  Embodied agents is a term used to denote intelligent agents, which are a
component of devices belonging to the Internet of Things (IoT) domain. Each
agent is provided with sensors and actuators to interact with the environment,
and with a 'controller' that usually contains an artificial neural network
(ANN). In previous publications, we introduced three software approaches to
design, implement and test IoT embodied agents. In this paper, we propose a
reference model based on statecharts that offers abstractions tailored to the
development of IoT applications. The model represents embodied agents that are
controlled by neural networks. Our model includes the ANN training process,
represented as a reconfiguration step such as changing agent features or neural
net connections. Our contributions include the identification of the main
characteristics of IoT embodied agents, a reference model specification based
on statecharts, and an illustrative application of the model to support
autonomous street lights. The proposal aims to support the design and
implementation of IoT applications by providing high-level design abstractions
and models, thus enabling the designer to have a uniform approach to
conceiving, designing and explaining such applications.
