The "Intelligent Container" - A Cognitive Sensor Network for Transport Management
by , , , , ,
Abstract:
The “Intelligent Container” is a sensor network used for the management of logistic processes, especially for perishable goods such as fruit and vegetables. The system measures relevant parameters such as temperature and humidity. The concept of “cognitive systems” provides an adequate description of the complex supervision tasks and sensor data handling. The cognitive system can make use of several algorithms in order to estimate temperature related quality losses, detect malfunctioning sensors, and to control the sensor density and measurement intervals. Based on sensor data, knowledge about the goods, their history and the context, decentralized decision making is realized by decision support tools. The amount of communication between the container and the headquarters of the logistic company is reduced, while at the same time the quality of the process control is enhanced. The system is also capable of self-evaluation using plausibility checking of the sensor data.
Reference:
The "Intelligent Container" - A Cognitive Sensor Network for Transport Management (Walter Lang, Reiner Jedermann, Damian Mrugala, Amir Jabbari, Bernd Krieg-Brückner, Kerstin Schill), In IEEE Sensors J., Institute of Electrical & Electronics Engineers (IEEE), volume 11, 2011.
Bibtex Entry:
@Article{Lang2011,
  author    = {Walter Lang and Reiner Jedermann and Damian Mrugala and Amir Jabbari and Bernd Krieg-Brückner and Kerstin Schill},
  title     = {The "Intelligent Container" - A Cognitive Sensor Network for Transport Management},
  journal   = {{IEEE} Sensors J.},
  year      = {2011},
  volume    = {11},
  number    = {3},
  pages     = {688--698},
  month     = {mar},
  abstract  = {The “Intelligent Container” is a sensor network used for the management of logistic processes, especially for perishable goods such as fruit and vegetables. The system measures relevant parameters such as temperature and humidity. The concept of “cognitive systems” provides an adequate description of the complex supervision tasks and sensor data handling. The cognitive system can make use of several algorithms in order to estimate temperature related quality losses, detect malfunctioning sensors, and to control the sensor density and measurement intervals. Based on sensor data, knowledge about the goods, their history and the context, decentralized decision making is realized by decision support tools. The amount of communication between the container and the headquarters of the logistic company is reduced, while at the same time the quality of the process control is enhanced. The system is also capable of self-evaluation using plausibility checking of the sensor data.},
  doi       = {10.1109/JSEN.2010.2060480},
  publisher = {Institute of Electrical {\&} Electronics Engineers ({IEEE})},
  url       = {10.1109/JSEN.2010.2060480">http://dx.doi.org/10.1109/JSEN.2010.2060480},
}