research-article

Modeling the Carbon Footprint of Battery-Powered IoT Sensor Nodes for Environmental-Monitoring Applications

Authors:

Pol Maistriaux,

Thibault Pirson,

Maxime Schramme,

Jérôme Louveaux,

David BolAuthors Info & Claims

IoT '22: Proceedings of the 12th International Conference on the Internet of Things

Pages 9 - 16

https://doi.org/10.1145/3567445.3567448

Published: 05 January 2023 Publication History

IoT '22: Proceedings of the 12th International Conference on the Internet of Things

Modeling the Carbon Footprint of Battery-Powered IoT Sensor Nodes for Environmental-Monitoring Applications

Pages 9 - 16

Abstract
References

Abstract

The Internet-of-Things (IoT) is frequently presented as an effective tool to monitor our environment and subsequently reduce the environmental footprint of human activities. However, the environmental footprint of IoT nodes themselves is often overlooked. The standardized life-cycle assessment (LCA) methodology can help in this respect. While production impacts can be estimated using LCA databases, use phase impacts are complex to model for battery-powered IoT nodes, commonly used in environmental monitoring. Indeed, battery maintenance operations involve component replacement, transportation and depend on the service lifetime which is strongly influenced by the use phase scenario. We therefore propose a comprehensive open-source parametric model of battery-powered IoT nodes use phase in environmental monitoring applications. The model assesses the overall environmental footprint, including deployment and maintenance, with an enhanced service lifetime evaluation. Using a custom node prototype, additionally validating the underlying power consumption modeling, we then analyze a case study. The use phase model fosters eco-design by allowing the optimal battery capacity identification and highlighting the impact of various parameters on the carbon footprint, e.g., use phase scenario, operating conditions, node positioning, transport scheme, and replacement strategy. Finally, the model can easily be transposed to evaluate economic aspects, motivating the environmental and economic co-optimization.

References

[1]

Ambiq. 2022. Apollo3 Blue MCU - Datasheet. Technical Report.

[2]

Jérémy Bonvoisin, Alan Lelah, Fabrice Mathieux, and Daniel Brissaud. 2012. An environmental assessment method for wireless sensor networks. Journal of Cleaner Production 33 (2012), 145–154.

[3]

Jeremy Bonvoisin, Alan Lelah, Fabrice Mathieux, and Daniel Brissaud. 2014. An integrated method for environmental assessment and ecodesign of ICT-based optimization services. Journal of Cleaner Production 68 (2014), 144–154. https://doi.org/10.1016/j.jclepro.2014.01.003.

[4]

Bosch. 2022. BME680 - Low Power Gas, Pressure, Temperature & Humidity - Datasheet. Technical Report.

[5]

Chesney Buyle, Bart Thoen, Bert Cox, Matthias Alleman, Stijn Wielandt, and Lieven De Strycker. 2019. Ultra-Low-Power Smart Sensing Platform for Urban Sound Event Monitoring. Proceedings of the 2019 Symposium on Information Theory and Signal Processing in the Benelux, 35–40. http://www.w-i-c.org/

[6]

Gilles Callebaut, Guus Leenders, Jarne Van Mulders, Geoffrey Ottoy, Lieven De Strycker, and Liesbet Van der Perre. 2021. The Art of Designing Remote IoT Devices—Technologies and Strategies for a Long Battery Life. Sensors 21, 3 (Jan. 2021), 913. https://doi.org/10.3390/s21030913

[7]

Gilles Callebaut and Liesbet Van der Perre. 2020. Characterization of LoRa Point-to-Point Path Loss: Measurement Campaigns and Modeling Considering Censored Data. IEEE Internet of Things Journal 7, 3 (March 2020), 1910–1918. https://doi.org/10.1109/JIOT.2019.2953804

[8]

Min Chen and G.A. Rincon-Mora. 2006. Accurate Electrical Battery Model Capable of Predicting Runtime and I-V Performance. IEEE Transactions on Energy Conversion 21, 2 (June 2006), 504–511. https://doi.org/10.1109/TEC.2006.874229

[9]

Louis-Philippe P. V. P. Clément, Quentin E. S. Jacquemotte, and Lorenz M. Hilty. 2020. Sources of Variation in Life Cycle Assessments of Smartphones and Tablet Computers. Environmental Impact Assessment Review 84 (Sept. 2020), 106416. https://doi.org/10.1016/j.eiar.2020.106416

[10]

Louis-Philippe P.-V.P. Clément, Quentin E.S. Jacquemotte, and Lorenz M. Hilty. 2020. Sources of variation in life cycle assessments of smartphones and tablet computers. Environmental Impact Assessment Review 84 (2020), 106416.

[11]

D. Culler, D. Estrin, and M. Srivastava. 2004. Guest Editors’ Introduction: Overview of Sensor Networks. Computer 37, 8 (Aug. 2004), 41–49. https://doi.org/10.1109/MC.2004.93

Digital Library

[12]

Sujit Das and Elizabeth Mao. 2020. The global energy footprint of information and communication technology electronics in connected Internet-of-Things devices. Sustainable Energy, Grids and Networks 24 (2020), 100408. https://doi.org/10.1016/j.segan.2020.100408.

[13]

International Organization for Standardization. 2006. ISO 14044:2006. https://www.iso.org/standard/38498.html.

[14]

Mohamed Hefeeda and Majid Bagheri. 2007. Wireless Sensor Networks for Early Detection of Forest Fires. In 2007 IEEE International Conference on Mobile Adhoc and Sensor Systems. IEEE, Pisa, Italy, 1–6. https://doi.org/10.1109/MOBHOC.2007.4428702

[15]

ITU. 2020. Internet Waste: Geneva: International Telecommunication Union and the WEEE Forum (Licence: CC BY-NC-SA 3.0 IGO). https://www.itu.int/en/ITU-D/Environment/Documents/Publications/2020/Internet-Waste%202020.pdf?csf=1&e=iQq5Zi, accessed August 2022.

[16]

Mihai T. Lazarescu. 2013. Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications. IEEE Journal on Emerging and Selected Topics in Circuits and Systems 3, 1 (March 2013), 45–54. https://doi.org/10.1109/JETCAS.2013.2243032

[17]

Jens Malmodin and Dag Lundén. 2018. The energy and carbon footprint of the global ICT and E&M sectors 2010-2015. Sustainability 10, 9 (2018), 3027. https://doi.org/10.3390/su10093027.

[18]

Borja Martinez, Màrius Montón, Ignasi Vilajosana, and Joan Daniel Prades. 2015. The Power of Models: Modeling Power Consumption for IoT Devices. IEEE Sensors Journal 15, 10 (Oct. 2015), 5777–5789. https://doi.org/10.1109/JSEN.2015.2445094

[19]

Antonio Molina-Pico, David Cuesta-Frau, Alvaro Araujo, Javier Alejandre, and Alba Rozas. 2016. Forest Monitoring and Wildland Early Fire Detection by a Hierarchical Wireless Sensor Network. Journal of Sensors 2016(2016), 1–8. https://doi.org/10.1155/2016/8325845

[20]

Élodie Morin, Mickael Maman, Roberto Guizzetti, and Andrzej Duda. 2017. Comparison of the Device Lifetime in Wireless Networks for the Internet of Things. IEEE Access 5(2017), 7097–7114. https://doi.org/10.1109/ACCESS.2017.2688279

[21]

Thibault Pirson and David Bol. 2021. Assessing the embodied carbon footprint of IoT edge devices with a bottom-up life-cycle approach. Journal of Cleaner Production 322 (2021), 128966.

[22]

Tomo Popović, Nedeljko Latinović, Ana Pešić, Žarko Zečević, Božo Krstajić, and Slobodan Djukanović. 2017. Architecting an IoT-enabled Platform for Precision Agriculture and Ecological Monitoring: A Case Study. Computers and Electronics in Agriculture 140 (Aug. 2017), 255–265. https://doi.org/10.1016/j.compag.2017.06.008

[23]

Ernesto Quisbert-Trujillo, Thomas Ernst, Karine Evrard Samuel, Emmanuelle Cor, and Elise Monnier. 2020. Lifecycle Modeling for the Eco Design of the Internet of Things. Procedia CIRP 90 (Jan. 2020), 97–101. https://doi.org/10.1016/j.procir.2020.02.120

[24]

Mina Rady, Jean-Philippe Georges, and Francis Lepage. 2021. Can Energy Optimization Lead to Economic and Environmental Waste in LPWAN Architectures?ETRI Journal 43, 2 (2021), 173–183. https://doi.org/10.4218/etrij.2019-0524

[25]

Semtech. 2020. SX1276/77/78 - 137-1050 MHz Ultra Low Power Long Range Transceiver - Datasheet. Technical Report.

[26]

Jalpa Shah and Biswajit Mishra. 2016. IoT Enabled Environmental Monitoring System for Smart Cities. In 2016 International Conference on Internet of Things and Applications (IOTA). 383–388. https://doi.org/10.1109/IOTA.2016.7562757

[27]

Ritesh Kumar Singh, Priyesh Pappinisseri Puluckul, Rafael Berkvens, and Maarten Weyn. 2020. Energy Consumption Analysis of LPWAN Technologies and Lifetime Estimation for IoT Application. Sensors 20, 17 (Aug. 2020), 4794. https://doi.org/10.3390/s20174794

[28]

Jesús Martín Talavera, Luis Eduardo Tobón, Jairo Alejandro Gómez, María Alejandra Culman, Juan Manuel Aranda, Diana Teresa Parra, Luis Alfredo Quiroz, Adolfo Hoyos, and Luis Ernesto Garreta. 2017. Review of IoT Applications in Agro-Industrial and Environmental Fields. Computers and Electronics in Agriculture 142 (Nov. 2017), 283–297. https://doi.org/10.1016/j.compag.2017.09.015

Digital Library

[29]

Bart Thoen, Gilles Callebaut, Guus Leenders, and Stijn Wielandt. 2019. A Deployable LPWAN Platform for Low-Cost and Energy-Constrained IoT Applications. Sensors 19, 3 (2019). https://doi.org/10.3390/s19030585

Cited By

Krug SHutschenreuther TToepfer HO’Nils M(2024)Impact of Real-World Energy Consumption Variance on Internet of Things Node Lifetime PredictionsElectronics10.3390/electronics1323457813:23(4578)Online publication date: 21-Nov-2024
https://doi.org/10.3390/electronics13234578
Mytton DLundén DMalmodin J(2024)Network energy use not directly proportional to data volume: The power model approach for more reliable network energy consumption calculationsJournal of Industrial Ecology10.1111/jiec.1351228:4(966-980)Online publication date: 21-Jun-2024
https://doi.org/10.1111/jiec.13512
Ohs RJanson HSchmidt AGerhorst LHerzog BHönig T(2024)Dirty Electrons: On the Carbon Intensity of Stored Energy2024 IEEE 15th International Green and Sustainable Computing Conference (IGSC)10.1109/IGSC64514.2024.00018(45-51)Online publication date: 2-Nov-2024
https://doi.org/10.1109/IGSC64514.2024.00018

Index Terms

Modeling the Carbon Footprint of Battery-Powered IoT Sensor Nodes for Environmental-Monitoring Applications
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Wireless integrated network sensors
  2. Power and energy
    1. Impact on the environment
    2. Power estimation and optimization

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IoT '22: Proceedings of the 12th International Conference on the Internet of Things

November 2022

259 pages

ISBN:9781450396653

DOI:10.1145/3567445

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 05 January 2023

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Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture
Fonds européen de développement régional

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IoT 2022

IoT 2022: The 12th International Conference on the Internet of Things

November 7 - 10, 2022

Delft, Netherlands

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Cited By

Krug SHutschenreuther TToepfer HO’Nils M(2024)Impact of Real-World Energy Consumption Variance on Internet of Things Node Lifetime PredictionsElectronics10.3390/electronics1323457813:23(4578)Online publication date: 21-Nov-2024
https://doi.org/10.3390/electronics13234578
Mytton DLundén DMalmodin J(2024)Network energy use not directly proportional to data volume: The power model approach for more reliable network energy consumption calculationsJournal of Industrial Ecology10.1111/jiec.1351228:4(966-980)Online publication date: 21-Jun-2024
https://doi.org/10.1111/jiec.13512
Ohs RJanson HSchmidt AGerhorst LHerzog BHönig T(2024)Dirty Electrons: On the Carbon Intensity of Stored Energy2024 IEEE 15th International Green and Sustainable Computing Conference (IGSC)10.1109/IGSC64514.2024.00018(45-51)Online publication date: 2-Nov-2024
https://doi.org/10.1109/IGSC64514.2024.00018

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