Short paper: Harmonizing heterogeneous components in SeSaMe

Baresi, Luciano; Guinea, Sam; Shahzada, Adnan

doi:10.1109/wf-iot.2014.6803157

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…Baresi et al [15], for example, provide a simulation for a smart green house scenario. In their simulation, flowers are distributed in different rooms based on specific characteristics.…”

Section: Related Workmentioning

confidence: 99%

Engineering cooperative smart things based on embodied cognition

Nascimento

Lucena

2017

2017 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)

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Abstract-The goal of the Internet of Things (IoT) is to transform any thing around us, such as a trash can or a street light, into a smart thing. A smart thing has the ability of sensing, processing, communicating and/or actuating. In order to achieve the goal of a smart IoT application, such as minimizing waste transportation costs or reducing energy consumption, the smart things in the application scenario must cooperate with each other without a centralized control. Inspired by known approaches to design swarm of cooperative and autonomous robots, we modeled our smart things based on the embodied cognition concept. Each smart thing is a physical agent with a body composed of a microcontroller, sensors and actuators, and a brain that is represented by an artificial neural network. This type of agent is commonly called an embodied agent. The behavior of these embodied agents is autonomously configured through an evolutionary algorithm that is triggered according to the application performance. To illustrate, we have designed three homogeneous prototypes for smart street lights based on an evolved network. This application has shown that the proposed approach results in a feasible way of modeling decentralized smart things with self-developed and cooperative capabilities.

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“…Baresi et al [15], for example, provide a simulation for a smart green house scenario. In their simulation, flowers are distributed in different rooms based on specific characteristics.…”

Section: Related Workmentioning

confidence: 99%