| Autor: |
Ali Elyounsi, Alexander N. Kalashnikov |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Engineering Proceedings, Vol 27, Iss 1, p 55 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2673-4591 |
| DOI: |
10.3390/ecsa-9-13337 |
| Popis: |
Temperature sensors are widely employed in control systems that maintain a required temperature in a vessel or container irrespective of the temperature changes in the outer environment. However, the limited power of the heater/cooler (the plant of the control system) might lead to uncomfortable or even unacceptable deviations from the required temperature. This behavior can be mitigated if the control system can have access not only to the present temperature in the vessel but also to the forecasted environmental temperature. This situation occurs, among other situations, in industrial vessels that require elevated temperatures during their operation but shut down out of hours. To start heating these to the required temperature at the beginning of a working shift wastes processing time until the required temperature is reached. It is more productive to turn on heating in advance in order to get the vessel ready on time. In order to achieve fully autonomous automatic operation, the sensor should have some intelligence and access to the temperature forecast, which can be provided over the internet. Both these requirements can be met by employing a WiFi-enabled microcontroller. We present the development of a predictive IoT temperature sensor based on the ESP32 microcontroller, which uses the internet service to obtain the time and weather forecast and upload temperature logs to a cloud server for convenient remote access and storage. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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