Indicator-based Potential Analysis for Asset Tracking Applications

Abstract

The increasing adoption of advanced technologies such as wireless sensor networks and real-time location systems has significantly impacted asset tracking applications in industry and logistics. These technologies enhance the tracking and monitoring of assets, offering a new paradigm in factory automation by replacing traditional methods like labels and barcodes. Despite the clear benefits, the diverse range of technological solutions available necessitates expert knowledge to identify optimal systems for specific applications. However, the scarcity and commercial biases of such experts present challenges. This article aims to support companies in the decision-making process by presenting an indicator-based potential analysis methodology tailored for asset tracking applications. The methodology was developed through a comprehensive literature review and expert validation via a delphy study. The study identified and refined a set of indicators to accurately describe and compare asset tracking use cases. The results demonstrate a high level of agreement among experts regarding the relevance and attributes of the indicators. The validated indicators enable the quantification of the potential of various asset tracking applications, providing a structured approach to determine sub-potentials and overall application potential.