Arbeitsgruppe Verteilte Systeme

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Smart fLAIr
A Smartphone App for the Fast Leaf Area Index Retrieval

The continuous exploration and monitoring of bio-physical crop parameters enabled by modern sensor technology in the context of Smart Farming is crucial for a sustainable agriculture. The leaf area index (LAI) is one of the most important parameters that serves as an indicator for the vital condition of plants and is a key enabler for a site-specific management. In-situ LAI monitoring has the potential to boost decision-making support for famers and to increase crop yields and farm output.

Smart fLAIr is a smartphone application developed for a reliable in-situ LAI estimation. It provides a non-destructive, radiation-based approach using the ambient light sensor of the smartphone and offers a cost-efficient alternative to commercial plant canopy analyzers.
Without special hard- and software requirements and due to a focus on simplicity and usability, a wide user group of many scientific disciplines, interested in a feasible LAI acquisition, is addressed by this app.

Smart fLAIr also allows to collect LAI data from sensor devices deployed in the field using Wireless Sensor Network technology. Recently, Smart fLAIr is extended by a crowd sensing feature enabling a collaborative and distributed acquisition of LAIs (v4.0 Nov 2017).

For questions, suggestions, and bug reports, please contact Jan Bauer.
We are happy for every feedback!


  • Jan Bauer, Bastian Siegmann, Thomas Jarmer, Nils Aschenbruck
    "Smart fLAIr: a Smartphone Application for Fast LAI Retrieval using Ambient Light Sensors"
    Proc. of the 11th IEEE Sensors Applications Symposium
    SAS, Catania, Italy, April 20-22, 2016, [pdf].
  • Jan Bauer, Bastian Siegmann, Thomas Jarmer, Nils Aschenbruck
    "Fast LAI Retrieval with Smart fLAIr"
    4th Mobile App Competition in conjunction with the 22nd ACM International Conference on Mobile Computing and Networking
    MobiCom, NYC, New York, USA, Oct. 3-7, 2016.
    pdf | slides | video trailer ]
  • Lars Hunning, Jan Bauer, Nils Aschenbruck
    "A Privacy Preserving Mobile Crowdsensing Architecture for a Smart Farming Application"
    accepted for the ACM Workshop on Mobile Crowdsensing Systems and Applications
    in conjunction with the 15th ACM Conference on Embedded Networked Sensor Systems
    SenSys, Delft, The Netherlands, Nov. 5-8, 2017, [pdf].


Disclaimer: This app is provided as it is and without any guarantee or liability. Use at your own risk.