Artificial intelligence for monitoring and remediating radioactive contamination in agriculture

Gerd, D.*; Albinet, F.*; 斎藤 公明  ; 武宮 博; 町田 昌彦  ; 江口 哲也*; Smolders, E.*; Blackburn, C.*; Heng, L.*

Gerd, D.*; Albinet, F.*; Saito, Kimiaki; Takemiya, Hiroshi; Machida, Masahiko; Eguchi, Tetsuya*; Smolders, E.*; Blackburn, C.*; Heng, L.*

Under the situation of a major nuclear accident with adverse consequences for food production and agricultural systems, due to an uncontrolled release of large amounts of radionuclides, remediation of farmland requires accurate environmental data. Area-wide radiation mapping and soil information are such data which play a major role. Radiation mapping help prioritize where and how to remediate, and soil information assist in selecting the optimal agricultural measures. Through the international research network under the IAEA funded Coordinated Research Project D1.50.19 on "Remediation of Radioactive Contaminated Agricultural Land", the Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture investigated how artificial intelligence tools can be used to assist decisions makers in their efforts to provide such information. This presentation will provide three examples.