**6. Future work**

#### **6.1 Appliance recognition**

It is expected to develop a recognition model for household appliances where it is possible to compare and/or use different types of machine learning tools such as

**Figure 16.** *Machine learning techniques for the recognition of consumption patterns.*

Support Vector Machines (SVM), k-Nearest Neighbors (kNN), Deep Learning (DL), and Principal Components Analysis (PCA), among others [31–33] (**Figure 16**).

This work would allow the identification of said household appliances in real-time, depending on the target group being analyzed: homes, neighborhoods, residential buildings, and industrial buildings, among others. However, above all things, it would help to optimize the computing capacity necessary to carry out said work [34].

#### **6.2 Optimization methods for HEMS**

Incrementally and in relation to the concept of Smart Grid and Smart Cities, it is expected to inquire about the optimization of a home energy management system (Home Energy Management System – HEMS). On this subject, the state of the art is much more advanced, where it is feasible to find publications related to various types of techniques: Artificial Intelligence, Conventional Methods, and Metaheuristics, among others. With quite ambitious comparisons [35]. Mainly with metaheuristic techniques such as Evolutionary Algorithms or Swarm Intelligence, which are the most used for this type of problem (**Figure 17**).

**Figure 17.** *Optimization methods for HEMS.*

*Characterization of the Electrical Consumption Pattern of Household Appliances for Home… DOI: http://dx.doi.org/10.5772/intechopen.110355*

#### **Figure 18.**

*Consumption prediction techniques.*

## **6.3 Consumption forecast**

It is expected to design an AI algorithm that allows predicting the energy consumption of the home/company/grid system as consumption increases over time and complement the consumption control system with this information (**Figure 18**).

## **6.4 Smart socket design**

The current work operates under the assumptions already described above. Based on this, it is expected to make the following improvements at the SS design level in order to meet the following objectives (**Figure 19**):


**Figure 19.** *Future ILM smart socket system.*
