Abstract
In an industrial environment, some phenomena such as wind, humidity, pressure or temperature are required to be controlled in a distributed and low invasive manner. This paper describes the development of a wireless sensor network that can easily be spread out and connected to a wide range of sensors. This versatility is reinforced by the processing and transmission capacities of each component of the network. An application to temperature mapping is provided to illustrate the functionality of the network. In particular, the previous hardware has been developed in order to perform temperature control while managing several airflow units. The learning based control proposal presented herein involves first, a neuro-fuzzy system in charge of generating a reliable model of the refrigeration process and then, an ant colony metaheuristic to find an optimum airflow solution that fits the required temperature distribution. Keywords: Ant colony optimization, learning based control, neuro-fuzzy system, wireless sensor network.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal of Sensors Wireless Communications and Control
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.