diplomsko delo
Urban Vidovič (Author), Aleš Holobar (Mentor)

Abstract

Namen diplomskega dela je bil dokazati, da lahko z nekaj denarja, znanja in časa ustvarimo svoj majhen sistem IoT, ki nudi snemanje vožnje in dokazovanje voznikove prisebnosti, nalaganje posnetka v oblak, ogled posnetkov in upravljanje z njimi. Najprej smo opisali uporabljeno tehnologijo in strojno opremo, zasnovo infrastrukture sistema, nato pa implementacijo. Sistem delimo na tri dele: odjemalca, spletno stran in vmesnik API. Vmesnik API in spletna stran sta ustvarjena z ogrodjem Node.js, odjemalec pa je napisan v programskem jeziku Python. Odjemalec izmeri vsebnost alkohola v izdihanem zraku in tako potrdi, da voznik ni pod vplivom alkohola. Nato posname vožnjo in ob povezavi na znano, zaupanja vredno omrežje posnetek naloži v oblak. Vmesnik API skrbi za komunikacijo med odjemalcem in spletno stranjo ter upravlja s podatkovno bazo. Spletna stran omogoča uporabniku registracijo in prijavo ter pregled in brisanje videoposnetkov.

Keywords

platforma Raspberry Pi;avtokamera;senzor MQ3;internet stvari;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher: [U. Vidovič]
UDC: 004.777(043.2)
COBISS: 43134979 Link will open in a new window
Views: 381
Downloads: 111
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Other data

Secondary language: English
Secondary title: Platform Raspberry Pi as dashcam and breathalyzer
Secondary abstract: The main goal of our work was to prove that with some money, knowledge and time, we can develop our own little IoT system, which acts as a dashcam and at the same time shows that we are not driving under the influence of alcohol. It is also capable of uploading the dashcam video to the cloud as soon as it connects to the internet via a secure network. Users can also watch and delete their dashcam videos on a web application. First, we described the technology and hardware, which was used for the development, the infrastructure of our system and the implementation itself. The system is divided into three parts: the client, the website, and the API. The webpage and the API are created with Node.js, whereas the client is written in Python. Client measures the alcohol concentration in the air and therefore confirms that the driver is not under the influence of alcohol. After that it starts recording the ride. When the ride is over and the client connects to the internet, the video is uploaded to the cloud. API handles all the communication between the client, website, and database. The website is used to watch and delete uploaded videos, for which a user must have an active account.
Secondary keywords: Raspberry Pi;dashcam;MQ3 sensor;Internet of Things;
Type (COBISS): Bachelor thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages: VIII, 48 str.
ID: 11987060