# Central Heating Cost Optimization for Smart-Homes with Fuzzy Logic and a Multi-Agent Architecture
###### Abstract
So, both AI and IoT are, in fact, responsible for effectiveness and pollution reduction [10]. This study makes use of the fuzzy logic that is capable of interpreting the values read by the IoT devices to infer an output that will be a control action that will be triggered on a heating system with the aim of reducing cost and harmful emissions. These technologies can help to implant a progressive plan in order to achieve zero non-green energy emissions. The first step of this plan usually consists of reducing non-green energy emissions while green energy infrastructures are being implemented and introduced in the energy production system. In this way, control systems that are usually responsible for turning the system on/off and/or regulating other aspects of the system like, for example, flow regulation could help to achieve this first step. As mentioned before, IoT systems are hardware distributed systems in which the different sensors used by the system and even the gateways are distributed in a real environment. This environment can be small or big; this characteristic depends on the problem or real system that the developers want to resolve. However, the crucial thing here is that the system has several components distributed over the area of the system. These hardware components will be controlled by software. Therefore, it is considered that the best software solution for this kind of hardware system is a distributed software system. In particular, a Multi-Agent System (MAS); MAS is a kind of distributed system that is composed of different entities or agents [11; 12]. Usually, these agents represent real entities of the world, entities like the sensors of an IoT system. This characteristic is one of the keys that make MASs an ideal solution for IoT infrastructures. However, more advantages of MASs will be explained in future sections. Hence, with all this information and taking into account that a lot of big and medium cities in Spain still have homes and buildings with central heating installations, it is crucial to develop and research a system that can optimize the use of these old installations while they are replaced with modern ones. This is important given the new policies established in society that aim to reduce energy consumption and gradually introduce green energy; while this transition is developing, proposals like the one presented in this article are important. Therefore, a control system based on MAS architecture and fuzzy logic is presented to optimize the use and reduce the energy consumption of old central heating systems. Data will be collected from sensors that will be integrated into the multi-agent architecture, promoting the correct behavior of the different agents in the system to promote energy savings in the heating system. With the solution presented in this article, it is expected to reduce consumption and, therefore, the emissions of these kinds of systems during the winter months. The rest of the article will be divided as follows: Section 2 will introduce the most relevant works developed during the last years in this research area, Section 3 will define the proposed system presented in this article, Section 4 will explain the case of study defined in order to prove the effectiveness of the proposed system, Section 5 will show the result obtained from the study and their discussions and finally, Section 6 is where the conclusion of the work and future lines of research will be explained.