This page cannot be printed from here

Please use the dedicated print option from the 'view' drop down menu located in the blue ribbon in the top, right section of the publication.

screenshot of print menu option

Description: Applying machine learning to find value in industrial IoT
Applying machine learning to find value in industrial IoT
As the Internet of Things (IoT) and smart cities move from the realm of industry buzzwords to everyday tools being deployed by the thousands, there is a concurrent growth in the vast amounts of data collected for analysis. According to the German online portal, Statista, the total installed base of Internet of Things (IoT) connected devices is projected at more than 75 billion worldwide by 2025....
Author(s)
Kimberly BruceAlicja Dobrzeniecka
SourceArticle from Sept/ Oct 2019 World Water Magazine
Project IDWW18
SubjectData Analytics;Water Infrastructure;Distribution
Document typeMagazine article
PublisherWater Environment Federation
Print publication date Apr 2019
ISSN1354-313X
Volume / Issue42 / 5
Content sourceWorld Water Magazine
First / last page(s)22 - 22
Copyright2019
Word count790
Subject keywordsmachine learningIoTsmart citiessensorsmonitoringpredictive analyticsartificial intelligenceCarl Data Solutionsdata cleaningstatistical analysisdata anomalies

Purchase price $5.50

Get access
Description: Applying machine learning to find value in industrial IoT
Author’s Note
Applying machine learning to find value in industrial IoT
Alicja Dobrzeniecka is a data scientist and Kimberley Bruce is the marketing and communications manager at Carl Solutions, based in Vancouver, British Columbia, Canada.
PublisherWater Environment Federation
Copyright2019
Word count26
Read
Applying machine learning to find value in industrial IoT