Naslov
IoT Wallet: Machine Learning-based Sensor Portfolio Application

Autori
Šolić, Petar ; Lojić Kapetanović, Ante ; Županović, Tomislav ; Kovačević, Ivo ; Perković, Toni ; Popovski, Petar

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
5th International Conference on Smart and Sustainable Technologies (SpliTech) / - , 2020, 1-5

ISBN
978-953-290-105-4

Skup
5th International Conference on Smart and Sustainable Technologies 2020

Mjesto i datum
Bol, Hrvatska, 23.09.2020. - 26.09.2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Internet of Things ; LoRa ; deep learning ; time series modeling ; long short-term memory neural networks

Sažetak
In this paper an application for building sensor wallet is presented. Currently, given system collects sensor data from The Things Network (TTN) cloud system, stores the data into the Influx database and presents the processed data to the user dashboard. Based on the type of the user, data can be viewed-only, controlled or the top user can register the sensor to the system. Moreover, the system can notify users based on the rules that can be adjusted through the user interface. The special feature of the system is the machine learning service that can be used in various scenarios and is presented throughout the case study that gives a novel approach to estimate soil moisture from the signal strength of a given underground LoRa beacon node.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Informacijske i komunikacijske znanosti

POVEZANOST RADA