The application discloses an agricultural process
big data statistical analysis and alarm method, collects meteorological, soil,
insect,
irrigation state and equipment working condition data in agricultural production, carries out cleaning,
time alignment and unified modeling on multi-
source data, forms a monitoring sequence, carries out
standardization and rank
statistical processing on the monitoring sequence, identifies candidate abnormal points, further combines local significance test and
interval distribution change test, confirms abnormal intervals, and then comprehensively scores
mutation strength, significance strength and distribution change strength, generates early warning grades, early warning time and related index information, and outputs alarm results. The application realizes
statistical analysis and graded early warning of abnormal changes in agricultural processes.