance IoT data analysis, improving the performance of IoT applications and overcoming related challenges. Real-time data collection using sensors like DHT11 and Gas level sensors, coupled with machine learning algorithms, enables efficient analysis of IoT data, aiding in the identification of anomalies and attacks. The comprehensive overview of enhancing IoT data analysis with machine learning provides insights for future research, including exploring advanced machine learning algorithms and optimizing data preprocessing techniques to enhance IoT data analysis capabilities.

IoT Architecture for Vehicle Pollutant Gas Emission Monitoring and Validation through Machine Learning

This study proposes an IoT architecture for monitoring emissions of polluting gases in vehicles, in response to the growing concern about air pollution and global warming. The architecture is based on a node equipped with DHT22, MQ9, and MQ135 sensors to capture temperature, humidity, and gas emissions, respectively. This node effectively communicates through the LTE network to send the data to the ThingSpeak platform. An analysis of CO2, CO, and CH4 pollution levels is conducted using the collected data. These data are validated through the technical review of a test vehicle. Subsequently, an Artificial Neural Network (ANN) is trained using a specific database of CO2 emissions from vehicles in Canada. As a result, a high R2 of 99.2% is achieved, along with low values of RMSE and MSE, indicating that the model is making accurate predictions and fits well to the training data. The ANN aims to predict CO2 emissions and verify CO2 data from the IoT network. The architecture demonstrates its capability for real-time monitoring and its potential to contribute to pollution reduction.

Adaptive Classroom Berbasis IoT (Internet of Things), Manajemen Penggunaan Air Conditioner (AC) secara otomatis

Temperature and humidity are one of the comfort factors. According to the SNI standard, the comfortable temperature range is at 20.5°C-27.1°C. If the temperature is above 27.1°C, an Air Conditioner (AC) is needed to get the effective thermal comfort. AC installed in each PSTI FT UNRAM classroom is operated manually. This research implements Internet of Things (IoT) for automatic AC usage management. This IoT device is made using PIR sensor and DHT22 sensor, the MQTT protocol for data communication between the IoT device and the web system. Based on the testing scenario for the classroom containing students and the empty classroom that has been done, the IoT device is able to manage the AC usage automatically, so that the classroom can be called adaptive classroom. From the MOS testing that has been done, a value of 4.57 from a scale of 5, the system is feasible to use.

IoT revolutionizes orchid cultivation in Indonesia with precision and efficiency

The Orchidaceae family is highly valued in ornamental, perfume, medical, and cosmetic industries, but cultivation often fails due to human error. This research aims to design an IoT-integrated automation system to monitor and control key parameters such as air temperature, humidity, and moss moisture for orchid cultivation. Using the research and development method, we observed plant needs, reviewed relevant literature, designed an effective system, and tested sensor accuracy and system reliability. Results showed the DHT-22 sensor had a minimal error in temperature (0.9%) and humidity (2.1%) readings, and the soil moisture sensor had a 3.65% error. The system maintained optimal conditions, and the Blynk app effectively displayed data. This innovation reduces human error and enhances orchid cultivation efficiency, with potential applications in other sensitive plant systems. Highlight: Error Reduction: IoT system minimizes human error in orchid cultivation. Sensor Accuracy: DHT-22 sensors show minimal temperature (0.9%) and humidity (2.1%) errors. Optimal Conditions: Maintains air humidity 40%-80%RH and moss moisture 50%-80%RH. Keyword: Orchidaceae, IoT automation, sensor accuracy, environmental control, orchid cultivation

Optimized Smart Home Temperature Monitoring Using IoT

This research aims to monitor residential home temperatures using the Internet of Things (IoT) and Google Sheets. By adopting a Research and Development (R&D) approach, the study designs and tests a temperature monitoring tool with DHT11 sensors, NodeMCU ESP8266, and LCD displays. Data is integrated into Google Sheets for real-time access. The results show improved service efficiency, reducing waiting times to 0.41-2.45 minutes, with fewer waiting customers and lower utilization rates. This system enhances living conditions by providing easy temperature monitoring, recommending future studies to extend data collection periods for comprehensive analysis. Highlight: Efficient Monitoring: Real-time temperature data via Google Sheets. Integrated System: Uses DHT11 sensors and NodeMCU ESP8266. Research Implications: Extend data collection for thorough analysis. Keywoard: Temperature Monitoring, Internet of Things, Google Sheets, DHT11 Sensors, NodeMCU ESP8266

Website-Based Monitoring System for Methane (CH4) Concentration, Humidity, and Temperature

Abstract The research developed a monitoring system that focuses on the development of a system and the acquisition of its readings into a simple website. This research was conducted in an effort to obtain data that can be used for managing methane gas pollution in the environment. Methane gas (CH 4) is a natural gas consisting of one carbon atom and four hydrogen atoms. Methane gas is one of the greenhouse gases that contribute to global warming, while humidity and temperature can increase or decrease methane gas productivity. Therefore, in this research, a monitoring system was created for methane gas concentration using TGS2611 sensor, humidity and temperature using DHT11 sensor through the creation of a chamber connected to test materials such as cow dung digesters and tofu wastewater as a source of methane gas production. The results obtained indicate that, in the development of the monitoring system as a measuring tool, it successfully detects the concentration of methane gas, humidity and temperature for each test material using calibration through characteristic equation V = 0,5591 ln(n) − 2,2657. For data acquisition in the form of methane gas concentration parameter readings by the TGS2611 sensor, humidity and temperature by the DHT11 sensor to the ESP8266 microcontroller to be displayed on the serial monitor, LCD, and the website that has been created in real-time. To display the data acquisition of the monitoring system, each component of the system is connected. Starting from software, hardware, and test materials. Data acquisition begins with sensor readings by ESP8266 through a program from Arduino IDE displayed on the serial monitor and LCD. Once connected to wifi or a hotspot and the data is successfully sent, the data will be checked by notepad++ and entered into the phpMyAdmin website database for storage. From this database. The data will then be displayed on the website that has been created in real-time. Additionally, humidity and temperature affect the increase and decrease in methane gas concentration productivity.

Methane (CH4) Detection System Using The TGS2611 Sensor and MQ-4 Sensor

Abstract This research focused on cow dung digesters as measurement samples, utilizing the TGS2611 and MQ-4 sensors, both known for their affordability. The objective was to develop a low-cost gas sensor system for monitoring methane gas concentrations through a straightforward web-based data acquisition platform. The DHT11 sensor was employed to measure air temperature and humidity. The electronic sensor circuit in this research utilized a voltage divider circuit. Testing the performance of the low-cost gas sensor involved integrating it with an anaerobic digestion system. For both the TGS2611 and MQ-4 sensors, the graph illustrating the relationship between sensor voltage (volts) and methane gas concentration (ppm) formed a logarithmic or non-linear pattern. The measurement range for the system was around 4700 ppm to 6300 ppm for TGS2611 and 4000 ppm to 5100 ppm for MQ-4. The sensor sensitivity was determined as 0.5433 Volts/ppm for TGS2611 and 0.5639 Volt/ppm for MQ-4. The TGS2611 sensor exhibited a higher response to changes in methane gas concentration, while the MQ-4 sensor successfully detected methane gas within its designated range. Interestingly, the TGS2611 sensor accurately detected methane gas concentrations above its specified range. The gas sampling procedure involved automatic gas sampling in a vacuum chamber for measurement, a strategy potentially enhancing sensor robustness. This research successfully amalgamated sensor advantages, circuit control, and data analysis to realize an economical yet reliable monitoring system.

High-performance Smart Home System based on Optimization Algorithm

Background: With the recent COVID-19 pandemic, people have become increasingly concerned about their physical health. Therefore, the ability to monitor changes in the surrounding environment in real-time and automatically improve the environment has become a current hot topic to improve the overall health level. Objective: This article describes the design of a high-performance intelligent home system that can simultaneously perform monitoring and automatic adjustment functions. Methods: The ESP8266 was used as the core controller, and the DHT11 and G12-04 sensors were used to collect data, such as temperature, humidity, and ambient light intensity. The sampling frequency was increased and the sampled data were processed to improve data accuracy. The sampled data were wirelessly transmitted to a PC or mobile terminal for real-time display. When the sampled data underwent sudden changes, an alert message was sent via the mobile terminal. Based on the real-time changes in ambient light, an improved lighting brightness adjustment algorithm combining bang-bang and single neuron adaptive PID control was used to adjust the lighting brightness. Results: After testing the system designed in this paper and analyzing the errors compared to standard values, the temperature measurement error ranged from 0% to 0.01107%, and the humidity measurement error ranged from 0% to 0.03797%. The improved algorithm was simulated and tested using MATLAB software and compared with traditional PID algorithms and single-neuron adaptive PID algorithms. The improved algorithm did not overshoot during adjustment, and the system reached a steady state much faster than traditional algorithms. Conclusion: The system showed good performance in real-time, stability, and accuracy, fully demonstrating the effectiveness of the devices and algorithms used in the system. This provides ideas for the design and improvement of future smart homes.

Rancang Bangun Sistem Monitoring Cuaca Berbasis Google Spreadsheet Untuk Nelayan Di Wilayah Pesisir Pantai

Coastal areas are vital areas for fishing activities, and the weather in this area plays a very important role in the safety and efficiency of fishermen's operations. Fishermen on the coast often face the challenges of weather that is changeable and can be very extreme, including strong winds that can cause high waves and unsafe sea conditions. Therefore, the development of a Google spreadsheet-based weather monitoring system for fishermen in coastal areas is very relevant and strategic to support safer and more productive fishing activities. This research aims to make it easier for fishermen to monitor the weather in coastal areas in real time. Testing is carried out by running the system for observation for a predetermined time duration. This research uses an anemometer, DHT11 and raindrop sensors connected to a NodeMCU ESP32 microcontroller to send data to a Google spreadsheet, with readings of wind speed, temperature, air humidity and rain values. This research was carried out at the Nusantara Prigi fishing port, Trenggalek, challenging the work of anemometer sensors, DHT11 and raindrop sensors. Testing of tools and data obtained by comparing data on wind speed, temperature and air humidity using a digital anemometer and digital thermometer hygrometer humidity. The results of this research are that a Google spreadsheet-based weather monitoring design for fishermen in coastal areas can monitor wind speed, air humidity, temperature and detect rain online using a spreadsheet application and functions well with an average error accuracy of 3%.

DESIGN A CIRCUIT FOR HUMIDITY PREDICTION USING CMOS TECHNOLOGY AND IMPLEMENTING ANN

This research paper presents the knowledge about Humidity prediction model based on Arduino Uno, DHT11 Sensor and 16*2 LCD display. The model combines real-time data acquisition with predictive machine learning algorithm to estimate future humidity levels. The microcontroller of Arduino processes from the DHT sensor and shows the predicted and actual humidity data in the LCD display. This system gives a low-cost and user-friendly solution for humidity monitoring in various environments. Keyword: Arduino UNO, DHT-11, 16*2 LCD

Sistem Kontrol Otomatis dan Efesiensi Energi Listrik dari Penggunaan Air Cooler Berbasis IOT

Air Coolers are the right choice as an air conditioning tool compared to AC because they are much more energy efficient and environmentally friendly. In this system, the Air Cooler on/off function will be controlled automatically based on the room temperature detected by the DHT22 sensor. If the room temperature reaches 24o Celsius, the Air Cooler will be off. Then this automatic system is also able to control the on/off of the Air Cooler based on the number of people entering and leaving the room using the IR Proximity sensor. The Blynk application connected to a smartphone allows for regular monitoring of the voltage and current used by the Air Cooler. Then a comparison of the electrical energy used by the Air Cooler is carried out before and after using the system that has been designed. The conclusion obtained is that the system designed is able to control automatically and save electrical energy from using the Air Cooler.

IOT BASED PLANT MONITORING SYSTEM

The internet of things (IOT) has various use in Agriculture filed. Main moto is making IOT based Plant monitoring system is monitor plant growth system and control plant monitoring growth. In this system using DHT11 sensor, Touch sensor, soil moisture to monitor and collecting data. collect the data through the real time basic and send it through the cloud there is alert system if there anyone touches the plant then you have given an alert through an Alert Notification, On your mobile phone. there is one sensor dh11 to you know the real time temperature in what temperature is our environment if there is less soil moisture in soil, you again receive an alert message to Turn on the motor through your phone. This all about our project. KEYWORDS: Plant monitoring, Soil monitor, Alert system, Automation monitoring Plant,

Smart Temperature and Humidity Tracker

The HC-05 Bluetooth module for data transmission, the things of network (IoT) smart temperature and humidity tracker presents an economical and effective Wireless Bluetooth Temperature and Humidity Monitoring System. Real-time temperature is offered by the system in a variety of situations, including homes, workplaces, warehouses, and agricultural settings. A dependable communication link between the monitoring devices and a central monitoring station—usually a computer or smartphone—is supplied by the HC-05 Bluetooth communication. The particulars for monitoring system's creation and implementation are covered in detail, with an emphasis on how the HC-05 Bluetooth modules are integrated with temperature and humidity sensors. The system design makes sure that data is acquired, processed, and transmitted in order for users to obtain accurate and timely environmental data from a distance. Important aspects of the system. The Wireless Bluetooth Temperature and moisture sensing system, in conjunction with Network of Things(IOT)-based smart temperature and humidity tracker, essentially ushers in a new era of environmental monitoring. By combining hardware and software components in a seamless manner and adding strong security measures, the system gives users practical information about temperature dynamics, which in turn promotes a more sustainable and healthy living and working environment. Keywords—HC-05 Bluetooth, NodeMCU ESP8266, DHT11 sensor, Temperature monitoring, Thingspeak.

Air and Water Quality Indexing and Environment Monitoring

The current state of the environment continues to be a pressing global matter resulting from various human activities that release harmful substances posing a threat to living beings. To combat this issue advancements in technology have paved the way for the creation of an Internet of Things (IoT) based Water and Air Quality Monitoring System providing real-time data on environmental conditions. Through web and mobile applications individuals can easily access this system and view graphical representations of water and air quality readings. This innovative system involves sensor nodes strategically placed in different locations collecting field data and evaluating it against the set standards in India. For water monitoring sensors such as the Turbidity Sensor PH Sensor DHT 11 and TDS Sensor are utilized while for air quality the DHT11 sensor MQ-7 sensor and MQ-135 sensor play a crucial role. With this advanced monitoring system timely and accurate information on the state of the environment can be obtained aiding in taking necessary measures to combat pollution

IoT ENBALED SMART AQUARIUM FOR MONITORING THROUGH SENSORS

The development of an IoT-enabled smart aquarium system offering real-time monitoring and automated control of crucial environmental parameters. The core of the system lies in the ESP8266 microcontroller, facilitating seamless internet connectivity and data processing. Water quality assessment is achieved through a turbidity sensor, detecting suspended particles indicative of potential pollution. Environmental conditions are monitored using a DHT11 sensor, providing data on both temperature and humidity – essential factors for maintaining a healthy habitat for specific fish species. For automated lighting control mimicking natural day/night cycles and preventing excessive algae growth, a Light-Dependent Resistor (LDR) is implemented. The LDR adjusts aquarium lighting based on ambient light levels. Finally, a relay module controls the operation of a water pump, ensuring optimal water circulation and distribution of nutrients throughout the aquarium. While an I2C LCD connected to an Arduino Nano provides local data visualization within the aquarium setup, the ESP8266 transmits sensor readings to a user-friendly platform accessible remotely through a mobile application or web interface. This allows for convenient real-time monitoring of water quality, temperature, humidity, and lighting conditions. The system can be further programmed to generate alerts when critical parameters deviate from the ideal range, enabling proactive user intervention to maintain a healthy environment. This project demonstrates the potential of IoT technology to create a more automated, efficient, and user-friendly system for maintaining a thriving aquatic ecosystem. KEYWORDS: IoT (Internet of Things), Smart Aquarium, ESP8266, Turbidity Sensor, DHT11 Sensor, LDR(Light-Dependent Resistor), Relay Module, Water Pump, I2C LCD, Arduino Nano, Real-Time Monitoring, Automated Control, Remote Access, Mobile Application, Web Interface, Water Quality, Temperature, Humidity, Light Control, Aquatic Environment.

Flood early warning system at Jakarta dam using internet of things (IoT)-based real-time fishbone method to support industrial revolution 4.0

This research aims to develop an effective flood early warning system to provide timely information to the public and support the government in disaster management. The Raspberry Pi mini-computer functions as the central control, collecting data from the Water Level Sensor to measure water height, the Ultrasonic Sensor for further monitoring, the DHT11 Sensor to monitor temperature and humidity, and a Buzzer as an audible warning device. The research method involves review of the literature and data acquisition from related journals. These data are utilized to design an Internet of Things (IoT)-based flood detection tool with the Raspberry Pi minicomputer as the main controller. The system can be implemented in vulnerable locations such as reservoirs, sluice gates, and rivers, as part of the Smart City and Smart Environment concepts. The test results indicate that the developed early warning system, integrating the Raspberry Pi minicomputer, the Water Level Sensor, the the Ultrasonic Sensor DHT11 Sensor, and Buzzer, approaches perfection. Real-time information is transmitted through the Twitter social media platform, which is shown to be more effective than manual notifications. The system can provide accurate early warnings, reduce flood-related damages, and positively contribute to flood prevention and disaster management efforts. This research is expected to make a significant contribution to improving the community and government preparedness for future flood disasters.

Sign Recognition and Voice Conversion Device for Dumb

This project proposes a comprehensive hardware setup for home automation and environmental monitoring. The system includes components such as a Bluetooth module for remote control, a voice module (APR9600) for audio feedback, an LCD for display purposes, relay modules for controlling electrical devices, bulbs with holders for lighting, a CPU fan for temperature regulation, speakers for audio output, and a 5V power supply for operation. The core functionality of the system revolves around the integration of flux sensors for environmental monitoring. When flux sensors detect specific conditions, predefined audio signals are played through the voice module. These conditions correspond to six distinct signs, facilitating real-time alerts and notifications. Moreover, the system offers remote control capabilities through Bluetooth connectivity, enabling users to manage lighting and fan operations conveniently. Additionally, temperature monitoring is implemented using a DHT11 sensor, triggering the activation of the CPU fan when temperature thresholds are exceeded. Furthermore, an LCD display enhances user interaction by providing visual feedback and status updates. The project utilizes Arduino UNO as the central processing unit and incorporates 12V 1A adapters for powering specific components. Connectors and power cables are utilized for seamless integration and electrical connectivity. Overall, this project presents an integrated solution for home automation and environmental monitoring, offering flexibility, convenience, and enhanced user experience.

Design an Automatic Condenser in Swallow Bird House

This design is a system development carried out by swallow breeders in stabilizing the temperature and humidity of swallow houses. This design uses the principles of the Internet of Things (IoT), which will monitor temperature and humidity through internet media. This design aims to make a temperature and humidity control system in the swallow house automatically and find out the level of accuracy of temperature and humidity readings in the design made. This design uses a Wemos D1 Mini Board microcontroller that controls components such as DHT22 sensors, DS18B20 sensors and relays. The result of this design can control the condenser automatically, when the temperature and humidity are above the standard temperature, it will turn on the condenser automatically.

PENGONTROLAN ENERGI PANAS DAN KELEMBABAN MENGGUNAKAN SENSOR DHT22 DAN ESP32 PADA PROSES FERMENTASI TEMPE GEMBUS

The fermentation process of tempe embus with conventional methods is highly dependent on weather conditions and requires heat energy (temperature) 25°C - 35°C within 36 - 48 hours. This research aims to stabilize the heat energy and reduce the fermentation process time to get quality tempeh production results in a short time. The research method used is the experimental method by making an automatic temperature and humidity controller and testing its performance. This tool works using the DHT22 sensor and ESP32 microcontroller as the control center. Temperature automation is done with two conditions that are used to regulate lights and fans. If the fermentation temperature is lower than the setpoint, the lower light and upper light turn on, if the temperature rises, the upper light turns off and the fan turns on, to keep the temperature within the pre-set setpoint value. This research shows that the temperature and humidity control device operates stably in the temperature range of 32°C to 35°C. At these temperature conditions, the fermentation process runs stably. At that temperature condition, the fermentation process of tempe embus lasts 16 hours, with testing of color, taste, and smell for the best quality category Tempe.

Smart Home Warning System Using ESP- 32 Cam

Abstract: Smart home warning systems using ESP32-CAM have emerged as a pivotal solution in today's landscape, addressing the growing need for remote monitoring and security. By harnessing the power of ESP32-CAM alongside a suite of compatible sensors and actuators, homeowners can exercise vigilance over their properties from afar. With sensors like DHT22, MQ2, and fire and IR sensors seamlessly integrated, the system stands ready to detect a myriad of potential threats, from temperature fluctuations to gas leaks and even unauthorized intrusions. Leveraging IoT for wireless connectivity, this system facilitates realtime communication, empowering homeowners with immediate alerts and notifications, including visual evidence via Telegram in case of security breaches.