Estimating Missing Information by Cluster Analysis and Normalized Convolution

Cesare Fabio Valenti, Davide Andrea Guastella, Davide Andrea Guastella

Risultato della ricerca: Conference contribution

4 Citazioni (Scopus)

Abstract

Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.
Lingua originaleEnglish
Titolo della pubblicazione ospiteIEEE 4th International Forum on Research and Technologies for Society and Industry, RTSI 2018 - Proceedings
Pagine1-6
Numero di pagine6
Stato di pubblicazionePublished - 2018

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Industrial and Manufacturing Engineering
  • Instrumentation

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