IoFClime: The fuzzy logic and the Internet of Things to control indoor temperature regarding the outdoor ambient conditions
| Autor: | Daniel Meana-Llorián, Nestor Garcia-Fernandez, Cristian González García, B. Cristina Pelayo G-Bustelo, Juan Manuel Cueva Lovelle |
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| Rok vydání: | 2017 |
| Předmět: |
FOS: Computer and information sciences
Value (ethics) Architectural engineering Temperature control Computer Science - Artificial Intelligence Computer Networks and Communications Computer science business.industry Control (management) Humidity 020206 networking & telecommunications 02 engineering and technology Computer security computer.software_genre Fuzzy logic Artificial Intelligence (cs.AI) Hardware and Architecture Order (business) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Set (psychology) Internet of Things business computer Software |
| Zdroj: | Future Generation Computer Systems. 76:275-284 |
| ISSN: | 0167-739X |
| Popis: | The Internet of Things is arriving to our homes or cities through fields already known like Smart Homes, Smart Cities, or Smart Towns. The monitoring of environmental conditions of cities can help to adapt the indoor locations of the cities in order to be more comfortable for people who stay there. A way to improve the indoor conditions is an efficient temperature control, however, it depends on many factors like the different combinations of outdoor temperature and humidity. Therefore, adjusting the indoor temperature is not setting a value according to other value. There are many more factors to take into consideration, hence the traditional logic based in binary states cannot be used. Many problems cannot be solved with a set of binary solutions and we need a new way of development. Fuzzy logic is able to interpret many states, more than two states, giving to computers the capacity to react in a similar way to people. In this paper we will propose a new approach to control the temperature using the Internet of Things together its platforms and fuzzy logic regarding not only the indoor temperature but also the outdoor temperature and humidity in order to save energy and to set a more comfortable environment for their users. Finally, we will conclude that the fuzzy approach allows us to achieve an energy saving around 40% and thus, save money. |
| Databáze: | OpenAIRE |
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