Two conference presentations in February 2017
Frutic, Berlin and SCC, Hamburg
Somehow, conferences always come in pairs. In the second week of February 2017 you can join two conferences with contributions from the intelligent container project:
FRUTIC Symposium 2017: Quality and safety of Fresh Horticultural Commodities
Berlin, Germany, February, 7-9 2017, www.frutic.atb-potsdam.de
Challenges and opportunities in remote monitoring of perishable products -
Lessons learned from the intelligent container
Reiner Jedermann, Ulrike Praeger, Walter Lang
Temperature deviations during transport and storage still cause a significant amount of food loss. A large portion of this loss could be avoided if information regarding deviating transport conditions and resulting changes in remaining shelf life of the product would be available in real-time. In this study, we detail a prototype of such an intelligent container. The technical system, and results from tests in trans-ocean transportation of bananas are presented. The system is also able to predict hot-spots, which were identified as the most crucial risk for product loss.
Although several technical solutions for remote container monitoring (RCM) and wireless temperature data logging are available on the market, a wide application of the concept of real-time shelf life monitoring is still lacking. Challenges that still have to be met are mostly related to problems which result from the splitting of the cold chain into multiple actors, and different manufacturers and target customer groups for RMC and for wireless sensor systems.
11th International ITG Conference on Systems, Communication and Coding
February 6-9, 2017, Hamburg Germany, www.scc2017.net
In-network Processing by the Example of Maxima Estimation in Spatial Fields
Reiner Jedermann, Henning Paul, Walter Lang
Wireless sensor networks are often used to observe the spatial distribution of a physical quantity. By summarizing the observations of hundred or more nodes in a small set of parameters, the amount of data that has to be transmitted from the network to an external observer can be reduced. In this article we show by the example of an algorithm for estimation of local field maxima, that it is also possible to reduce the data exchange within the network by in-network processing. Each sensor node requires information only from its 15 closest neighbors, thus reducing communication by more than 50% compared with central data processing by the gateway between network and external observer. The algorithm is well suited for distributed implementation. The accuracy of the estimation was evaluated for different measurement noise powers, numbers of sensors, and sensor placement schemes.