Introduction of information technologies in the regional agricultural infrastructure is of special interest for its future development and modernization. New trends in agricultural production in the world are based on the advanced technologies, including widely spread use of information technologies. This leads to a new concept, so called precision agriculture, which takes into account local variations of the crop and accordingly adjust all agro-technical measures, thus providing more efficient and healthier agricultural production with considerable savings.
Wireless Sensor Network (WSN) and Remote Sensing are of special interest in precision agriculture, since they provide timely access to in-field data and prompt reactions. Consequently, agro-technical measures can be administrated more precisely thus leading to a higher level of food quality, environmental protection and significant savings. Another benefit is better understanding of the underlying processes in agriculture and validation and improvement of the applied models. WSN are composed of multiple sensors which communicate through wireless connections and acquire data of interest. In terms of precision agriculture, sensors acquire data such as: humidity, soil temperature, illumination, plant diameter growth rate, etc, within a longer time interval. Larger number (tens or hundreds) of sensors distributed appropriately allow for timely and precise crop monitoring, and wireless communication enables the deployment of sensor networks on practically all terrains.
Remote sensing is based on the usage of low-cost unmanned aerial vehicles, capable of acquiring important data, otherwise inacceptable from the ground. Images gathered in this way provide simple identification of crop condition, by assessing the bio-mass or by detecting parts of the field with nutrition deficiency.
Main responsibilities of BioSense Center:
- Developing Web interface and database implementation on existing equipment
- Analysis of existing motes and application requirements in agriculture and the development of a WSN gateway prototype
- Statistical modelling of remote data collection and coding in WSN
- Synchronization in WSN and algorithms for the classification of remotely collected data
- Implementation of WSN motes prototypes for use in agriculture
- Digital signal processing at the physical level of WSN and algorithms for detecting changes in multi-temporal remotely collected images
- Testing and development of a protocol on the second level in WSN, and use regression analysis in estimation of biophysical and geophysical land parameters in Remote Sensing
- Integration of results and expert system development