Skip to main content

Advertisement

SpringerLink
Log in

Value-centric design of the internet-of-things solution for food supply chain: Value creation, sensor portfolio and information fusion

  • Published:
Information Systems Frontiers Aims and scope Submit manuscript

Abstract

The revolution of Internet-of-Things (IoT) is reshaping the modern food supply chains with promising business prospects. To be successful in practice, the IoT solutions should create “income-centric” values beyond the conventional “traceability-centric” values. To accomplish what we promised to users, sensor portfolios and information fusion must correspond to the new requirements introduced by this income-centric value creation. In this paper, we propose a value-centric business-technology joint design framework. Based on it the income-centric added-values including shelf life prediction, sales premium, precision agriculture, and reduction of assurance cost are identified and assessed. Then corresponding sensor portfolios are developed and implemented. Three-tier information fusion architecture is proposed as well as examples about acceleration data processing, self-learning shelf life prediction and real-time supply chain re-planning. The feasibilities of the proposed design framework and solution have been confirmed by the field trials and an implemented prototype system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

References

  • Abad, E., Palacio, F., Nuin, M., González de Zárate, A., Juarros, A., Gómez, J. M., & Marco, S. (2009). RFID smart tag for traceability and cold chain monitoring of foods: Demonstration in an intercontinental fresh fish logistic chain. Journal of Food Engineering, 93(4), 394–399.

  • Anastasi, G., Farruggia, O., Re, L. G., & Ortolani M. (2009). Monitoring high-quality wine production using wireless sensor networks. In Proceedings of the 42nd Hawaii international conference on system sciences, doi: 10.1109/HICSS.2009.313

  • Angeles, R. (2010). Moderated regression: Effects of IT infrastructure integration and supply chain process integration on the relationships between RFID adoption attributes and system deployment outcomes. In J. E. Quintela Varajão et al. (Eds.), CENTERIS 2010, Part II, CCIS 110, (pp. 406–415), 2010. Springer-Verlag: Berlin Heidelberg.

  • Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: a survey. Computer Networks, 54(15), 2787–2805.

    Article  Google Scholar 

  • Boddie, W., & Kun, L. (2008). Health care, public health, and the food and agriculture critical infrastructures. IEEE Engineering in Medicine and Biology Magazine, 27(6), 54–58.

    Article  Google Scholar 

  • Carullo, A., Corbellini, S., Parvis, M., & Vallan, A. (2009). A wireless sensor network for cold-chain monitoring. IEEE Transactions on Instrumentation and Measurement, 58(5), 1405–1411.

    Article  Google Scholar 

  • Chang, R. (1981). Physical chemistry with applications to biological systems (2nd ed.). New York: Macmillan Publishing Co, Inc.

    Google Scholar 

  • Choe, Y. C., Park, J., Chung, M., & Moon, J. (2009). Effect of the food traceability system for building trust: price premium and buying behavior. Information System Frontiers, 11, 167–179.

    Article  Google Scholar 

  • Claire, S. (2011). Hartford encourages its food-industry clients to deploy RFID temperature tags. RFID Journal. Aug. 10, 2011.

  • Crisosto, C. H., Mitcham, B., & Cantwell, M. (2008). Optimum temperature conditions for producehandlers. In Central Valley Postharvest Newsletter of University of California, 17(3), 1–18.

  • Dalgaard, P. (1995). Modelling of microbial activity and prediction of shelf life for packed fresh fish. International Journal of Food Microbiology, 26(3), 305–317.

    Article  Google Scholar 

  • Dalgaard, P., Buch, P., & Silberg, S. (2002). Seafood spoilage predictor—development and distribution of a product specific application software. International Journal of Food Microbiology, 73(2–3), 343–349.

    Article  Google Scholar 

  • Duan, L., & Xu, L. (2012). Business intelligence for enterprise systems: a survey. IEEE Transactions on Industrial Informatics, published online, doi: 10.1109/TII.2012.2188804

  • European Commission Information Society (2008). Internet of things in 2020: a roadmap for the future. In reports of DG INFSO and EPoSS—05 September 2008.

  • European Commission Information Society (2009). Internet of things strategic research roadmap 2009. In reports of CERP-IoT cluster—15 September 2009.

  • EU (2002). Regulation (EC) No 178/2002 of the European parliament and of the council. Official Journal of the European Communities. 1.2.2002, L31/1–24.

  • Fellows, P. (2000). Food processing technology: Principles and practice (2nd ed.). Cambridge: Woodhead Publishing Limited.

    Book  Google Scholar 

  • German Insurance Association (2002–2011). Container Handbook. Marine and loss prevention department of GDV, www.containerhandbuch.de. Accessed Apr 23, 2012.

  • Goff-Pronost, M. L., & Sicotte, C. (2010). The added value of thorough economic evaluation of telemedicine networks. The European Journal of Health Economics, 11(1), 45–55.

    Article  Google Scholar 

  • Hertog, M. L. A. T. M., Boerrigter, H. A. M., van den Boogaard, G. J. P. M., Tijskens, L. M. M., & van SchaikOpen, A. C. R. (1999). Predicting keeping quality of strawberries (cv. ‘Elsanta’) packed under modified atmospheres: an integrated model approach. Postharvest Biology and Technology, 15(1), 1–12.

    Article  Google Scholar 

  • Hong, I.-H., Dang, J., Tsai, Y., Liu, C., Lee, W., Wang, M., & Chen, P. (2011). An RFID application in the food supply chain: a case study of convenience stores in Taiwan. Journal of Food Engineering, 106(2), 119–126.

    Article  Google Scholar 

  • Hsu, Y., Chen, A., & Wang, C. (2008). A RFID-enabled traceability system for the supply chain of live fish. In Proceedings of IEEE International Conference on Automation and Logistics, (pp. 81–86), doi: 10.1109/ICAL.2008.4636124

  • Huang, H., Chen, C., & Chen, T. (2006). Mobile diagnosis based on RFID for food safety. In Proceedings of IEEE International Conference on Automation Science and Engineering (pp. 357–362), doi: 10.1109/COASE.2006.326908.

  • Hulstijn, J., Christiaanse, R., Bharos, N., Schmid, F., Wijk, R., et al. (2011). Continuous Control monitoring-based regulation: A case in the meat processing industry. In: C. Salinesi and O. Pastor (Eds.) CAiSE 2011 workshops, LNBIP 83, (pp. 238–248). Berlin Heidelberg: Springer-Verlag.

  • ITU (2005). The internet of things-executive summary. International Telecommunication Union (ITU) Internet Report. http://www.itu.int/osg/spu/publications/internetofthings. Accessed Apr 23, 2012.

  • Jedermann, R., Palafox-Albarran, J., Jabarri, A., Lang, W., et al. (2011). Embedded intelligent objects in food logistics technical limits of local decision making. In M. Hülsmann (Ed.), Autonomous cooperation and control in logistics. Berlin: Springer. doi:10.1007/978-3-642-19469-6_16.

    Google Scholar 

  • Jones, P. (2006). Networked RFID for use in the food chain. In Proceedings of IEEE Conference on Emerging Technologies and Factory Automation (pp. 1119–1124), doi: 10.1109/ETFA.2006.355252

  • José, á. M., Berrone, P., Husillos, F. J., & Lado, N. (2007). Reverse logistics, stakeholders’ influence, organizational slack, and managers’ posture. Journal of Business Research, 60(5), 463–473.

    Article  Google Scholar 

  • Kim, Y., Evans, R. G., & Iversen, W. M. (2008). Remote sensing and control of an irrigation system using a distributed wireless sensor network. IEEE Transactions on Instrumentation and Measurement, 57(7), 1379–1387.

    Article  Google Scholar 

  • Kuck, M. (2007). The chill-on project: Novel technologies for a safe and transparent food supply. http://www.chill-on.com. Accessed Apr 23, 2012.

  • Lao, G., & Wang, Qi. (2008). A circulation management model for safer food supply based on RFID. In Proceedings of 4th International Conference on Wireless Communications, Networking and Mobile Computing (pp. 1–4).

  • Lao, S. I., Choy, K. L., Ho, G. T. S., Tsim, Y. C., Poon, T. C., & Cheng, C. K. (2012). A real-time food safety management system for receiving operations in distribution centers. Expert Systems with Applications, 39(3), 2532–2548.

    Article  Google Scholar 

  • Lea-Cox, J. D., Kantor, G., Anhalt, J., Ristvey, A., & Ross, D. S. A. (2007). Wireless sensor network for the nursery and greenhouse industry. In Proceedings of in southern nursery association research conference, Vol. 52.

  • Lee, W. S., Alchanatis, V., Yang, C., Hirafuji, M., Moshou, D., & Li, C. (2010). Sensing technologies for precision specialty crop production. Computers and Electronics in Agriculture, 74(1), 2–33.

    Article  Google Scholar 

  • Li, L. (2007). Supply chain management: Concepts, techniques, and practices—enhancing value through collaboration. World Scientific Publishing.

  • Li, L. (2011). Assessing the relational benefits of logistics services perceived by manufacturers in supply chain. International Journal of Production Economics, 132, 58–67.

    Article  Google Scholar 

  • Li, L., & Warfield, J. (2011). Guest editorial: perspectives on quality coordination and assurance in global supply chains. International Journal of Production Research, 49(1), 1–4.

    Article  Google Scholar 

  • Li, S., Xu, L., Wang, X., & Wang, J. (2012). Integration of hybrid wireless networks in cloud services oriented enterprise information systems. Enterprise Information Systems, 6(2), 165–187.

    Article  Google Scholar 

  • Liu, R., & Kumar, A. (2011). Leveraging information sharing to configure supply chains. Information System Front, 13, 139–151.

    Article  Google Scholar 

  • López, T. S., Ranasinghe, D. C., Patkai, B., & McFarlane, D. (2011). Taxonomy, technology and applications of smart objects. Information Systems Frontiers, 13(2), 281–300.

    Article  Google Scholar 

  • Man, C. M. D., & Jones, A. A. (2000). Shelf-life evaluation of foods (2nd ed.). New York: Aspen.

    Google Scholar 

  • Martinez-Romero, D., Serrano, M., Carbonell, A., Castillo, S., Riquelme, F., & Valero, D. (2004). Mechanical damage during fruit post-harvest handling: Technical and physiological implications. In R. Dris & S. M. Jain (Eds.), Production practices and quality assessment of food crops, vol. 3, “Quality handling and evaluation” (pp. 233–252). Netherlands: Kluwer.

    Chapter  Google Scholar 

  • Martínez-Sala, A. S., Egea-López, E., Garcia-Sanchez, F., & García-Haro, J. (2009). Tracking of Returnable Packaging and Transport Units with active RFID in the grocery supply chain. Computers in Industry, 60(3), 161–171.

    Google Scholar 

  • McWilliams, G. (2006). Wal-Mart’s radio-tracked inventory hits static. Wall Street Journal. February 15, 2006, page B1.

  • Oms-Oliu, G., Martínez, R. R. M., Soliva-Fortuny, R., & Martín-Belloso, O. (2008). Effect of superatmospheric and low oxygen modified atmospheres on shelf-life extension of fresh-cut melon. Food Control, 19(2), 191–199.

    Article  Google Scholar 

  • Pang, Z., Chen, J., Sarmiento, M. D., Zhang, Z., Gao, J., Chen, Q., & Zheng, L. (2009). Mobile and wide area deployable sensor system for networked services. In Proceedings of IEEE sensors conference (pp. 1396–1399). doi: 10.1109/ICSENS.2009.5398428.

  • Pang, Z., Chen, J., Zhang, Z., Chen, Q., & Zheng, L. (2010). Global fresh food tracking service enabled by wide area wireless sensor network. In Proceedings of IEEE sensors applications symposium (SAS2010), (pp. 6–9), doi: 10.1109/SAS.2010.5439425.

  • Pang, Z., Chen, Q., & Zheng, L. (2012). Scenario-based design of wireless sensor system for food chain visibility and safety. Advances in Computer, Communication, Control and Automation. Lecture Notes in Electrical Engineering, 121, 541–548. doi:10.1007/978-3-642-25541-0_69.

    Article  Google Scholar 

  • Palazón, M. A., Pérez-Conesa, D., Abellán, P., Ros, G., Romero, F., & Vidal, M. L. (2009). Determination of shelf-life of homogenized apple-based beikost storage at different temperatures using Weibull hazard model. LWT- Food Science and Technology, 42(1), 319–326. doi:10.1016/j.lwt.2008.03.011.

    Article  Google Scholar 

  • Qi, L., Zhang, J., Xu, M., Fu, Z., Chen, W., & Zhang, X. (2011). Developing WSN-based traceability system for recirculation aquaculture. Mathematical and Computer Modeling, 53(11–12), 2162–2172.

    Article  Google Scholar 

  • Rong, A., Akkerman, R., & Grunow, M. (2011). An optimization approach for managing fresh food quality throughout the supply chain. International Journal of Production Economics, 131, 421–429.

    Article  Google Scholar 

  • Ruiz-Garcia, L., & Lunadei, L. (2011). The role of RFID in agriculture: applications, limitations and challenges. Computers and Electronics in Agriculture, 79(1), 42–50.

    Article  Google Scholar 

  • Ruiz-Garcia, L., Lunadei, L., Barreiro, P., & Robla, J. I. (2009). A review of wireless sensor technologies and applications in agriculture and food industry: state of the art and current trends. Sensor, 9(6), 4728–4750. doi:10.3390/s90604728.

    Article  Google Scholar 

  • Ruiz-Garcia, L., Steinberger, G., & Rothmund, M. (2010). A model and prototype implementation for tracking and tracing agricultural batch products along the food chain. Food Control, 21(2), 112–121.

    Article  Google Scholar 

  • Sallabi, F., Fadel, M., Hussein, A., Jaffar, A., & Khatib, H. E. (2011). Design and implementation of an electronic mobile poultry production documentation system. Computers and Electronics in Agriculture, 76(1), 28–37.

    Google Scholar 

  • Sarac, A., Absi, N., & Dauzère-Pérès, S. (2010). A literature review on the impact of RFID technologies on supply chain management. International Journal of Production Economics, 128(1), 77–95.

    Article  Google Scholar 

  • Sheng, Q., Zeadally, S., Luo, Z., Chung, J., & Maamar, Z. (2010). Ubiquitous RFID: where are we? Information Systems Frontiers, 12(5), 485–490.

    Article  Google Scholar 

  • Shin, T.-H., Chin, S., Yoonc, S.-W., & Kwonb, S.-W. (2011). A service-oriented integrated information framework for RFID/WSN-based intelligent construction supply chain management. Automation in Construction, 20(6), 706–715.

    Google Scholar 

  • Sinderen, M., & Almeida, J. P. A. (2011). Empowering enterprises through next-generation enterprise computing. Enterprise Information Systems, 5(1), 1–8.

    Article  Google Scholar 

  • Strauss, C., Stummer, C., Bauer, C., & Trieb, A. (2009). A networked ubiquitous computing environment for damage prevention: a decision support framework for the insurance sector. In Proceedings of International Conference on Parallel Processing Workshops (pp. 276–281), doi: 10.1109/ICPPW.2009.79.

  • Tajima, M. (2007). Strategic value of RFID in supply chain management. Journal of Purchasing & Supply Management, 13, 261–273.

    Article  Google Scholar 

  • Tijskens, L. M. M., & Polderdijk, J. J. (1996). A generic model for keeping quality of vegetable produce during storage and distribution. Agricultural Systems, 51(4), 431–452.

    Article  Google Scholar 

  • Tsironi, T., Gogou, E., Velliou, E., & Taoukis, P. S. (2008). Application and validation of the TTI based chill chain management system SMAS (Safety Monitoring and Assurance System) on shelf life optimization of vacuum packed chilled tuna. International Journal of Food Microbiology, 128(1), 108–115.

    Article  Google Scholar 

  • Tsironi, T., Stamatiou, A., Giannoglou, M., Velliou, E., & Taoukis, P. S. (2011). Predictive modelling and selection of time temperature integrators for monitoring the shelf life of modified atmosphere packed gilthead seabream fillets. LWT- Food Science and Technology, 44(4), 1156–1163. doi:10.1016/j.lwt.2010.10.016.

    Article  Google Scholar 

  • Ugazio, E., & Pigni, F. (2010). Measuring RFID benefits in the supply chain. In A. D’Atri & D. Saccà (Eds.), Information systems: People, organizations, institutions, and technologies, Part 8 (pp. 469–476). Berlin: Springer.

    Google Scholar 

  • Victoria de-la-Fuente, M., Ros, L. (2010). What to Do with Rejected Loads in the Agri-food Chain. In J.E. Quintela Varajão et al. (Eds.): CENTERIS 2010, Part I, CCIS 109, pp. 251–260, 2010. Berlin Heidelberg, Springer-Verlag.

  • Visich, J. K., Reyes, P. M., & Li, S. (2011). Is RFID dead? Definitely not! DC Velocity Technology Review. June 27, 2011.

  • Voisard, A., & Ziekow, H. (2010). Modeling trade-offs in the design of sensor-based event processing infrastructures. Information Systems Frontiers, 14(2), 317–330.

    Article  Google Scholar 

  • Wamba, S. F., & Chatfield, A. T. (2010). The impact of RFID technology on warehouse process innovation: a pilot project in the TPL industry. Information Systems Frontiers, 13(5), 693–706.

    Article  Google Scholar 

  • Xu, L. (2011a). Enterprise systems: state-of-the-art and future trends. IEEE Transactions on Industrial Informatics, 7(4), 630–640.

    Article  Google Scholar 

  • Xu, L. (2011b). Information architecture for supply chain quality management. International Journal of Production Research, 49(1), 183–198.

    Article  Google Scholar 

  • Yoo, S., Kim, J., Kim, T., Ahn, S., Sung, J., & Kim, D. (2007). A2S: automated agriculture system based on WSN. IEEE International Symposium on Consumer Electronics. doi:10.1109/ISCE.2007.4382216.

  • Zhang, M., & Li, P. (2012). RFID application strategy in agri-food supply chain based on safety and benefit analysis. Physics Procedia, 25, 636–642.

    Article  Google Scholar 

  • Zhang, W. (2010). Market Research for RFID Real-time Cold-chain Monitoring System. Master Thesis of Royal Institute of Technology, No.TRITA-ICT-EX-2010:296

Download references

Author information

Authors and Affiliations

  1. iPack Vinn Excellence Center, School of Information and Communication Technology, Royal Institute of Technology (KTH), Isafjordsgatan 39, 164 40, Kista-Stockholm, Sweden

    Zhibo Pang, Qiang Chen & Lirong Zheng

  2. Corporate Research, ABB AB, Forskargränd 7, 721 78, Västerås, Sweden

    Zhibo Pang

  3. Software School, Fudan University, No. 825, Zhangheng Road, Shanghai, Peoples’ Republic of China

    Weili Han

  4. School of Information Science and Technology, Fudan University, No. 220, Handan Road, Shanghai, Peoples’ Republic of China

    Lirong Zheng

Authors
  1. Zhibo Pang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qiang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weili Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lirong Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhibo Pang.

Appendices

Appendix A

Table 6 Comparison between this work and others
Full size table

Appendix B

Table 7 Some of existing shelf life prediction models and applications
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Pang, Z., Chen, Q., Han, W. et al. Value-centric design of the internet-of-things solution for food supply chain: Value creation, sensor portfolio and information fusion. Inf Syst Front 17, 289–319 (2015). https://doi.org/10.1007/s10796-012-9374-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10796-012-9374-9

Keywords

Search

Navigation