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Optimering av datamängder med Machine learning: En studie om Machine learning och Internet of Things
University of Skövde, School of Informatics.
2017 (Swedish)Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesisAlternative title
Optimizing dataflow with Machine learning : a study about Machine learning and Internet of Things (English)
Abstract [en]

This report is about how an Internet of Things (IoT) optimization can be done with Machine learning (ML). The IoT- devices in this report are sensors in containers that read how full the containers are. The report contains a case from Sogeti. Were a client can use this optimization to get better routes for their garbage truck, with this solution the garbage trucks will only go to full containers and be able to skip empty or close to empty containers. This will result in less fuel costs and a better environment. This solution can be used for every industry that needs a route optimization. To do this there must first be understanding for what IoT is and what is possible to do with it then there need to be understanding about ML. The report cover these parts and tell how the method Design science (DS) is being used to produce this solution and some information about the method. This project also works agile with iterations under the implementation stage in DS. On the ML part there is an argumentation of a comparison of witch algorithm should be used. There are two candidates: Hill- Climbing and K-means Cluster. For this solution K-means cluster will be the one being used. K-means clustering is an unsupervised algorithm that doesn’t need practice data, it pairs data that are very similar and builds clusters. It will do this with full containers and build clusters with the ones that have similar coordinates so the full containers are close to each other. When this is done the clusters exports to a database and then there is a brief description on how its possible to make a map that makes a route between the containers in the cluster. 

Place, publisher, year, edition, pages
2017. , 37 p.
Keyword [sv]
Machine learning, Internet of Things, cluster, Rutt optimering, rutt optimering med machine learning, ML, IoT
National Category
Information Systems
Identifiers
URN: urn:nbn:se:his:diva-13747OAI: oai:DiVA.org:his-13747DiVA: diva2:1111127
External cooperation
Sogeti
Subject / course
Informationsteknologi
Educational program
Information Systems - Enterpise Information Management
Supervisors
Examiners
Available from: 2017-07-09 Created: 2017-06-17 Last updated: 2017-07-09Bibliographically approved

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fulltext(1185 kB)37 downloads
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Type fulltextMimetype application/pdf

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf