Water quality analysis using mmWave radars

Dariush Salami; Anni Juvakoski; Riku Vahala; Michael Beigl; Stephan Sigg

doi:10.1109/PerComWorkshops56833.2023.10150256

Water quality analysis using mmWave radars

Dariush Salami, Anni Juvakoski, Riku Vahala, Michael Beigl, Stephan Sigg

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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Abstract

Water quality and drinkability assessment are of high importance for various applications from monitoring water utilities to emergency water source evaluation. Traditionally, water quality assessment is done in laboratories with spacious and expensive equipment. We propose a wearable, mm Wave Frequency-Modulated Continuous Wave (FMCW) radar based system to assess water quality. Given its small form-factor, low price, and its robustness to lighting and weather conditions, this family of radars can be integrated into wearable devices such as smart-watches, smart glasses, smart rings, etc. Equipped with mm Wave radar sensors, such wearables enable seamless monitoring of water quality in hands free settings. The proposed system is able to directly process the In-phase and Quadrature (IQ) data generated by the radar to detect varying levels of different contaminants in four different kinds of water. Specifically, it can identify different concentrations of salt with 100% accuracy, namely nitrate and chloride, as well as detecting different types of waters including Reverse Osmosis (RO), tap, river, and well water with 99.1 % accuracy.

Original language	English
Title of host publication	2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023
Publisher	IEEE
Pages	412-415
Number of pages	4
ISBN (Electronic)	978-1-6654-5381-3
DOIs	https://doi.org/10.1109/PerComWorkshops56833.2023.10150256
Publication status	Published - 2023
MoE publication type	A4 Conference publication
Event	IEEE International Conference on Pervasive Computing and Communications Workshops - Atlanta, United States Duration: 13 Mar 2023 → 17 Mar 2023

Publication series

Name	IEEE International Conference on Pervasive Computing and Communications Workshops
ISSN (Electronic)	2766-8576

Conference

Conference	IEEE International Conference on Pervasive Computing and Communications Workshops
Abbreviated title	PerCom
Country/Territory	United States
City	Atlanta
Period	13/03/2023 → 17/03/2023

Keywords

AI
ML
mmWave radar
water quality analysis

Access to Document

10.1109/PerComWorkshops56833.2023.10150256

Water_Quality_AnalysisAccepted author manuscript, 1.41 MB

Cite this

Salami, D., Juvakoski, A., Vahala, R., Beigl, M., & Sigg, S. (2023). Water quality analysis using mmWave radars. In 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023 (pp. 412-415). (IEEE International Conference on Pervasive Computing and Communications Workshops). IEEE. https://doi.org/10.1109/PerComWorkshops56833.2023.10150256

@inproceedings{f44dfc4ed58f427ca80df961dc986616,

title = "Water quality analysis using mmWave radars",

abstract = "Water quality and drinkability assessment are of high importance for various applications from monitoring water utilities to emergency water source evaluation. Traditionally, water quality assessment is done in laboratories with spacious and expensive equipment. We propose a wearable, mm Wave Frequency-Modulated Continuous Wave (FMCW) radar based system to assess water quality. Given its small form-factor, low price, and its robustness to lighting and weather conditions, this family of radars can be integrated into wearable devices such as smart-watches, smart glasses, smart rings, etc. Equipped with mm Wave radar sensors, such wearables enable seamless monitoring of water quality in hands free settings. The proposed system is able to directly process the In-phase and Quadrature (IQ) data generated by the radar to detect varying levels of different contaminants in four different kinds of water. Specifically, it can identify different concentrations of salt with 100% accuracy, namely nitrate and chloride, as well as detecting different types of waters including Reverse Osmosis (RO), tap, river, and well water with 99.1 % accuracy.",

keywords = "AI, ML, mmWave radar, water quality analysis",

author = "Dariush Salami and Anni Juvakoski and Riku Vahala and Michael Beigl and Stephan Sigg",

note = "Funding Information: This project has received funding from the European Union s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant agreement No. 813999, HPY Research Foundation and Nokia Foundation. Funding Information: ACKNOWLEDGMENT This project has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under the Marie Sk{\l}odowska-Curie Grant agreement No. 813999, HPY Research Foundation and Nokia Foundation. Publisher Copyright: {\textcopyright} 2023 IEEE. | openaire: EC/H2020/813999/EU//WINDMILL; IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom ; Conference date: 13-03-2023 Through 17-03-2023",

year = "2023",

doi = "10.1109/PerComWorkshops56833.2023.10150256",

language = "English",

series = "IEEE International Conference on Pervasive Computing and Communications Workshops",

publisher = "IEEE",

pages = "412--415",

booktitle = "2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023",

address = "United States",

}

Salami, D, Juvakoski, A, Vahala, R, Beigl, M & Sigg, S 2023, Water quality analysis using mmWave radars. in 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023. IEEE International Conference on Pervasive Computing and Communications Workshops, IEEE, pp. 412-415, IEEE International Conference on Pervasive Computing and Communications Workshops, Atlanta, United States, 13/03/2023. https://doi.org/10.1109/PerComWorkshops56833.2023.10150256

Water quality analysis using mmWave radars. / Salami, Dariush; Juvakoski, Anni; Vahala, Riku et al.
2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023. IEEE, 2023. p. 412-415 (IEEE International Conference on Pervasive Computing and Communications Workshops).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Water quality analysis using mmWave radars

AU - Salami, Dariush

AU - Juvakoski, Anni

AU - Vahala, Riku

AU - Beigl, Michael

AU - Sigg, Stephan

N1 - Funding Information: This project has received funding from the European Union s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant agreement No. 813999, HPY Research Foundation and Nokia Foundation. Funding Information: ACKNOWLEDGMENT This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant agreement No. 813999, HPY Research Foundation and Nokia Foundation. Publisher Copyright: © 2023 IEEE. | openaire: EC/H2020/813999/EU//WINDMILL

PY - 2023

Y1 - 2023

N2 - Water quality and drinkability assessment are of high importance for various applications from monitoring water utilities to emergency water source evaluation. Traditionally, water quality assessment is done in laboratories with spacious and expensive equipment. We propose a wearable, mm Wave Frequency-Modulated Continuous Wave (FMCW) radar based system to assess water quality. Given its small form-factor, low price, and its robustness to lighting and weather conditions, this family of radars can be integrated into wearable devices such as smart-watches, smart glasses, smart rings, etc. Equipped with mm Wave radar sensors, such wearables enable seamless monitoring of water quality in hands free settings. The proposed system is able to directly process the In-phase and Quadrature (IQ) data generated by the radar to detect varying levels of different contaminants in four different kinds of water. Specifically, it can identify different concentrations of salt with 100% accuracy, namely nitrate and chloride, as well as detecting different types of waters including Reverse Osmosis (RO), tap, river, and well water with 99.1 % accuracy.

AB - Water quality and drinkability assessment are of high importance for various applications from monitoring water utilities to emergency water source evaluation. Traditionally, water quality assessment is done in laboratories with spacious and expensive equipment. We propose a wearable, mm Wave Frequency-Modulated Continuous Wave (FMCW) radar based system to assess water quality. Given its small form-factor, low price, and its robustness to lighting and weather conditions, this family of radars can be integrated into wearable devices such as smart-watches, smart glasses, smart rings, etc. Equipped with mm Wave radar sensors, such wearables enable seamless monitoring of water quality in hands free settings. The proposed system is able to directly process the In-phase and Quadrature (IQ) data generated by the radar to detect varying levels of different contaminants in four different kinds of water. Specifically, it can identify different concentrations of salt with 100% accuracy, namely nitrate and chloride, as well as detecting different types of waters including Reverse Osmosis (RO), tap, river, and well water with 99.1 % accuracy.

KW - AI

KW - ML

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KW - water quality analysis

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U2 - 10.1109/PerComWorkshops56833.2023.10150256

DO - 10.1109/PerComWorkshops56833.2023.10150256

M3 - Conference article in proceedings

AN - SCOPUS:85164140445

T3 - IEEE International Conference on Pervasive Computing and Communications Workshops

SP - 412

EP - 415

BT - 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023

PB - IEEE

T2 - IEEE International Conference on Pervasive Computing and Communications Workshops

Y2 - 13 March 2023 through 17 March 2023

ER -

Salami D, Juvakoski A, Vahala R, Beigl M, Sigg S. Water quality analysis using mmWave radars. In 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023. IEEE. 2023. p. 412-415. (IEEE International Conference on Pervasive Computing and Communications Workshops). doi: 10.1109/PerComWorkshops56833.2023.10150256

Water quality analysis using mmWave radars

Abstract

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Keywords

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WINDMILL: Integrating Wireless Communication ENgineering and MachIne Learning

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Water quality analysis using mmWave radars

Abstract

Publication series

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Keywords

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Projects

WINDMILL: Integrating Wireless Communication ENgineering and MachIne Learning

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