Assessing the dynamic behavior of wsn motes and rfid semi-passive tags for temperature monitoring.

Abstract Wireless Sensor Networks (WSN) and Radio Frequency Identification (RFID) are two wireless technologies that are being used for cold chain monitoring and tracking. Several applications in this field have been reported in the last few years. However, there are no studies about the the dynamic behavior of this hardware and how this affects the measurements. Therefore the purpose of this study is to evaluate the dynamic behavior of the sensors. A series of trials were designed and performed, covering temperature steps between cold chamber (5 °C), room temperature (23 °C) and heated environment (35 °C). Three WSN motes, with different sensor configurations, and four RFID tags (with and without housing), were compared. In order to assess the dynamic behavior two alternative methods have been applied for adjusting experimental data to a first order dynamic response that allows extracting the time response (τ) and corresponding determination coefficient (r2). The shortest response time (10.4 s) is found for one of the RFID semi-passive tags. Its encapsulated version provides a significantly higher response (60.0 s), both times are obtained with the same method. The longest τ corresponds to one of the sensors embedded in a WSN mote (308.2 s). We found that the dynamic response of temperature sensors within wireless and RFID nodes is dramatically influenced by the way they are housed (to protect them from the environment); its characterization is basically to allow monitoring of high rate temperature changes and to certify the cold chain.

[1]  D J Tanner,et al.  Modelling product quality changes as a result of temperature variability in shipping systems. , 2003 .

[2]  E. Abad,et al.  RFID smart tag for traceability and cold chain monitoring of foods: Demonstration in an intercontinental fresh fish logistic chain , 2009 .

[3]  Pilar Barreiro,et al.  Performance of ZigBee-Based wireless sensor nodes for real-time monitoring of fruit logistics , 2008 .

[4]  Walter Lang,et al.  Testing network protocols and signal attenuation in packed food transports , 2011, Int. J. Sens. Networks.

[5]  Walter Lang,et al.  Spatial temperature profiling by semi-passive RFID loggers for perishable food transportation , 2009 .

[6]  Roberto Montanari,et al.  Cold chain tracking: a managerial perspective , 2008 .

[7]  M. Bogataj,et al.  Stability of perishable goods in cold logistic chains , 2005 .

[8]  Mojca Jevšnik,et al.  Cold chain maintaining in food trade , 2006 .

[9]  Maohua Wang,et al.  Wireless sensors in agriculture and food industry — Recent development and future perspective , 2005 .

[10]  V. Alchanatis,et al.  Review: Sensing technologies for precision specialty crop production , 2010 .

[11]  L. Ruiz-Garcia,et al.  The role of RFID in agriculture: Applications, limitations and challenges , 2011 .

[12]  Pilar Barreiro,et al.  A Review of Wireless Sensor Technologies and Applications in Agriculture and Food Industry: State of the Art and Current Trends , 2009, Sensors.

[13]  Li-Rong Zheng,et al.  Scenario-Based Design of Wireless Sensor System for Food Chain Visibility and Safety , 2011 .

[14]  Jean-Pierre Emond,et al.  Application of RFID technologies in the temperature mapping of the pineapple supply chain , 2008 .

[15]  Pilar Barreiro,et al.  Testing ZigBee Motes for Monitoring Refrigerated Vegetable Transportation under Real Conditions , 2010, Sensors.

[16]  Ning Wang,et al.  Review: Wireless sensors in agriculture and food industry-Recent development and future perspective , 2006 .

[17]  D. Diamond,et al.  Simultaneous Web-based real-time temperature monitoring using multiple wireless sensor networks , 2005, IEEE Sensors, 2005..