CEIFA: A multi-level anomaly detector for smart farming

Climate change, the water crisis, and population growth add new challenges for food production. The modernization of agricultural methods is essential to increase production rates and preserve natural resources. Smart agriculture provides resources that can enhance farming tasks by efficiently controlling actuators, optimizing utility and resource use, managing production, maximizing profit, and minimizing costs. For these technologies to become popular, they must have a high level of reliability and safety. To improve the reliability in Smart Agriculture, this paper proposes CEIFA, a low-cost, hybrid anomaly detector capable of identifying failures, faults, errors and attacks that impact these systems. CEIFA operates on local or remote cloud servers, filtering data sent by agricultural system sensors. It can operate on resource-restricted devices and save financial resources related to computing costs. Real tests on a set of faults, failures, and errors point to an efficiency greater than 95% in anomaly detection.