A new Collaborative Platform for Research in Smart Farming
Author(s) -
Olivier Debauche,
Saïd Mahmoudi,
Pierre Manneback,
Jérôme Bindelle,
Frédéric Lebeau
Publication year - 2020
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2020.10.061
Subject(s) - computer science , encryption , benchmark (surveying) , confidentiality , computer security , data sharing , information sharing , world wide web , medicine , alternative medicine , geodesy , pathology , geography
The sharing of experimental dataset and benchmark between researchers is particularly import for the cross validation of models and algorithms that have been developed. In practice the sharing of data is difficult because certain legislations must be respected such as protecting privacy, copyrights, information confidentiality... etc. In this paper, we propose a scientific collaborative platform to share, exchange, and transfer data, applications, and models between researchers. This is only possible if we implement a high-level of encryption and security. The choice of encryption algorithms is crucial to ensure a long-term high level of protection against theft, willful alteration, and falsification. Our platform has been experimented within a community of researchers interested in cow behavior analysis based on Inertial Movement Unit and GPS data acquired by iPhone at high frequency (100 Hz).
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