## 3 The Proposed Solution  
In the literature, several approaches based on WNs for smart grids and smart homes have been proposed [23, 24]. In fact, advanced information and communications technologies (ICTs), monitoring and control, energy harvesting [25] and innovative metering technologies via smart wireless devices are becoming increasingly important. For instance, in [26], a domestic energy management scheme based on a wireless sensor home area network (WSHAN) is introduced. This scheme focuses on the communication among smart appliances and an EMU through the wireless network, and consumer demands are processed in near real time. On the contrary, the approaches proposed in [27, 28] aim at a TOU pricing benefit in order to decrease the energy cost. The goal of these authors is to shift the consumer load to off-peak periods using the WN to deliver their requests to the EMU. However, although the analyzed WN-based works (from [23] to [28]) obtain good performance, their authors do not bother to choose the most appropriate wireless protocol. In fact, as mentioned above, the choice of a proper wireless protocol with respect to another one may involve significant benefits and quite different results. The system proposed in this paper is depicted in Figure 1 and consists of various energy sources, storage devices, electrical appliances, a control unit and related communication tools. As it is possible \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **BLE** & **IEEE 802.15.4** & **IEEE 802.11** \\ \hline Cost & ✓ & ✓ & ✓ \\ Security & ✓ & ✓ & ✓ \\ Power consumption & ✓ & ✓ & ✗ \\ Ecosystem & ✓ & ✗ & ✓ \\ Reliability & ✓ & ✓ & ✓ \\ Ease of use & ✓ & ✓ & ✓ \\ Range & ✓ & ✓ & ✓ \\ Transmission rate & ✓ & ✓ & ✓ \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of wireless technologies and their usefulness in smart homes. BLE, Bluetooth Low Energy. to see, the smart home is able to generate its own energy thanks to renewable energy sources, such as wind turbine and solar photovoltaic panels, and stores this energy by means of batteries. It is necessary to highlight that the renewable power forecasting methodology is not addressed in this paper, because it is not the main aim of this work. However, it is useful to note an important feature in the considered smart home. In fact, in the interaction between the EMU and the storage devices, a key role is played by a \"charging station\", a kind of inverter, that converts direct current electricity from renewable energy sources or a home battery into the alternating current used by home's lights, appliances and devices. Anyhow, it is obvious that even the energy from a high voltage power line can be used. However, it is clear that in homes, the high voltage is not used. For this reason, transformer stations, outside of the housing, are used for the transformation from high to low voltage. The communication-based domestic energy management solution proposed in this work aims at reducing home electricity consumption charges, decreasing the electricity bill of the consumer by shifting the appliances' operation from peak demand hours to off-peak ones. In fact, the electrical appliances that are part of the home system can be used at various time periods every day depending mainly on the day of the week. In fact, there are substantial differences in the usage time of appliances throughout the day, especially between working days and the weekend. For instance, a refrigerator can be active for a 25 min period every 50 min because of its operation principle, and similarly, an air conditioner can be operated for 15 min every half an hour only in the summer months. The system introduced in this paper, shown in Figure 1, involves communications among smart appliances, a central EMU and a WN. As it is possible to see, the decision making center is represented by  
Figure 1: The proposed energy management system for smart homes. the EMU, where a fuzzy-based algorithm, described in Section 3.2, deals with the HEM.