Development of sensor nodes and sensors for smart farming

Technical report


  • Moritz Schlagmann Infineon Technologies AG, Am Campeon 1-15, 85579 Neubiberg, Germany and Technische Universität Chemnitz, Reichenhainer Str. 70, 09107 Chemnitz, Germany
  • Jos Balendonck Wageningen University & Research, Droevendaalsesteeg 1, 6708 Wageningen, The Netherlands
  • Thomas Otto Technische Universität Chemnitz, Reichenhainer Str. 70, 09107 Chemnitz, Germany and Fraunhofer ENAS, Technologie Campus 3, 09126 Chemnitz, Germany
  • Michelle Brandao Silva de Assis Kurt-Schwabe-Institut für Mess- und Sensortechnik Meinsberg e.V., 04736 Waldheim, Germany and Physikalische Chemie, Technische Universität Dresden, 01062 Dresden, Germany
  • Michael Mertig Kurt-Schwabe-Institut für Mess- und Sensortechnik Meinsberg e.V., 04736 Waldheim, Germany and Physikalische Chemie, Technische Universität Dresden, 01062 Dresden, Germany
  • Stefan Hess Infineon Technologies AG, Am Campeon 1-15, 85579 Neubiberg, Germany



agriculture, sensor systems, leaf wetness sensor, nitrate sensor, sustainability
Graphical Abstract


The world population is continuously increasing. Smart farming is required to keep up with this development by producing more food in a sustainable way. In many new sensor solution developments, the results of the sensor itself is at the target, but the whole solution fails to meet the requirements of the agriculture sensing use cases: the developments suffer from singular approaches with a constricted view solely on the sensor, which might be exchangeable. In this article, we present a holistic approach that can help to overcome these challenges. This approach considers the whole use case, from sense, compute, and connect to power. The approach is discussed with the example of the PLANtAR project, where we develop a soil nitrate sensor and a new leaf wetness and microclimate sensor for application in a greenhouse. The resulting sensor is integrated into a sensor node and compared to a state-of-the-art system. The work shows what is needed to assess the best tradeoffs for agriculture use cases based on a horticulture application.


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J. P. Giraldo, H. Wu, G. M. Newkirk, S. Kruss, Nanobiotechnology approaches for engineering smart plant sensors, Nature Nanotechnology 14 (2019) 541-553.

M.S. Ben Saleh, R. Saida, Y.H. Kacem, M. Abid, Wireless Sensor Network Design Methodologies: A Survey, Journal of Sensors 2020 (2020) 9592836.

M. Collotta, G. Pau, T. Talty, O. K. Tonguz, Bluetooth 5: A Concrete Step Forward toward the IoT, IEEE Communications Magazine 56 (2018) 125-131.

B. Warneke, M. Last, B. Liebowitz, K. S. J. Pister, Smart Dust: communicating with a cubic-millimeter computer, Computer 34 (2001) 44-51.

F. Liechti, S. Bauer, K. L. Dhanjal-Adams, T. Emmenegger, P. Zehtindjiev, S. Hahn, Miniaturized multi-sensor loggers provide new insight into year-round flight behaviour of small trans-Sahara avian migrants, Movement Ecology 6 (2018) 19.

M. S. Farooq, S. Riaz, M. A. Helou, F. S. Khan, A. Abid, A. Alvi, Internet of Things in Greenhouse Agriculture: A Survey on Enabling Technologies, Applications, and Protocols, IEEE Access 10 (2022) 53374-53397.

Harriet Sumnall, Agriculture’s Digital Transformation: AG-Tech and Farming, ABIresearch, 2019.

G. V. Lowry, A. Avellan, L. M. Gilbertson, Opportunities and challenges for nanotechnology in the agri-tech revolution, Nature Nanotechnology 14 (2019) 517-522.

K. L. Lueth, M. Hasan, S. Sinha, S. Annaswamy, P. Wegner, F. Bruegge, M. Kulezak, State of IoT - Spring 2022, IoT Analytics GmbH, 2022.

V. K. Quy, N. V. Hau, D. V. Anh, N. M. Quy, N. T. Ban, S. Lanza, G. Randazzo, A. Muzirafuti, IoT-Enabled Smart Agriculture: Architecture, Applications, and Challenges, Applied Sciences 12 (2022) 3396.

V. P. Kour, S. Arora, Recent Developments of the Internet of Things in Agriculture, IEEE Access 8 (2020) 129924-129957.

J. Fraden, Handbook of modern sensors: physics, designs, and applications, 5th edition, Springer, Cham Heidelberg, New York, Dordrecht, London, 2016.

T. Rowlandson, M. Gleason, P. Sentelhas, T. Gillespie, C. Thomas, B. Hornbuckle, Reconsidering Leaf Wetness Duration Determination for Plant Disease Management, Plant Disease 99 (2015) 310-319.

T. Boulard, M. Mermier, J. Fargues, N. Smits, M. Rougier, J.C. Roy, Tomato leaf boundary layer climate: implications for microbiological whitefly control in greenhouses, Agricultural and Forest Meteorology 110 (2002) 159-176.

A. van Westreenen, N. Zhang, J. C. Douma, J. B. Evers, N. P. R. Anten, L. F. M. Marcelis, Substantial differences occur between canopy and ambient climate: Quantification of interactions in a greenhouse-canopy system, PLoS ONE 15 (2020) e0233210.

B. Jos, E. A. van Os, R. van der Schoor, B. A. J. van Tuijl, L. C. P. Keizer, Monitoring spatial and temporal distribution of temperature and relative humidity in greenhouses based on wireless sensor technology, in: International Conference on Agricultural Engineering-AgEng, Clermont Ferrand, France, 2010, pp. 443-452.

PHYTOS 31, Leaf Wetness Sensor, METER Environment. (accessed November 8, 2022).

Leaf Wetness Sensor, Spectrum Technologies, (accessed November 8, 2022).

M. Schlagmann, F. Selbmann, M. Haubold, M. Vobl, T. Otto, Miniaturized and Highly Integrated Humidity Sensor with Biocompatible Sensing Material for Smart Farming, 2022 Smart Systems Integration, IEEE, Grenoble, France, 2022, 22114757.

M. Silva de Assis, K. Trommer, A. Kick, J. Schwarz, M. Mertig, Stabilitätsuntersuchungen an miniaturisierten Nitratsensoren, AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2021, pp. 193-198.

R. Cheour, S. Khriji, M. abid, O. Kanoun, Microcontrollers for IoT: Optimizations, Computing Paradigms, and Future Directions, 2020 IEEE 6th World Forum on Internet of Things, IEEE, New Orleans, LA, USA, 2020, 20055793.

F. Gu, J. Niu, L. Jiang, X. Liu, M. Atiquzzaman, Survey of the low power wide area network technologies, Journal of Network and Computer Applications 149 (2020) 102459.

K. Mekki, E. Bajic, F. Chaxel, F. Meyer, Overview of Cellular LPWAN Technologies for IoT Deployment: Sigfox, LoRaWAN, and NB-IoT, 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, Athens, 2018, pp. 197-202.

G. Callebaut, G. Leenders, J. Van Mulders, G. Ottoy, L. De Strycker, L. Van der Perre, The Art of Designing Remote IoT Devices—Technologies and Strategies for a Long Battery Life, Sensors 21 (2021) 913

O. Kanoun, S. Bradai, S. Khriji, G. Bouattour, D. El Houssaini, M. Ben Ammar, S. Naifar, A. Bouhamed, F. Derbel, C. Viehweger, Energy-Aware System Design for Autonomous Wireless Sensor Nodes, Sensors 21 (2021) 548.


12-07-2023 — Updated on 12-07-2023

How to Cite

Schlagmann, M., Balendonck, J., Otto, T., Brandao Silva de Assis, M., Mertig, M., & Hess, S. (2023). Development of sensor nodes and sensors for smart farming: Technical report. Journal of Electrochemical Science and Engineering, 13(5), 825–838.



8th RSE SEE & 9th Kurt Schwabe symposium Special Issue