Learning IoT: Basic Experiments of Home Automation using ESP8266, Arduino and XBee

Sarah, Annisa; Ghozali, Theresia; Giano, Geraldo; Mulyadi, Melisa; Octaviani, Sandra; Hikmaturokhman, Alfin

doi:10.1109/smartiot49966.2020.00051

Cited by 20 publications

(13 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The designed NFT hydroponics is also equipped with an IoT monitoring system to monitor the values of each parameter. IoT system uses the ESP01 IoT Module [58] and the Blynk application framework as user interface [59]. Water circulation in NFT hydroponics is the same as circulation in an aquarium.…”

Section: A Nft Hydroponic Designmentioning

confidence: 99%

NFT Hydroponic Control Using Mamdani Fuzzy Inference System

Agustian

Prayoga

Santosa

et al. 2022

Journal of Robotics and Control

View full text Add to dashboard Cite

The Nutrient Film Technique (NFT) method is one of the most popular hydroponic cultivation methods. This method has advantages such as easier maintenance, faster and optimal plant growth, better use of fertilizers, and less deposition. The disadvantages of NFT include the consumption of electrical power and the faster spread of disease. Therefore, NFT requires a good nutrient control and monitoring system to save electricity and achieve optimal growth and resistance to pests and diseases. In this study, a nutrient control was designed with indicators of pH and TDS levels and equipped with an Internet of Things (IoT) based monitoring system. The control system used is the Mamdani Fuzzy Inference System. The output of the system is the active time of the pH Up, pH Down, and AB Mix nutrient pumps, which aim to normalize the pH and TDS of nutrient liquids. The experimental results show that one to three control steps are needed to normalize pH. One control step has a response time of 60 seconds, and it can prevent pH Up and pH Down oscillations. As for TDS control, the prediction of AB mix pump active time works accurately, and TDS levels can be normalized in one control step. Overall, based on surface control, simulations, and real experimental data, it is indicated that the control system operates very well and can normalize pH and TDS to the desired normal standard.

show abstract

Section: A Nft Hydroponic Designmentioning

confidence: 99%

NFT Hydroponic Control Using Mamdani Fuzzy Inference System

Agustian

Prayoga

Santosa

et al. 2022

Journal of Robotics and Control

View full text Add to dashboard Cite

show abstract

“…The employed Android application was created in the "MIT App Inventor" online environment, which was established by Google and is run by the Massachusetts Institute of Technology. This platform relies on the development of a graphical user interface based on a visual programming language (i.e., block arrangement), which enables users to drag and drop visual blocks to create the necessary software [46][47][48][49][50].…”

Section: System Design and Constructionmentioning

confidence: 99%

Design and Development of Control and Management Systems for Smart Homes

Baballe¹

2022

IJRMEE

View full text Add to dashboard Cite

The smart home and management system in this study are powered by D.C. batteries. Before running out of power, a fully charged battery can last for two to three days. When you turn on the system, the maximum temperature and the name of the study are shown on the LCD. Additionally, it will demonstrate that no one is in the house. As more individuals enter the house after you click the push button to enter, it will show on the Liquid Crystal Display (LCD) that you are welcome and that there are now more people inside. You get to decide how many people you let inside the residence. If you set the limit to 12, the door won't open again until someone quits the building by pressing the exit button before another person is allowed to enter. You can pick when you want the fan to turn on automatically by setting the maximum temperature. The fan in the house is used to lower the temperature if the weather is hot. The fan won't turn on until the maximum temperature of 30 °C has been reached, for example. Additionally, if everyone leaves the house, the fan and light will turn off automatically because nobody is inside. For safety purposes, there is a light in front of the house. It will automatically turn on if it becomes dark outside at night. The second LDR outside the home is in charge of controlling this light. The exterior light will turn off during the day if the LDR detects light, and it will turn on automatically at night if it detects dark. This is done for security reasons. Within the residence is the first LDR. It will switch on the lights when someone enters the house. No one will be able to exit the house before the light is turned off.

show abstract

“…This rapid development of the internet of things (IoT) across multiple domains starts from home automation to the environment, agriculture, health, and manufacturing systems. The application of IoT in home automation as a module trainer in [1], as home security and monitoring system in [2], like a remote control for home devices in [3]. The application of IoT in the environment as a real-time environment monitoring in [4], [5], as a weather monitoring system in [6].…”

Section: Introductionmentioning

confidence: 99%

Smart monitoring system using NodeMCU for maintenance of production machines

Pranowo

Artanto

2022

IJEECS

View full text Add to dashboard Cite

Maintenance is an activity that helps to reduce risk, increase productivity, improve quality, and minimize production costs. The necessity for maintenance actions will increase efficiency and enhance the safety and quality of products and processes. On getting these conditions, it is necessary to implement a monitoring system used to observe machines' conditions from time to time, especially the machine parts that often experience problems. This paper presents a low-cost intelligent monitoring system using NodeMCU to continuously monitor machine conditions and provide warnings in the case of machine failure. Not only does it provide alerts, but this monitoring system also generates historical data on machine conditions to the Google Cloud (Google Sheet), includes which machines were down, downtime, issues occurred, repairs made, and technician handling. The results obtained are machine operators do not need to lose a relatively long time to call the technician. Likewise, the technicians assisted in carrying out machine maintenance activities and online reports so that errors that often occur due to human error do not happen again. The system succeeded in reducing the technician-calling time and maintenance workreporting time up to 50%. The availability of online and real-time maintenance historical data will support further maintenance strategy.

show abstract

Learning IoT: Basic Experiments of Home Automation using ESP8266, Arduino and XBee

Cited by 20 publications

References 0 publications

NFT Hydroponic Control Using Mamdani Fuzzy Inference System

NFT Hydroponic Control Using Mamdani Fuzzy Inference System

Design and Development of Control and Management Systems for Smart Homes

Smart monitoring system using NodeMCU for maintenance of production machines

Contact Info

Product

Resources

About