New publication in the Journal of Sensor and Actuator Networks [14.10.25]
Elia Henrichs from the Department of Food Informatics is author of the publication "Enabling Adaptive Food Monitoring Through Sampling Rate Adaptation for Efficient, Reliable Critical Event Detection" in the Journal of Sensor and Actuator Networks (Impact Factor 4.2).
The publication "Enabling Adaptive Food Monitoring Through Sampling Rate Adaptation for Efficient, Reliable Critical Event Detection" from Elia Henrichs (Department of Food Informatics, University of Hohenheim) with co-authors Dana Jox, Pia Schweizer and Christian Krupitzer (all Department of Food Informatics, University of Hohenheim) was published in MDPI Journal of Sensor and Actuator Networks (Impact Factor 4.2).
Monitoring systems are essential in many fields, such as food production, storage, and supply, to collect information about applications or their environments to enable decision-making. However, these systems generate massive amounts of data that require substantial processing. To improve data analysis efficiency and reduce data collectors’ energy demand, adaptive monitoring is a promising approach to reduce the gathered data while ensuring the monitoring of critical events. Adaptive monitoring is a system’s ability to adjust its monitoring activity during runtime in response to internal and external changes. This work investigates the application of adaptive monitoring—especially, the adaptation of the sensor sampling rate—in dynamic and unstable environments. This work evaluates 11 distinct approaches, based on threshold determination, statistical analysis techniques, and optimization methods, encompassing 33 customized implementations, regarding their data reduction extent and identification of critical events. Furthermore, analyses of Shannon’s entropy and the oscillation behavior allow for estimating the efficiency of the adaptation algorithms. The results demonstrate the applicability of adaptive monitoring in food storage environments, such as cold storage rooms and transportation containers, but also reveal differences in the approaches’ performance. Generally, some approaches achieve high observation accuracies while significantly reducing the data collected by adapting efficiently.
The publication is available at MDPI Journal of Sensor and Actuator Networks.
