Methods and Services of Data processing for Data Logged by Automatic Data Acquisition Systems

Automated data logging on agricultural machinery based on GPS and open communication standards for electronics will be applied more and more as fast as the demands for documentation in crop production increase. But to collect many data doesn 't make sense without having powerful tools for data processing analysis. This project investigated methods to master this task and developed a data management system. The amplitude of information that raw data contains should be conditioned in a compact and concise form. For this, different user groups, which want to evaluate data from different aspects, had to be considered. The first period of investigations, in which a first evaluation tool has been developed on a Microsoft Access® database system, resulted in the cognition, that the best way to realize a stable and easy to use data management system is to establish a central server platform for storing and processing data with remote data access by the users. A MySQL database server was used for data keeping and parts of processing. The Script Language PI-IP was used to enable remote data access and the rest of data processing. PHP scripts are usually embedded in the code of HTML sites, which build up the user interface. Access to the data management system occurs with a common browser software via Internet from anywhere. No additional software installations on the local PC are necessary. All of the used software components on the data server are Open Source and for free. The developed data management system is built up in a modular way and it's not finished, but can be upgraded continuously by adding more modules. Especially Interfaces for data exchange have to be defined in the future to make the information available for other software tools and to minimise redundancy at data entry.     «

Automated data logging on agricultural machinery based on GPS and open communication standards for electronics will be applied more and more as fast as the demands for documentation in crop production increase. But to collect many data doesn 't make sense without having powerful tools for data processing analysis. This project investigated methods to master this task and developed a data management system. The amplitude of information that raw data contains should be conditioned in a compact and...     »