Comparative Study of Seamless Asset Location and Tracking Technologies

Abstract From manufacturers, suppliers, retailers, distributors to the consumers, all stakeholders are gearing up to use indoor asset tracking technologies to increase the visibility of goods and assets within their supply chain and their work environments. At its nascent stage, real-time asset tracking capabilities have been at the forefront of the connected production system and Industry 4.0. However, little is known regarding the scope, accuracy, reliability, and practical benefits of this emerging technology, which is hindering its widespread adoption. To better understand the tracking technologies, in this study, a generic asset tracking service framework for the indoor environment is presented. A comparative evaluation of the available approaches is also introduced using a Technology Enablers Evaluation Matrix, which tries to find out the suitability of asset tracking approaches for indoor location services. As pilot testing, we have evaluated the capabilities of the seamless location tracking capabilities developed by HERE Technologies and the Smart Manufacturing Demonstration Center (SMDC). Their asset tracking works indoor and outdoor seamlessly and uses GPS and Wi-Fi based methods as well as Bluetooth based tracking approaches. The testing evaluates seamless real-time asset tracking in the indoor environment and helps in finding a suitable tracking approach based on requirements.

[1]  David Wood,et al.  BlueBot: asset tracking via robotic location crawling , 2005, ICPS '05. Proceedings. International Conference on Pervasive Services, 2005..

[2]  Brian W. Anthony,et al.  Real-Time Imaging of Invisible Micron-Scale Monolayer Patterns on a Moving Web Using Condensation Figures , 2020, IEEE Transactions on Industrial Electronics.

[3]  Bernhard Mitschang,et al.  A mobile dashboard for analytics-based information provisioning on the shop floor , 2016, Int. J. Comput. Integr. Manuf..

[4]  Mario Gerla,et al.  Crowdsource Based Indoor Localization by Uncalibrated Heterogeneous Wi-Fi Devices , 2016, Mob. Inf. Syst..

[5]  Filip Maly,et al.  Improving Indoor Localization Using Bluetooth Low Energy Beacons , 2016, Mob. Inf. Syst..

[6]  Wen Yao,et al.  The Adoption and Implementation of RFID Technologies in Healthcare: A Literature Review , 2012, Journal of Medical Systems.

[7]  Fernando Las Heras Andres,et al.  A received signal strength RFID-based indoor location system , 2017 .

[8]  Ramón F. Brena,et al.  Evolution of Indoor Positioning Technologies: A Survey , 2017, J. Sensors.

[9]  Kai-Wei Chiang,et al.  An intelligent navigator for seamless INS/GPS integrated land vehicle navigation applications , 2008, Appl. Soft Comput..

[10]  Antonio Pietrabissa,et al.  Optimal planning of sensor networks for asset tracking in hospital environments , 2013, Decis. Support Syst..

[11]  Xinwei Wang,et al.  Dynamic localization based on spatial reasoning with RSSI in wireless sensor networks for transport logistics , 2011 .

[12]  Thomas R. Kurfess,et al.  Indoor location service in support of a smart manufacturing facility , 2018, Comput. Ind..

[13]  Ingrid Moerman,et al.  Performance analysis of multiple Indoor Positioning Systems in a healthcare environment , 2016, International Journal of Health Geographics.