IoT Wallet: Machine Learning-based Sensor Portfolio Application

Petar Solic; Ante Lojic Kapetanovic; Tomislav Zupanovic; Ivo Kovacevic; Toni Perkovic; Petar Popovski

doi:10.23919/SpliTech49282.2020.9243699

IoT Wallet: Machine Learning-based Sensor Portfolio Application

Petar Solic, Ante Lojic Kapetanovic, Tomislav Zupanovic, Ivo Kovacevic, Toni Perkovic, Petar Popovski

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

5 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	2020 5th International Conference on Smart and Sustainable Technologies (SpliTech)
Editors	Petar Solic, Sandro Nizetic, Joel J. P. C. Rodrigues, Joel J. P.C. Rodrigues, Diego Lopez-de-Ipina Gonzalez-de-Artaza, Toni Perkovic, Luca Catarinucci, Luigi Patrono
Number of pages	5
Publisher	IEEE
Publication date	4 Nov 2020
Article number	9243699
ISBN (Print)	978-1-7281-7363-4
ISBN (Electronic)	978-953-290-105-4
DOIs	https://doi.org/10.23919/SpliTech49282.2020.9243699
Publication status	Published - 4 Nov 2020
Event	2020 5th International Conference on Smart and Sustainable Technologies (SpliTech) - Split, Croatia Duration: 23 Sept 2020 → 26 Sept 2020

Conference

Conference	2020 5th International Conference on Smart and Sustainable Technologies (SpliTech)
Country/Territory	Croatia
City	Split
Period	23/09/2020 → 26/09/2020

Keywords

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

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10.23919/SpliTech49282.2020.9243699

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Solic, P., Kapetanovic, A. L., Zupanovic, T., Kovacevic, I., Perkovic, T., & Popovski, P. (2020). IoT Wallet: Machine Learning-based Sensor Portfolio Application. In P. Solic, S. Nizetic, J. J. P. C. Rodrigues, J. J. P. C. Rodrigues, D. Lopez-de-Ipina Gonzalez-de-Artaza, T. Perkovic, L. Catarinucci, & L. Patrono (Eds.), 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech) Article 9243699 IEEE. https://doi.org/10.23919/SpliTech49282.2020.9243699

Solic, Petar ; Kapetanovic, Ante Lojic ; Zupanovic, Tomislav et al. / IoT Wallet : Machine Learning-based Sensor Portfolio Application. 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech). editor / Petar Solic ; Sandro Nizetic ; Joel J. P. C. Rodrigues ; Joel J. P.C. Rodrigues ; Diego Lopez-de-Ipina Gonzalez-de-Artaza ; Toni Perkovic ; Luca Catarinucci ; Luigi Patrono. IEEE, 2020.

@inproceedings{d5906859341e422d8cb2796362bbf09b,

title = "IoT Wallet: Machine Learning-based Sensor Portfolio Application",

abstract = "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.",

keywords = "Internet of Things, LoRa, deep learning, long short-term memory neural networks, time series modeling",

author = "Petar Solic and Kapetanovic, {Ante Lojic} and Tomislav Zupanovic and Ivo Kovacevic and Toni Perkovic and Petar Popovski",

year = "2020",

month = nov,

day = "4",

doi = "10.23919/SpliTech49282.2020.9243699",

language = "English",

isbn = "978-1-7281-7363-4",

editor = "Petar Solic and Sandro Nizetic and Rodrigues, {Joel J. P. C.} and Rodrigues, {Joel J. P.C.} and {Lopez-de-Ipina Gonzalez-de-Artaza}, Diego and Toni Perkovic and Luca Catarinucci and Luigi Patrono",

booktitle = "2020 5th International Conference on Smart and Sustainable Technologies (SpliTech)",

publisher = "IEEE",

address = "United States",

note = "2020 5th International Conference on Smart and Sustainable Technologies (SpliTech) ; Conference date: 23-09-2020 Through 26-09-2020",

}

Solic, P, Kapetanovic, AL, Zupanovic, T, Kovacevic, I, Perkovic, T & Popovski, P 2020, IoT Wallet: Machine Learning-based Sensor Portfolio Application. in P Solic, S Nizetic, JJPC Rodrigues, JJPC Rodrigues, D Lopez-de-Ipina Gonzalez-de-Artaza, T Perkovic, L Catarinucci & L Patrono (eds), 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech)., 9243699, IEEE, 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech), Split, Croatia, 23/09/2020. https://doi.org/10.23919/SpliTech49282.2020.9243699

IoT Wallet: Machine Learning-based Sensor Portfolio Application. / Solic, Petar; Kapetanovic, Ante Lojic; Zupanovic, Tomislav et al.
2020 5th International Conference on Smart and Sustainable Technologies (SpliTech). ed. / Petar Solic; Sandro Nizetic; Joel J. P. C. Rodrigues; Joel J. P.C. Rodrigues; Diego Lopez-de-Ipina Gonzalez-de-Artaza; Toni Perkovic; Luca Catarinucci; Luigi Patrono. IEEE, 2020. 9243699.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - IoT Wallet

T2 - 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech)

AU - Solic, Petar

AU - Kapetanovic, Ante Lojic

AU - Zupanovic, Tomislav

AU - Kovacevic, Ivo

AU - Perkovic, Toni

AU - Popovski, Petar

PY - 2020/11/4

Y1 - 2020/11/4

N2 - 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.

AB - 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.

KW - Internet of Things

KW - LoRa

KW - deep learning

KW - long short-term memory neural networks

KW - time series modeling

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U2 - 10.23919/SpliTech49282.2020.9243699

DO - 10.23919/SpliTech49282.2020.9243699

M3 - Article in proceeding

SN - 978-1-7281-7363-4

BT - 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech)

A2 - Solic, Petar

A2 - Nizetic, Sandro

A2 - Rodrigues, Joel J. P. C.

A2 - Rodrigues, Joel J. P.C.

A2 - Lopez-de-Ipina Gonzalez-de-Artaza, Diego

A2 - Perkovic, Toni

A2 - Catarinucci, Luca

A2 - Patrono, Luigi

PB - IEEE

Y2 - 23 September 2020 through 26 September 2020

ER -

Solic P, Kapetanovic AL, Zupanovic T, Kovacevic I, Perkovic T, Popovski P. IoT Wallet: Machine Learning-based Sensor Portfolio Application. In Solic P, Nizetic S, Rodrigues JJPC, Rodrigues JJPC, Lopez-de-Ipina Gonzalez-de-Artaza D, Perkovic T, Catarinucci L, Patrono L, editors, 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech). IEEE. 2020. 9243699 doi: 10.23919/SpliTech49282.2020.9243699

IoT Wallet: Machine Learning-based Sensor Portfolio Application

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