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Microsystems at Bremen University Walter Lang MCB: Microsystems Center Bremen. MCB Microsystems Center Bremen Walter Lang Wolfgang Benecke Rainer Laur IMSAS Institut für Mikrosensoren, -aktoren und -systeme. Microsystems Center Bremen. Spin Off Companies. 16 Membranes. Size:
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Microsystems at Bremen University Walter Lang MCB: Microsystems Center Bremen
MCB Microsystems Center Bremen Walter Lang Wolfgang Benecke Rainer Laur IMSAS Institut für Mikrosensoren, -aktoren und -systeme
Microsystems Center Bremen Spin Off Companies
16 Membranes Size: 0.4 mm x 0,7 mm Microsystems Center Bremen Pressure Sensors
Microsystems Center Bremen Thermal Flow Sensor Thermal flow sensors
Microsystems Center Bremen Gasanalysis Miniaturized Gas Chromatographic System BTX in 10ppb concentration (Sick building syndrom) Ethylene (Fruit logistics)
Microsystems Center Bremen Gasanalysis Chromatographic Column
Microsystems Center Bremen Autonomous Sensor Networks for Logistics – the Intelligent Container
RFID for food products Fright: Bananas Temperature: 16.5 °C Quality Index: 80% • Beyond Traceability • Additional Information • Combination with sensors • Temperature logging • Automated quality monitoring • Pro-active self-supervising goods ? Sell the fruits on the left side first!
Meet compartment • Average of reefer side ~2 °C colder than other side • Single loggers behave 'chaotic' • Replacing one sensor by averaging its neighbors not possible
Example of the intelligent container Local Pre- Processing RFID Reader Freight Object (RFID) Sensor Nodes External Commu-nication
Solutions for the communication bottleneck • Transmission of multiple full sensor protocols at unloading can’t be handled by passive RFID On-Chip processing of sensor data Intelligent RFID / sensor label Split between identification and measurement task Shelf life model to assess effects of temperature Only state flag transmitted at read out Standard identification tag at item level Active sensor nodes for permanent access
What’s the future: Automated shelf life evaluation • Shelf life: number of remaining days until a threshold is passed (colour, firmness, con-sumer acceptance) • Prediction for dynamic temper-ature conditions • Software opti-mization for low-power micro-controllers
Application of Shelf-Life-Model for recorded Data Pattern repeated for test of long term effects Temperature course of warmest and coldest box Difference in shelf life after 2 days of transport
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