Third party funded individual grant
Acronym: AMMOD
Start date : 01.11.2019
End date : 31.10.2022
Website: https://www.zfmk.de/de/forschung/projekte/ammod-eine-wetterstation-fuer-artenvielfalt
This project is funded by the Federal Ministry of Education and Research (BMBF) as part of the AMMOD project. The implementation of the project is overseen by the German Aerospace Center (DLR).
Our planet loses biodiversity year after year. Since 1990, the number of insects and birds in Central Europe has fallen sharply, which has been confirmed by individual studies. However, there is no comprehensive collection and scientific evaluation of such data, as is the case, for example, in climate research. The main reason being that technical prerequisites and infrastructures are lacking.
The AMMOD project combines innovative technologies and adapts them to automatize the detection of species, in analogy to continuous measurements achieved with autonomous weather stations.
Analogously, we design in this subproject "weather stations of biodiversity". These will make it possible to monitor the occurrence of insects, mammals, birds, pollen, spores, etc. using various sensor technologies such as DNA barcoding, image recognition and bioacoustics. The challenge in designing this platform is that, on the one hand, such stations have to process, store, and transmit large amounts of data via mobile radio. On the other hand, the available resources in the field are limited (energy based on solar or wind power for a self-sufficient power supply, data storage capacity and communication bandwidth).
This project is funded by the Federal Ministry of Education and Research (BMBF) as part of the AMMOD project. The implementation of the project is overseen by the German Aerospace Center (DLR).
Our planet loses biodiversity year after year. Since 1990, the number of insects and birds in Central Europe has fallen sharply, which has been confirmed by individual studies. However, there is no comprehensive collection and scientific evaluation of such data, as is the case, for example, in climate research. The main reason being that technical prerequisites and infrastructures are lacking.
The AMMOD project combines innovative technologies and adapts them to automatize the detection of species, in analogy to continuous measurements achieved with autonomous weather stations. For this purpose, the following modules are developed:
For the automated monitoring of the occurrence of different species in extensive, often inaccessible areas, these AMMOD technologies as well as the storage, processing and transmission of their data must be integrated on a generic platform, which serves as a "weather station of biodiversity". This platform must be equipped with various sensors and actuators and configurable with various software and hardware components. The challenge in designing this platform is that, on the one hand, such stations have to process, store, and transmit large amounts of data via mobile radio. On the other hand, the available resources in the field are limited (energy based on solar or wind power for a self-sufficient power supply, data storage capacity and communication bandwidth).
Our subproject deals with sensor data processing and storage within the base station. The subproject has two main objectives. On the one hand, designing a hardware architecture for the AMMOD base station which enables the processing and storage of sensor data energy-efficiently and in real time, but which can be generically adapted for the different application domains. On the other hand, the partners of other subprojects will be supported in the implementation of their algorithms in software and hardware, since the programming of the hardware architectures embedded in AMMOD stations (especially multi-core computers and programmable hardware components) requires expert knowledge. It is a declared goal to provide a design methodology that automatically generates an optimized hardware-software configuration of the platform from an intuitive and graphical description of data processing algorithms, so that experts from other areas are also able to program the platform without the corresponding know-how.