Weather Station IoT Educational Model Using Cloud Services

Molnar, Jan; Kiresová, Simona; Vince, Tibor; Kovac, Dobroslav; Jacko, Patrik; Beres, Matej; Hrabovský, Peter

doi:10.3897/jucs.2020.079

Cited by 21 publications

(6 citation statements)

References 7 publications

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“…The practical form of teaching is the most effective one as students can understand things correctly. Therefore, the goal of teachers is to create tools for practical teaching, whether in full-time teaching or online teaching by the virtual laboratories (VLs), which is confirmed by [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33]. The publication [20] focused on mechanical engineering in India states that students can only understand the curriculum well if they experiment in the laboratory.…”

Section: Introductionmentioning

confidence: 99%

Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips

Jacko

Beres

Kovacova

et al. 2022

Sensors

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The article describes the implementation of IoT technology in the teaching of microprocessor technology. The method presented in the article combines the reality and virtualization of the microprocessor technology laboratory. A created IoT monitoring device monitors the students’ microcontroller pins and sends the data to the server to which the teacher is connected via the control application. The teacher has the opportunity to monitor the development of tasks and student code of the program, where the functionality of these tasks can be verified. Thanks to the IoT remote laboratory implementation, students’ tasks during the lesson were improved. As many as 53% (n = 8) of those students who could improve their results achieved an improvement of one or up to two tasks during class. Before the IoT remote laboratory application, up to 30% (n = 6) of students could not solve any task and only 25% (n = 5) solved two tasks (full number of tasks) during the class. Before implementation, 45% (n = 9) solved one problem. After applying the IoT remote laboratory, these numbers increased significantly and up to 50% (n = 10) of students solved the full number of tasks. In contrast, only 10% (n = 2) of students did not solve any task.

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Section: Introductionmentioning

confidence: 99%

Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips

Jacko

Beres

Kovacova

et al. 2022

Sensors

Self Cite

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“…Three sensors were used in the model to measure temperature, pressure, humidity, and precipitation. Similarly, the primary purpose of the work discussed in Molnár et al ( 2020 ) was to describe how to develop and implement a weather station based on the IoT and cloud services to assist in teaching IoT technologies.…”

Section: Related Researchmentioning

confidence: 99%

Modeling and implementation of a low-cost IoT-smart weather monitoring station and air quality assessment based on fuzzy inference model and MQTT protocol

Fahim

Mhouti

Boudaa

et al. 2023

Model. Earth Syst. Environ.

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The automatic weather system serves to inform farmers, tourists, planners, and others with precise information to help them take the appropriate action. Today, with the advancement of smart technologies, the system has evolved into many sensing methods to gather real-time climate data. This article investigates the modeling and implementation of a low-cost weather station device that also functions to measure air quality. The proposed system based on the Internet of Things (IoT) allows access to real-time climate data for a given area. This system monitors environmental conditions such as ambient temperature, humidity, atmospheric pressure, altitude, and levels of harmful atmospheric gases like CO 2 and NO 2 . This real-time telemetry device uses MQ-135, DHT-11 and BMP280 sensors to gather data. The ESP32 board processes the obtained data from all sensors. Additionally, we present a model for a fuzzy inference system (FIS) that performs parameter categorization using a reasoning procedure and incorporates the results into an air quality index (AQI) that describes the levels of pollution for Al Hoceima city. The FIS takes CO 2 and NO 2 values as input and returns the AQI. The AQI for Al Hoceima city is categorized into six levels: Excellent , Good , Regular , Bad , Dangerous , and Very Dangerous . Furthermore, the suggested system's block hardware employs the Message Queuing Telemetry Transport (MQTT) protocol to broadcast collected data to a mobile and web application via the Internet. The suggested IoT-embedded device was tested in real life, and the results were promising.

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“…The authors in [27] proposed an educational IoT model to design a weather station based on ThingSpeak cloud services. Their platform involves both software and hardware parts including DHT11 and BMP180 sensors, Mega 2560 microcontroller, cloud API interfaces, MATLAB scripts as well as applications implemented upon both Windows and Android operating systems.…”

Section: Related Workmentioning

confidence: 99%

“…In [28], the authors presented an environmental monitoring infrastructure using a sensor network-based architecture. Similar to [27], this work employs three main components: sensors, gateway, and cloud. The data (temperature and humidity) is measured by specific sensors and routed by the gateway toward the cloud where data are accessible in real time for visualization and analysis using smart phones.…”

Section: Related Workmentioning

confidence: 99%

Framework for Sustainable Wireless Sensor Network Based Environmental Monitoring

Ouni

Saleem

2022

Sustainability

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Wireless sensor networks (WSN) are the base of the Internet of Things (IoT) that all together give rise to the smart city. These WSNs consist of several sensors, which are densely distributed to observe physical or environmental conditions, like humidity, temperature, light intensity, and gas concertation. The sensors reading data are transmitted to the network coordinator, the IP-gateway, which is at the heart of the wireless network. Many monitoring systems are to be found in the literature with generic designs and with the output of algorithms that runs on the given systems. In this paper, we review the related work on monitoring systems and propose the framework based on WSN to sense the readings from the environment to transmit and store in the cloud for calling on the handheld devices when required by the single or multiple users. A real sensor nodes-based experimental testbed is implemented in order to study the scalability, adaptability, and sustainability of the novel WSN-based environmental monitoring framework.

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Weather Station IoT Educational Model Using Cloud Services

Cited by 21 publications

References 7 publications

Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips

Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips

Modeling and implementation of a low-cost IoT-smart weather monitoring station and air quality assessment based on fuzzy inference model and MQTT protocol

Framework for Sustainable Wireless Sensor Network Based Environmental Monitoring

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