Analiza sustava za pohranu i vizualizaciju podataka u okružju Interneta stvari

master's thesis

• Title (english): Analysis of data storage and visualization systems in Internet of Things environment
• Author: Domagoj Kolega
• Mentor: Pavle Skočir (mentor)
• Committee member: Pavle Skočir (predsjednik povjerenstva)
• Committee member: Mario Kušek (član povjerenstva)
• Committee member: Krešimir Pripužić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2023-07-06, Croatia

Abstract

U ovom radu opisan je koncept Internata stvari te njegova povezanost s velikom količinom podataka(Big Data). Zatim što su to velike količine podataka, koje vrste postoje i koje su im karakteristike. Sustavi za pohranu i vizualizaciju podataka odigravaju bitnu ulogu u iskorištavanju velike količine podataka te smo se detaljno usredotočili na njih i njihove ključne indikatore performansi. Detaljno su istražene arhitekture i tehnologije sustava za pohranu i vizualizaciju podataka. Obuhvaćene su suvremene arhitekture sustava za pohranu velike količine podataka kao što su: grafovski model arhitekture, NoSQL arhitektura, hibridna arhitektura i druge. Također su objašnjene različite tehnike vizualizacije podataka, na primjer: Grafikoni, Karte i Vremenske crte.

Nadalje, prezentiran je studijski slučaj praćenja ljudskih aktivnosti, koji opisuje skup podataka koji se koristi za analizu sustava za pohranu i vizualizaciju podataka. Uz skup podataka osvrnuli smo se na korisnike(ispitanike), korištene uređaje i senzore te konačno model odabranog skupa podataka.

Na kraju je napravljena detaljna analiza i usporedba performansi dva sustava za pohranu i dva sustava za vizualizaciju podataka.

Abstract (english)

This paper describes the concept of the Internet of Things and its relationship with big data. It explains what big data is, the different types that exist, and their characteristics. Data storage and visualization systems play a crucial role in harnessing large amounts of data, and the focus is on exploring them and their key performance indicators. The architectures and technologies of data storage and visualization systems are thoroughly researched. Contemporary architectures for storing large amounts of data are covered, such as graph-based architecture, NoSQL architecture, hybrid architecture, and others. Different data visualization techniques are also explained, including graphs, maps, and timelines.

Furthermore, a case study on tracking human activities is presented, describing a dataset used for analyzing data storage and visualization systems. In addition to the dataset, the study considers users (subjects), the devices and sensors used, and the chosen model for the dataset.

Finally, a detailed analysis and comparison of the performance of two data storage systems and two data visualization systems is conducted.

• Keywords: Internet stvari; Velika količina podataka; Sustavi za pohranu podataka; Sustavi za vizualizaciju podataka; Arhitektura sustava; Distribuiranost; Grafikoni; Clickhouse; Redis; MPAndroidChart; GraphView
• Keywords (english): Internet of Things; Big Data; Data Storage Systems; Data Visualization Systems; System Architecture; Distributiveness; Graphs; Clickhouse; Redis; MPAndroidChart; GraphView
• Language: croatian
• URN:NBN: urn:nbn:hr:168:968222
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-10-11 09:19:56