An intelligent heating system based on the Internet of Things and STM32 microcontroller
Abstract Under the rapid growth of Internet of Things technology, many households are moving towards smart solutions. Addressing the inflexibility of temperature control in traditional heating systems, this research focuses on designing an intelligent heating system. To enhance flexibility and intel...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-04-01
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| Series: | Energy Informatics |
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| Online Access: | https://doi.org/10.1186/s42162-024-00326-2 |
| _version_ | 1797209098706485248 |
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| author | Yan Su |
| author_facet | Yan Su |
| author_sort | Yan Su |
| collection | DOAJ |
| description | Abstract Under the rapid growth of Internet of Things technology, many households are moving towards smart solutions. Addressing the inflexibility of temperature control in traditional heating systems, this research focuses on designing an intelligent heating system. To enhance flexibility and intelligence, an intelligent heating system based on the Internet of Things and STM32 microcontroller is proposed. Furthermore, the study identifies limitations of traditional proportional-integral-derivative control methods and establishes an optimization control model for heating system output temperature based on the Dynamic Matrix Control algorithm. Results indicate that the system's web interface successfully draws temperature curves, displaying clear data on detected temperature and humidity. The output temperature optimization control model shows a temperature rise of 2 °C and a temperature control error index of 0.0543 during the initial heating stage, and a control error index of 0.0353 during the mid-heating stage when the valve relative opening is close to 0. And the temperature control effect is better than traditional PID control, fuzzy PID control, genetic algorithm based PID control, and predictive feedback predictive control, without obvious indoor temperature overshoot phenomenon, which has certain advantages. In conclusion, the proposed system and model exhibit favorable application outcomes, offering technological support for the intelligent management of heating systems. |
| first_indexed | 2024-04-24T09:49:18Z |
| format | Article |
| id | doaj.art-e280d02471e34a5a8fde2d297aeca1da |
| institution | Directory Open Access Journal |
| issn | 2520-8942 |
| language | English |
| last_indexed | 2024-04-24T09:49:18Z |
| publishDate | 2024-04-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Energy Informatics |
| spelling | doaj.art-e280d02471e34a5a8fde2d297aeca1da2024-04-14T11:30:44ZengSpringerOpenEnergy Informatics2520-89422024-04-017111810.1186/s42162-024-00326-2An intelligent heating system based on the Internet of Things and STM32 microcontrollerYan Su0College of Information Engineering, Zhengzhou University of TechnologyAbstract Under the rapid growth of Internet of Things technology, many households are moving towards smart solutions. Addressing the inflexibility of temperature control in traditional heating systems, this research focuses on designing an intelligent heating system. To enhance flexibility and intelligence, an intelligent heating system based on the Internet of Things and STM32 microcontroller is proposed. Furthermore, the study identifies limitations of traditional proportional-integral-derivative control methods and establishes an optimization control model for heating system output temperature based on the Dynamic Matrix Control algorithm. Results indicate that the system's web interface successfully draws temperature curves, displaying clear data on detected temperature and humidity. The output temperature optimization control model shows a temperature rise of 2 °C and a temperature control error index of 0.0543 during the initial heating stage, and a control error index of 0.0353 during the mid-heating stage when the valve relative opening is close to 0. And the temperature control effect is better than traditional PID control, fuzzy PID control, genetic algorithm based PID control, and predictive feedback predictive control, without obvious indoor temperature overshoot phenomenon, which has certain advantages. In conclusion, the proposed system and model exhibit favorable application outcomes, offering technological support for the intelligent management of heating systems.https://doi.org/10.1186/s42162-024-00326-2Heating systemInternet of ThingsSTM32 microcontrollerDynamic matrix controlOptimization control |
| spellingShingle | Yan Su An intelligent heating system based on the Internet of Things and STM32 microcontroller Energy Informatics Heating system Internet of Things STM32 microcontroller Dynamic matrix control Optimization control |
| title | An intelligent heating system based on the Internet of Things and STM32 microcontroller |
| title_full | An intelligent heating system based on the Internet of Things and STM32 microcontroller |
| title_fullStr | An intelligent heating system based on the Internet of Things and STM32 microcontroller |
| title_full_unstemmed | An intelligent heating system based on the Internet of Things and STM32 microcontroller |
| title_short | An intelligent heating system based on the Internet of Things and STM32 microcontroller |
| title_sort | intelligent heating system based on the internet of things and stm32 microcontroller |
| topic | Heating system Internet of Things STM32 microcontroller Dynamic matrix control Optimization control |
| url | https://doi.org/10.1186/s42162-024-00326-2 |
| work_keys_str_mv | AT yansu anintelligentheatingsystembasedontheinternetofthingsandstm32microcontroller AT yansu intelligentheatingsystembasedontheinternetofthingsandstm32microcontroller |