Self-supervised Learning for Refrigeration System Monitoring in Iiot
Year: 2026
Type: dissertation
Abstract: This thesis evaluates self-supervised, semi-supervised, supervised, and rule-based machine learning approaches for anomaly detection in low-frequency LoRaWAN refrigeration monitoring across 84 sensors.
Source: Purdue
Author: Lopez, Xavier Alexander
Institution: Purdue University System
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7160421932