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A Neural Affective Approach to an Intelligent Weather Sensor System

  • 2020
  • OriginalPaper
  • Chapter
Published in:
Authors
John Richard
James Braman
Michael Colclough
Sudeep Bishwakarma
Published in
HCI International 2020 – Late Breaking Posters
Publisher
Springer International Publishing

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Abstract

The ability to capture data from our surrounding environment while learning user preferences has the potential to make our everyday decisions more straightforward and informed. Based on the idea of capturing weather data, we present our current design of a weather sensor network using several Raspberry Pi’s, combined with external resources, that presents recommendations based on personalized affect data. The goal of the system is to learn user preferences in combination with providing emotive output utilizing a neural network. The system has visualization capabilities that can interface with the web, along with other features based on preferences set by the user. This paper presents an overview of the system prototype.

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previous chapter Concept for Human and Computer to Determine Reason Based Scene Location
next chapter Role-Based Design of Conversational Agents: Approach and Tools
Title
A Neural Affective Approach to an Intelligent Weather Sensor System
Authors
John Richard
James Braman
Michael Colclough
Sudeep Bishwakarma
Copyright Year
2020
Book
HCI International 2020 – Late Breaking Posters

Print ISBN: 978-3-030-60699-2

Electronic ISBN: 978-3-030-60700-5

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-60700-5_46
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