Towards Digital Twins for Multi-Sensor Land and Plant Monitoring

Rui Neves Madeira, Pedro Albuquerque Santos, Oskars Java, Torsten Priebe, Eduardo Graça, Eszter Sarközi, Bernward Asprion, Raquel Pinto Bello Gomez

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)
70 Downloads (Pure)


Small and medium-sized farms struggle with increased needs for monitoring in different dimensions, even by having to respond to regulatory requirements, e.g., by the global push to reduce pesticides and to improve soil health. Moreover, with the rising needs for food production there has been an effort to shift agriculture into a new era, in which the sector needs to be modernized by using new digital technologies. The goal of our research work is to provide farmers with a reliable "digital twin", i.e., a monitoring ecosystem that allows them to visualize multi-sensor data collected from their fields, but also to "plug in" predictive models, e.g., for plant disease prediction. The paper presents an extensible solution, designed in co-creation with stakeholders, that can use a wide range of "sensors", ranging from free satellite images, low-cost off-the-shelf sensors, to even novel technologies, such as odour sensors. The TWINSOR concept is introduced, but also a first prototype applied to the vineyard is described as a first result.


  • digital agriculture
  • digital twin
  • HCI
  • IoT
  • mobile application
  • multi-sensor monitoring
  • vineyard


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