izpis_h1_title_alt

Razvoj pametnega šejkerja za mešanje koktajlov in mobilne aplikacije.
ID MERELA, MATIC (Author), ID Bešter, Janez (Mentor) More about this mentor... This link opens in a new window, ID Mali, Luka (Comentor)

.pdfPDF - Presentation file, Download (34,41 MB)
MD5: A42F1AB5FA74BCE38FE9BE46267F88FC

Abstract
Izdelava koktajlov je ena izmed tehnik, ki jo malokdo pozna in obvlada, veliko ljudi pa v odkrivanju novih koktajlov, izkušenj in raziskovanju novih okusov neizmerno uživa. Čeprav znanje s tega področja lahko vzbudi veselje, se le redki podajo na pot učenja tehnik izdelave koktajlov in kombiniranja razburljivih sestavin. Z izdelavo pametnega šejkerja in mobilne aplikacije ShakeUp smo uporabniku želeli prikazati, kako preprosta in zabavna je lahko izdelava koktajlov. Spoprijeli smo se s problemom pomanjkanja volje do spoznavanja te veščine. Po analizi konkurence smo se podali k razvoju prototipa s funkcionalnostmi, ki smo jih pri tekmecih pogrešali. Šejker in aplikacija sta zasnovana na način, da sta primerna tako za začetnike kot tudi za naprednejše uporabnike, ki si želijo nadgraditi svoje znanje. Zasnova šejkerja na mikrokrmilniku Arduino Nano 33 BLE Sense nam je omogočila uporabo pospeškometra in vezavo zunanje baterije ter temperaturnega senzorja. Na platformo Arduino smo uspešno integrirali model strojnega učenja, ki ocenjuje tehniko tresenja šejkerja ob pripravi koktajla ter meri temperaturo pijače. Oba podatka preko tehnologije Bluetooth posreduje mobilnemu terminalu, ki ju s pomočjo aplikacije ShakeUp in prijaznega uporabniškega vmesnika interpretira. Šejker je možno upravljati z aplikacijo za Android znotraj katere uporabnik izbere željeno pijačo. Ta ga nato vodi skozi proces izdelave ter s podatkovne baze Google Firebase prejme vse potrebne parametre in navodila za ustrezno ocenjevanje tehnike izdelave koktajla. Diplomsko delo obsega veliko uporabnih tehnologij in procesov, od izdelave modela strojnega učenja, vzpostavitve povezave Bluetooth na strani strežnika in odjemalca do izdelave strojne opreme in lotanja različnih komponent. Obsega tudi razvoj uporabniku prijaznega uporabniškega vmesnika in izdelavo aplikacije z orodjem Android Studio. Delo predstavlja celosten izdelek, ki je lep primer tesne integracije strojne in programske opreme z inovativnim načinom reševanja tegob s poglobitvijo v svet koktajlov. Šejker in aplikacija ShakeUp torej predstavljata delujoč prototip in odpirata številne možnosti za nadaljnji razvoj in implementacije izboljšav.

Language:Slovenian
Keywords:Arduino, BLE, Edge Impulse, Android Studio, model strojnega učenja, uporabniški vmesnik, prototip, mobilna aplikacija, strojna oprema, programska oprema, koktajl, šejker za mešanje koktajlov, pametna kuhinja, internet stvari
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FE - Faculty of Electrical Engineering
Year:2024
PID:20.500.12556/RUL-161363 This link opens in a new window
COBISS.SI-ID:207127555 This link opens in a new window
Publication date in RUL:10.09.2024
Views:167
Downloads:48
Metadata:XML DC-XML DC-RDF
:
Copy citation
Share:Bookmark and Share

Secondary language

Language:English
Title:Development of a smart shaker for mixing cocktails and the mobile application.
Abstract:
Cocktail making is one of those crafts that few people know and master, yet many immensely enjoy discovering new cocktails, experiences, and exploring new flavors. Although knowledge in this field brings fulfillment, only a few embark on the journey of becoming a mixologist, learning cocktail-making techniques and combining exciting ingredients. We have addressed this problem by developing a smart shaker and a mobile app named ShakeUp. After analyzing the competition, we developed a final product with the important features we found were missing in their products. The shaker and the app are designed to be suitable for both beginners and more advanced users who wish to enchance their cocktail-making skills. The design of the shaker being based on the Arduino Nano 33 BLE Sense microcontroller enabled access to built-in accelerometer as well as facilitated the integration of an external battery and a temperature sensor. We were able to successfully integrate a machine learning model into the Arduino platform, which enabled evaluating the shaking technique of the shaker while simultaneously measuring the drink's temperature. Both data points are then transmitted via Bluetooth to a mobile terminal, where they are interpreted using the user-friendly interface of the ShakeUp application. The shaker is entirely operated by an Android app, where the user selects the desired drink and is then guided through the process of curating that cocktail. During the process the app retrieves all of the necessary parameters and instructions for the technique evaluation and cocktail making from the Google Firebase database. This project showcases many useful technologies and processes, from developing the machine learning model, establishing Bluetooth connectivity on both the server and client sides, to hardware development and soldering various components. It also includes the prototyping of a friendly user interface and the development of the app using the Android Studio IDE. The final product is a fine example of close integration between hardware and software, which uses a modern approach to overcome the challenges of exploring the world of cocktails. The shaker and the ShakeUp app represent a working prototype and are opening numerous possibilities for further development and implementation of improvements.

Keywords:Arduino, BLE, Edge Impulse, Android Studio, machine learning model, user interface, prototype, mobile app, hardware, software, cocktail, cocktail shaker, smart kitchen, IoT

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back