Abstract
As a consequence of the growing globalization, transports which need a safe handling are increasing. Therefore, this paper introduces an innovative transport and condition monitoring system based on a mobile embedded sensor platform. The platform is equipped with a variety of sensors needed to extensively monitor a transport and can be attached directly to the transported good. The included microcontroller processes all relevant data served by the sensors in a very power efficient manner. Furthermore, it provides possible violations of previously given thresholds through a standardized Near Field Communication (NFC) interface to the user. Since falls are one major cause of damages while transportation, the presented system is the first one that not only detects every fall but also analyses the fall height and other parameters related to the fall event in real-time on the platform. The whole system was tested in different experiments where all critical situations and in particular all fall situations have been detected correctly.
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- 1.
In the case of the shock detection the method described in Sect. 4 for detecting only the start and end of a critical event is not used since shock events are by nature always very short.
References
Bundesverband Paket und Express Logistik e.V. (BIEK): KEP-Studie 2016: Analyse des Marktes in Deutschland. Study, Germany (2016)
Malinowski, M., Moskwa, M., Feldmeier, M., Laibowitz, M., Paradiso, J.A.: CargoNet: a low-cost micropower sensor node exploiting quasi-passive wakeup for adaptive asychronous monitoring of exceptional events. In: 5th ACM Conference on Embedded Networked Sensor Systems, pp. 145–159. ACM, New York (2007)
Instrumented Sensor Technology - Products. http://www.isthq.com/Products.aspx
Savi Technology - Container Security Tag ST-675. http://www.savi.com/wp-content/uploads/Hardware_Spec_Sheet_ST_6751.pdf
Fedex - Senseaware. http://www.senseaware.com/
Cambridge Consultants - Droptag. http://www.cambridgeconsultants.com/droptag
Pakkcheck. http://pakkcheck.com/
DHL - SmartSensor. http://www.dhl.com/smartsensor
ShockWatch - Impact Indicators. http://shockwatch.com/products/impact-and-tilt/impact-indicators
Lus̆trek, M., Gjoreski, H., Kozina, S., Cvetković, B., Mirchevska. V., Gams, M.: Detecting falls with location sensors and accelerometers. In: 23rd Innovative Applications of Artificial Intelligence Conference, pp. 1662–1667. AAAI Press, Menlo Park (2011)
Lan, M., Nahapetain, A., Vahdatpour, A., Au, L., Kaiser, W., Sarrafzadeh, M.: SmartFall: an automatic fall detection system based on subsequence matching for the SmartCane. In: 4th International Conference on Body Area Networks, pp. 8:1–8:8. ICST, Brussels (2009)
Bourke, A.K., O’Brien, J.V., Lyons, G.M.: Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. Gait Posture 26(2), 194–199 (2007)
Luan, J.E., Tee, T.Y., Pek, E., Lim, C.T., Zhong, Z.: Modal analysis and dynamic responses of board level drop test. In: 5th Electronics Packaging Technology Conference, pp. 233–243. IEEE Press, New York (2003)
Kionix: Free-fall sensing for drop-force modeling using Kionix MEMS tri-axis accelerometer (application note no. 001). Application Note (2016)
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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Pfeifer, M., Schubert, T., Becker, B. (2017). PackSens: A Condition and Transport Monitoring System Based on an Embedded Sensor Platform. In: Magno, M., Ferrero, F., Bilas, V. (eds) Sensor Systems and Software. S-CUBE 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 205. Springer, Cham. https://doi.org/10.1007/978-3-319-61563-9_7
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DOI: https://doi.org/10.1007/978-3-319-61563-9_7
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