HARVEST: an end-to-end solution for smart agriculture monitoring

HARVEST has been developed in collaboration with the American Farm School of Thessaloniki. Its goal is to harvest the knowledge that can be generated by the advanced processing of farm sensing data through applying cutting-edge analytics to address real-world problems with social impact. HARVEST adopts open-source technologies exclusively, such as Apache Kafka, Apache Flink, Apache Druid and PostgreSQL, and encapsulates state-of-the-art data science technologies for anomaly detection (https://datalab.csd.auth.gr/tools-apps/proud/) and useful insights’ extraction (https://www.microsoft.com/en-us/research/publication/metainsight-automatic-discovery-of-structured-knowledge-for-exploratory-data-analysis/).

The team: Ioannis Mavroudopoulos (PhD candidate), Thodoris Toliopoulos (post-doc), George Kynigopoulos (graduate student), Andreas Andreadis (graduate student), Anastasios Gounaris (Associate Professor).