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.

Natural waxes are functional ingredients in food, pharmaceutical, and cosmetic products, yet their crystallographic investigations remain superficial. This study characterized sunflower (SFX), candelilla (CLX), carnauba (CRX), rice bran (RBX), yellow beeswax (BYX), and white beeswax (BWX), each from two suppliers, focusing on crystal structure. Supplier differences were minor except in color. Scanning electron microscopy revealed platelet-like morphologies in all samples, with SFX and RBX showing the smallest particle sizes. X-ray diffraction distinguished highly ordered lamellar structures in SFX and RBX from less ordered layering in the other waxes. All waxes shared short spacings consistent with a perpendicular orthorhombic subcell, while beeswaxes indicated a parallel orthorhombic subcell. Crystallite anisotropy, quantified across samples, decreased in the order BYX > BWX > RBX > CRX > SFX > CLX. Melting and crystallization temperatures also varied by wax type. A schematic hierarchy of natural wax structures is proposed to guide future applications and research.