Framework for Agent-Based Simulation of Energy and Water Usage in Smart Homes

Agent-based models (ABMs) are computational models that help simulate actions, interactions between different entities in a controlled environment. It is a solid technique that provides a relatively inexpensive way to mimic a system in order to understand its behavior and extract the rules that govern its outcomes. In the context of smart cities, the use of (ABM) to model a home consumption of water and energy, represents a substantial alternative to installing smart homes at scale. Considering the cost, effort and time of converting existing homes to smart homes, ABM represents a reliable technique that allows to simulate the interaction of smart homes and different smart city components such as smart grid, water management, air quality meter etc. The objective of this study is to present how Smart homes can be modelled using ABM, and what benefits can be harvested from these models, we will also discuss how AI models can benefit from these models through synthetic data generation.