ThingSpeak Platform Research Articles

Monitoring system of photovoltaic panels using 433 MHz radio frequency module

In this article, we presented an innovative study that allows direct monitoring of the main parameters of photovoltaic panels. Our study focuses on the skills of radio frequency modules to send the main parameters of photovoltaic cells. In this paper, we used an Esp32 microcontroller in the radio frequency (RF) transmitter block and an Arduino Uno board in the receiver block, in addition, to measure current, we used a current sensor, and to measure voltage, we implemented a voltage divider. After that, we calculated the power and the energy. Note that the various measured and calculated values are stored and used via the ThingSpeak platform. In comparison with similar studies, our achievement presents an` effective and inexpensive solution because its operating principle is based on radio frequency transmission, so it works perfectly even in the absence of the internet. Finally, our study was very well tested without detecting any abnormalities, and the results obtained are a perfect witness to our success.

Design and Development of Real-Time Data Acquisition of Photovoltaic Panel Parameters via IoT

Abstract In recent years,there has been an urgent need in world for electricity. It has being increased constantly with the expansion of energy consumption via traditional energy sources which are depleting. The world has needed to turn to alternative energy, which is represented by renewable energy. The most important and most efficient of these is solar energy, and to get the maximum value of this energy with the highest efficiency, there should be direct monitoring of the performance of these solar panels. So, in this study, the Internet of Things (IoT) was used as a remote monitoring system to obtain the main factors like load current, terminal voltage, consumption power, temperature, humidity, and light intensity. The values were real and accurate, depending on the use of Adriano and sensors to measure the above-mentioned determinants and then using Wi-Fi technology to send the data that was processed in the circuit. Then the thing speak platform was used to display, analyze, and store the results in real-time

Remote monitoring of oil pipelines' cathodic protection system via GSM/GPRS modem and the thingspeak platform

Remote monitoring of oil pipelines' cathodic protection system via GSM/GPRS modem and the thingspeak platform

Intelligent home energy management using Internet of Things platform based on NILM technique

Due to the continuous increase in the global energy demand, it is essential to find solutions to improve energy efficiency. Non-intrusive load monitoring (NILM) is one of the most prominent energy management techniques, and it allows consumers and companies to manage their energy consumption efficiently. The energy footprint of residential buildings is monitored, and the total electrical consumption is disaggregated into appliance related signals through NILM. The NILM applications are working based on the “energy awareness” concept where the consumer receives some itemized information from the application to reduce its consumption and thus improves energy efficiency. This paper presents an Internet of Things (IoT) based criterion by using NILM to transform modern buildings and homes into energy-efficient and smart ones. The Factorial Hidden Markov Model (FHMM) is used as a NILM technique to disaggregate all appliances’ total power consumption into individual appliance load consumption by giving the power as an input. The FHMM is applied on reference energy disaggregation dataset (REDD) datasets, and a comparison is made between the measured and predicted values of appliances’ power consumption. Instant visualization of live data is then created using the ThingSpeak platform, which sends alerts through Twitter social media application to the consumer to control his consumption. The consumption behavior is assessed according to the time of use to make an energy saving based on the cost of electricity.

IoT Based Distribution Transformer Health Monitoring System

Abstract: This paper is about acquiring real time status of transformer. Transformer plays an important role in power system so, it is essential to monitor its condition for uninterrupted operation of any distribution network. This paper presents an IoT (Internet of Things) based health monitoring system, in this paper NodeMcu has been selected as the processor for transmitting the data sense by sensors, while Thingspeak platform has been used for the display of output data. Adoption of IoT technique in transformer may help for continuity of power supply. This low-cost system can be installed in the transformer to get monitored remotely, which not only determine health condition but also to assist in predicting the life span as well.

Design and analysis of water quality monitoring and filtration system for different types of water in Malaysia.

Water pollution always occurs in Malaysia due to industrial, construction, agriculture, and household activities. River pollution can disturb water supply that eventually affects business and household activities. Thus, water quality monitoring system is needed to detect contaminated water. We developed a water quality monitoring and filtration system controlled by Arduino. The proposed system was designed in Proteus software and ThingSpeak platform was used for real-time monitoring. The main objective of the study was to compare water quality of river, lake and tap water in terms of pH, temperature, turbidity, electrical conductivity and oxidation–reduction potential. If the water quality was not satisfied, the water sample would be filtered through filtration system. Water turbidity level, pH, temperature, electrical conductivity, and oxidation–reduction potential for filtered and nonfiltered water were compared and analyzed according to international and national water quality standard. Besides that, statistical analysis such as box plot and one-way analysis of variance test was applied to validate data from the system. The real-time water quality monitoring system was implemented through data storage, data transfer, and data processing. The system was connected to wireless fidelity whereas the output data was sent to the user and monitored by ThingSpeak. The system can be further upgraded and scaled up to be applied in the main tank at our home or factory. The outcome of this research can be used as a reference for further study on lake and river pollution monitoring system.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13762-022-04192-x.

Microcontroller-Based Water Quality Monitoring System Implementation

So far, Regional Drinking Water Companies (PDAMs) have used conventional methods by taking water samples, measuring all water quality parameters, and analyzing them one by one. In addition, the process of making conclusions on water quality has not been integrated so that it can cause misclassification of water quality and prolong the work. In this study, an expert system was designed to monitor water quality that works in real time so that it can be accessed anytime and anywhere. The water quality analysis process is carried out with a fuzzy classifier realized using Arduino Mega 2560. The fuzzy input variables include the pH value, total dissolved solids (TDS), and turbidity or turbidity. A fuzzy inference system is used to classify water quality into three classes, namely good (meets quality standards), ordinary, and bad (polluted). The expert system of success provides inference results with a 100% success percentage. The results of monitoring and water quality classification can be accessed online using the Internet of Things (IoT) ThingSpeak platform

Microgrid Energy Management System Based on Fuzzy Logic and Monitoring Platform for Data Analysis

Energy management and monitoring systems are significant difficulties in applying microgrids to smart homes. Thus, further research is required to address the modeling and operational parts of the system’s future results for various applications. This paper proposes a new technique for energy management in a microgrid using a robust control approach and the development of a platform for real-time monitoring. The developed controller is based on a fuzzy logic method used in the energy Internet paradigm with connected distributed generators (DGs) in the microgrid. The developed method regulates the power flow of the microgrid, and frequency/voltage regulation improved the load-management performance and monitoring system using the ThingSpeak platform for real-time data analysis. The MATLAB. simulation results show the feasibility and effectiveness of the proposed strategy and the introduced approach in microgrid control under various operating conditions. Additionally, the results show that the proposed monitoring platform facilitates real-time data analysis.

IoT based Substation Monitoring and Control

Abstract: The Smart Voltage and Current Monitoring System (SVCMS) approach is utilized in this undertaking. It shows a solitary stage electrical design that uses voltage and flow from the sensor by means of a microcontroller and afterward remotely conveys the expected information to the outcomes screen through another PC. It is vital to utilize the Internet of Things (IoT) to upgrade the idea of the power with substation observing and control discretionary change. Accordingly, it is basic to have a perception framework that can distinguish and channel. The Arduino Uno is utilized as a microcontroller in the coordinated Smart Voltage and Current Monitoring System (SVCMS) set up to ascertain the voltage and current sensor results. It then sends this data, after assessment, to the end client's PC contraption utilizing the IoT module. The Arduino Uno controller and IoT modules are a microcontroller and far off devices, separately. In light of the heap got by the electrical machines in the event that the heap is high, the power conveyed is to be limited or the power must be closed down. In the olden days there should be a one person at the substation to look for a faults if anything occurred and now due to the increase in the tremendous technology there are many new technologies introduced into the life cycle of the of the human beings. In that one of the technology that helps to reduce the efforts of the human beings is Internet of Things(IoT) that uses the Wi-Fi module that helps to connect the hardware and the software. The data collected will be shared to the ThingSpeak platform and it will displayed by using the graphs for each parameter different bar graphs are used. Keywords: Arduino Uno, LCD display, Servo Motor, wi-fi module, Thing view App, Internet of Things, Substation Monitoring and Control

Weather Monitoring System using IoT for Smart Farming

In most countries, agriculture is considered a major primary sector and a principal source of income. It is estimated that by the year 2050, the world’s population is expected to reach 9.1 billion people. According to the United Nations Food and Agriculture Organization (FAO), food production would need to expand by almost 70% to feed the growing population. As a result, the increase in agricultural productivity is critical in ensuring high crop yields and farm profitability. The proposed work aims to design an automated, fast-processing, real-time weather monitoring system for sustainable development in smart farming against climatic action. The proposed weather monitoring system is based on IoT technology designed using proteus simulation tool which collects necessary environmental data by using a Temperature sensor (LM35), Pressure sensor (BMP180), Soil moisture sensor, Rain sensor, and Raspberry Pi (RPI3) and the data are fed to ThingSpeak platform to predict the suitable condition for crop growth and better crop yield.

Utilization of control technology for mushroom production houses using the internet of things (IoT) in SMEs Omah Jamur Ungaran

Indonesians are currently well familiar with oyster mushroom cultivation. However, there are various issues with cultivation. Omah Jamur Ungaran in Semarang Regency likewise has same problem. The issue is that the mushroom house's production is not optimum because controlling humidity is still done manually, by turning on the pump if the temperature and humidity are not ideal. This causes the mushroom house's humidity to fluctuate. Moreover, the pump's electrical consumption is erratic. This service activity's objective is to provide an automatic device to control humidity and temperature in the mushroom house for optimal mushroom production. The method is to employ IoT technology. The community service determined that the temperature and humidity management system in the oyster mushroom production room can be automated, with the sprayer pump turning on when the temperature reaches 29º C and off when the temperature reaches 28.5º C. Furthermore, using the Thingspeak platform, MSME owners may automatically monitor the temperature and humidity of the mushroom production room.

ENVIRONMENTAL TEMPERATURE AND HUMIDITY MONITORING SYSTEM USING RASPBERRY PI 4 AND THINGSPEACK

In recent years, IoT platforms have become increasingly used due to their untapped potential. This paper aims to create an IoT system to monitor temperature and humidity in an enclosure The Raspberry Pi 4 SBC (Single-Board Computer) development board and ThingSpeak cloud platform will be used to make this system. Data from the DHT11 humidity and temperature sensor will be collected by the Raspberry PI 4 SBC development board, which will transmit it via the WiFi connection to the IoT ThingSpeak platform cloud for further analysis. The IoT ThingSpeak platform provides data storage, processing and visualization services.

IoT Based Street Lighting and Computer Aided Control

Traditional lighting systems have many disadvantages such as energy efficiency, failure tracking and lack of remote control. These disadvantages cause unnecessary energy consumption, extra labor, security threats and lack of follow-up. To overcome these problems, in this study, instead of traditional lighting, an IoT-based smart lighting prototype was developed and computer-assisted control was performed. In order to ensure energy efficiency, the light intensity of the street lamps was adjusted according to the intensity by taking data from the motion sensors. Data such as fault tracking and density obtained from LED armature sensors were transferred to the cloud and controlled independently of the venue. Thus, the data on the cloud can be easily tracked through the ThingSpeak platform. With the visualized ThingSpeak web interface, the electrical power, current drawn, temperature value, ambient light value, location information, motion detection and remote switching of the LED armature can be done independently of the location.

IoT System on Dynamic Fish Feeder Based on Fish Existence for Agriculture Aquaponic Breeders

Maintaining and breeding fish in a pond are a crucial task for a large fish breeder. The main issues for fish breeders are pond management such as the production of food for fishes and to maintain the pond water quality. The dynamic or technological system for breeders has been invented and becomes important to get maximum profit return for aquaponic breeders in maintaining fishes. This research presents a developed prototype of a dynamic fish feeder based on fish existence. The dynamic fish feeder is programmed to feed where sensors detected the fish's existence. A microcontroller board NodeMCU ESP8266 is programmed for the developed hardware. The controller controls the feeding and feedback mechanism based on attached sensors. An ultrasonic sensor is programmed with the controller to detect the level of food and waterproof ultrasonic to detect existing fish. The humidity sensor was used to measure the humidity in the food container to control the food freshness. Two servo motors were used to move the waterproof sensor to attract the fish and to dispense the food to the fish when existed. The result presents four measured levels that are the temperature of the food container, the quality of food based on humidity measured, fish detection counter and level of fish food in the container. Data analytics on all the measured levels was presented on the ThingSpeak platform by using Blynk to get data collections from all sensors. This research is significant for fish breeders that support IR4.0 system connected online and mobile apps which also contribute to today’s agriculture.

IoT-based performance analysis of hybrid solar heater-double slope solar still

Abstract Remote monitoring of solar still systems is an interesting step for performance analysis and supervision. In this article, a monitoring system is developed and integrated to a solar still system. The parameters considered (such as air temperatures, relative humidity, etc) have been posted on a webpage via the Internet of Things (IoT) technique. For this, the ThingSpeak platform of MathWorks is used. The results demonstrate that ground water after desalination has practically the same chemical parameter values as mineral water (Nestle) and ordinary home drinking water. It has also been confirmed that by adding a solar preheater, the process of evaporation of saline water has been accelerated, which permits improvement of the efficiency of the proposed prototype.

Environmental Parameters Monitoring System

Abstract The project presents the development of a system for monitoring environmental parameters. At the base of this system is the ESP-32S board that collects, processes and transmits data from the three sensors to the two web interfaces. The role of these web interfaces is to display the data collected from the sensors. The local web interface consists of two windows, the first window contains the table of sensors that displays the data measured by the sensors at that time. In the second window you can see the data measured by the sensors through graphs. They store the sensor data, giving the user the ability to view previously measured data. The local web interface provides sensor data only in the Wi-Fi network coverage area, and its data is deleted when the server is closed. The global web interface displays data using graphs. At the base of this web interface is the ThingSpeak platform that allows the system to transmit data anywhere in the world, store data in the Cloud space and the possibility of using special analysis functions.

Use of the MLX 90164 sensor and the ThingSpeak platform for internet of things-based animal body temperature check

The MLX 90614 sensor is an IR sensor used to measure temperature without contact. This sensor can measure the object's temperature and ambient temperature in the range of -40 oC – 125 oC. These sensors are widely used in areas such as room temperature measurement, machine temperature, ambient temperature, and body temperature. The MLX 90614 sensor is not yet fully usable directly to perform temperature measurements due to the program's simple defaults so that the measurement results are inaccurate. Therefore, optimization is needed to increase the precision value of the body's internal temperature estimation using this sensor. The method carried out in this study used 6 experimental sheep. Temperature checks are performed through a contact thermometer and compared to non-contact checks by MLX 90614 sensors. Results showed the average temperature of the contact thermometer was 39.28±0.09 oC while the MLX sensor yield was 35.78±1.38 oC. The average temperature difference was 3.5±1.48 oC. The results showed that the temperature difference correction factor needs to be included in the script code when running MLX 90614 sensor. The results of temperature checks by the sensor can be sent directly in real time to the ThingSpeak platform so that the results can be stored and accessed in different places easily. The use of MLX 90614 sensor combined with IoT concept using ThingSpeak can facilitate the process of non-contact body temperature check, and also make the data can be accessed dan stored easily.

Development of a micro weather station using Arduino and Internet of Things

The goal of this work is to build a low cost pedagogical device able to improve the comprehension of weather phenomena for African students in particular and in general for students across the world. This experimental and didactic device can be seen as an easy teaching tool to measure meteorological and climatic data. This structure is called a micro weather station. The investigation is done in Metipkwale one of the village of Ebolowa town in Cameroon (Central Africa). Some weather data automatically obtained from the micro weather station (sensors) such as temperature, humidity and pressure, are directly transmitted by a modem (Wi-Fi connection) to the ThingSpeak platform in order to be registered online and plotted as a diagram. The illustration process is assured by a computer or a smartphone. Moreover, the prediction process of climatic behaviour and the reactions of students have been also outlined. Further, some notions such as Internet of Things and Deep Learning associated with exponential smoothing algorithms are also presented.

SYSTEM PENDETEKSI KELAYAKAN KOLAM IKAN NILA MENGGUNAKAN METODE SAW (SIMPLE ADDITIVE WEIGHTING) BERBASIS IoT (INTERNET OF THINGS)

Tilapia (Oreochromis niloticus) is a type of freshwater fish consumption with elongated and flattened body shape laterally and blackish white color. Tilapia originated from the Nile River and surrounding lakes. Now this fish has spread to countries on five continents with tropical and subtropical climates. Whereas in cold climates, tilapia cannot live well. ideal water temperature in tilapia enlargement ponds ranges between 27.7-29.3 ° C, where fish will grow optimally at water temperatures around 25-32 ° C.for the pH of the tilapia enlargement ponds range between 6, 4-8.5 and turbidity range of 3-19 NTU, because this high turbidity level has an effect on the amount of tilapia mortality. With the system that the researchers created, it was easier to determine a suitable fish pond to maintain as a life of tilapia with the help of the Internet of Things network system and reduce the failure rate in breeding and implementation of Thingspeak as a platform to display the results of data obtained by sensors and calculated with method calculation.
 This system takes data with temperature sensors, pH and Turbidity, to find water temperature, acidity and alkalinity in water and turbidity of water. Then the data obtained is sent to the ESP8266 module network and sent to the thingspeak platform, the data that appears is inputted into the database to be processed using the SAW method, the results of the SAW method calculation are displayed by the system.
 Implementation of the SAW (Simple Additive Weighting) Method for Detecting the Feasibility of Iot-Based Fish Ponds (Internet of Things) has been successfully implemented. So that it can rank tilapia ponds based on parameters of temperature, pH, turbidity.

Electricity consumption meter for the White Tariff and feasibility study of tariff migration to residence

Until the end of 2019, only consumers who had a monthly average above 250 kWh/- month could join the White Tariff in Brazil, however, since January 1, 2020, there is no minimum consumption limitation required. This modality has different tariff values according to the consumption time range, which can bring savings of up to 14.17% in the electric bill at the end of the month if the consumer uses the energy service only during off-peak hours, and due to this possible economy, an increase in the number of customers is expected. However, it is common to question whether it is worth migrating, which depends on each consumption profile, since this modality can also increase the value of the monthly bill by up to 82.14%, if the consumer consumes energy only at peak hours, comparing the tariff values applied by Copel in June 2019. Using a typical residential energy consumption profile, the average is that the White Tariff is around 1.20% more expensive than the Conventional Tariff at the end of the month. Then, an electric energy meter was developed for the White Tariff, whose main objective is to indicate, at the end of a period, which method is more economically advantageous, the White Tariff or the Conventional Tariff, in a residence. The meter was developed based on the IC ADE7753, in which it performs several measurements, among them the active power. ESP82266 NodeMCU was also used to communicate with the IC, carry out the necessary calculations, and send the data to the IoT ThingSpeak platform, where it is possible to remotely monitor the results. The meter was developed to perform the analysis in a home serviced by a single-phase voltage of 127 V, where it was calibrated based on the PZEM-022 meter. In addition to the meter measuring active power, for the calculation of consumption, it also measures the power factor. The meter was on for 7 days in this residence, where residents maintained their common consumption routines. At the end of this period, the result was that the value of the White Tariff was about 0.81% above the value of the Conventional Tariff, indicating that for this residential unit, the migration is not economically worthwhile.