Edge Computing pp 145-170 | Cite as

Application of Cloud Computing and Internet of Things to Improve Supply Chain Processes

  • S. Kanimozhi Suguna
  • Suresh Nanda Kumar
Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)


Cloud computing eliminates the advantage, which large organizations have conventionally enjoyed in terms of the availability of technology specialists and technical superiority. Small and medium enterprises that take advantage of infrastructure providers to support their technology requirements and provide specialized platforms for development and testing can build an infrastructure that is innovative and is capable of enabling entry into a global marketplace with as much capability as the market demands. Smaller enterprises have the ability to leverage software services that provide software such as supply chain management, enterprise resource planning, customer relationship management, and business analytics which are traditionally available only to large enterprises and organizations. Being able to access infrastructures, platforms, and software services based on what is needed and paying for only what is used enable and empower start-up enterprises and small and medium enterprises, giving them an advantage in the market and also an equal position with much larger enterprises.

IoT can be viewed as networks of networks. There can be a wide range of applications in IoT that supports logistics and supply chain management. IoT technology can be leveraged to achieve cost reductions. IoT technology can be combined with real-time location systems to get live updates from the factory floor, enabling manufacturers to continuously monitor machine activity, maintenance needs, and also product movement during production. Cost reduction can be achieved across the digital supply chain by making use of these smart machines by providing data that allow manufacturers to adjust production on the fly. Manufacturing and assembly lines will receive updated schedules and quality-related information in real time and instantly. IoT data can be leveraged to schedule proactive, preventive, predictive repairs, maintenance, customize production to meet the customer’s orders, and the focus that is needed to be successful in the digital world. The concept of Industry 4.0 aims at achieving smart factory will soon be a reality. Smart products which consist of the embedded knowledge of their customers’ needs will provide data insights and analytics about the best way to achieve customer fulfillment. All this information will lead to more cost-efficient production and product development.

Digitally enabled real-time collaboration partners will need to collaborate across all nodes of the supply chain to profitably meet the customers’ demands. Select technology solutions so that the supply chain partners can work within and across various networks and at touch points. Supply chain management (SCM) manages to optimize processes and collaboration with other companies in the supply chain (suppliers and customers) to create more value. While SCM is already heavily supported by various IT solutions, the Internet of Things (IoT) can be of great value by providing additional information. One of the major challenges in SCM is reducing the bullwhip effect. A major cause of the bullwhip effect is information distortion. For a better information flow, the IoT is able to trigger all relevant actors in the supply chain upon the sale of a product. In traditional processes, information on demand was only passed to one’s direct downstream partner instead of sharing this information with the whole chain. IoT can enable sharing of information across the entire supply chain from the upstream suppliers to the downstream customers.


Supply chain management Internet of Things SCM collaboration Information collection Predictive maintenance Manufacturing Industry 4.0 Smart products RTLS 


  1. 1.
    E. Ahmed, I. Yaqoob, A. Gani, M. Imran, M. Guizani, Internet-of-things-based smart environments: state of the art, taxonomy, and open research challenges. IEEE Wirel. Commun. 23(5), 10–16 (2016)CrossRefGoogle Scholar
  2. 2.
    J.S. Arlbjørn, H. de Haas, K.B. Munksgaard, Exploring supply chain innovation. Logist. Res. 3(1), 3–18 (2011)CrossRefGoogle Scholar
  3. 3.
    V. Arora, V. Ravi, Data mining using advanced ant colony optimization algorithm and application to bankruptcy prediction. Int. J. Inf. Syst. Soc. Chang. 4(3), 33–56 (2013)CrossRefGoogle Scholar
  4. 4.
    L. Atzori, A. Iera, G. Morabito, The internet of things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)CrossRefGoogle Scholar
  5. 5.
    D. Bandyopadhyay, J. Sen, Internet of things: applications and challenges in technology and standardization. Wirel. Pers. Commun. 58(1), 49–69 (2011)CrossRefGoogle Scholar
  6. 6.
    M. Bensaou, Inter-organizational cooperation and the use of IT: an empirical comparison of U.S. and Japanese supplier relations. Inf. Syst. Res. 8(2), 107–124 (1997)CrossRefGoogle Scholar
  7. 7.
    Z. Bi, L.D. Xu, C. Wang, Internet of things for enterprise systems of modern manufacturing. IEEE Trans. Ind. Inf. 10(2), 1537–1546 (2014)CrossRefGoogle Scholar
  8. 8.
    S. Bin, L. Yuan, W. Xiaoyi, Research on Data Mining Models for the Internet of Things, in Proc. International Conference on Image Analysis and Signal Processing, (Xiamen, 2010), pp. 127–132Google Scholar
  9. 9.
    D. Boos, H. Guenter, G. Grote, K. Kinder, Controllable accountabilities: the internet of things and its challenges for organizations. Behav. Inform. Technol. 32(5), 449–467 (2013)CrossRefGoogle Scholar
  10. 10.
    R. Bose, Competitive intelligence process and tools for intelligence analysis. Ind. Manag. Data Syst. 108(4), 510–528 (2008)CrossRefGoogle Scholar
  11. 11.
    K. Butner, The smarter supply chain of the future. Strateg. Leadersh. 38(1), 22–31 (2010)CrossRefGoogle Scholar
  12. 12.
    S. Chapman, P. Carter, Supplier/customer inventory relationships under just-in-time. Decis. Sci. 21(1), 35–51 (1990)CrossRefGoogle Scholar
  13. 13.
    M. Chen, S. Mao, Y. Liu, Big data: a survey. Mobile Netw. Appl. 19(2), 171–209 (2014)CrossRefGoogle Scholar
  14. 14.
    H. Chesbrough, A.K. Crowther, Beyond high tech: early adopters of open innovation in other industries. R D Manag. 36(3), 229–236 (2006)CrossRefGoogle Scholar
  15. 15.
    S. Devaraj, R. Kohli, Information technology payoff in the health-care industry: a longitudinal study. J. Manag. Inf. Syst. 16(4), 41–67 (2000)CrossRefGoogle Scholar
  16. 16.
    N. Economides, E. Katsamakas, Two-sided competition of proprietary vs. open source technology platforms and the implications for the software industry. Manag. Sci. 52(7), 1057–1071 (2006)CrossRefGoogle Scholar
  17. 17.
    European Union, Digital agenda for Europe: monitoring and control (2015). Retrieved from
  18. 18.
    M.U. Farooq, M. Waseem, A. Khairi, S. Mazhar, A critical analysis on the security concerns of internet of things (IoT). Int. J. Comput. Appl. 111(7), 1–5 (2015)Google Scholar
  19. 19.
    D. Fisher, R. DeLine, M. Czerwinski, S. Drucker, Interactions with big data analytics. Interaction 19(3), 50–59 (2012)CrossRefGoogle Scholar
  20. 20.
    R.K. Ganti, F. Ye, H. Lei, Mobile Crowdsensing: current state and future challenges. IEEE Commun. Mag. 49(11), 32–39 (2011)CrossRefGoogle Scholar
  21. 21.
    Gartner Press Release, Gartner’s 2014 Hype Cycle for emerging technologies maps the journey to digital business. 2015 (2014)Google Scholar
  22. 22.
    G.L. Geerts, D.E. OLeary, A supply chain of things: the EAGLET ontology for highly visible supply chains. Decis. Support. Syst. 63(1), 3–22 (2014)CrossRefGoogle Scholar
  23. 23.
    M. Grunow, S. Piramuthu, RFID in highly perishable food supply chains – remaining shelf life to supplant expiry date? Int. J. Prod. Econ. 146(2), 717–727 (2013)CrossRefGoogle Scholar
  24. 24.
    J. Gubbi, R. Buyya, S. Marusic, M. Palaniswami, Internet of things (IoT): a vision, architectural elements, and future directions. Futur. Gener. Comput. Syst. 29(7), 1645–1660 (2013)CrossRefGoogle Scholar
  25. 25.
    T. Guimaraes, D. Cook, N. Natarajan, Exploring the importance of business clock-speed as a moderator for determinants of supplier network performance. Decis. Sci. 33(4), 629–644 (2002)CrossRefGoogle Scholar
  26. 26.
    O.K. Ha, Y.S. Song, K.Y. Chung, K.D. Lee, D. Park, Relation model describing the effects of introducing RFID in the supply chain: evidence from the food and beverage industry in South Korea. Pers. Ubiquit. Comput. 18(3), 553–561 (2014)CrossRefGoogle Scholar
  27. 27.
    T.S. Harrington, J.S. Srai, Designing a ‘concept of operations’ architecture for next-generation multi-organisational service networks. AI & Soc., (2016) Published online May 17
  28. 28.
    HP, HP study reveals 70 percent of internet of things devices vulnerable to attack. 2015 (2014)Google Scholar
  29. 29.
    C.-F. Hsueh, M.-S. Chang, A model for intelligent transportation of perishable products. Int. J. Intell. Transp. Syst. Res. 8(1), 36–41 (2010)Google Scholar
  30. 30.
    IBM, The Smarter supply chain of the future (2010). Retrieved January 21, 2015, from
  31. 31.
    IDC, Worldwide and regional internet of things (IoT) 2014–2020 forecast: a virtuous circle of proven value and demand. 2015 (2014)Google Scholar
  32. 32.
    Q. Jing, A.V. Vasilakos, J. Wan, J. Lu, D. Qiu, Security of the internet of things: perspectives and challenges. Wirel. Netw 20(8), 2481–2501 (2014)CrossRefGoogle Scholar
  33. 33.
    A. Karkouch, H. Mousannif, H. Al Moatassime, T. Noel, Data quality in internet of things: a state-of-the-art survey. J. Netw. Comput. Appl. 73, 57–81 (2016)CrossRefGoogle Scholar
  34. 34.
    R. Khan, S.U. Khan, R. Zaheer, S. Khan, Future Internet: The Internet of Things Architecture, Possible Applications and Key Challenges, in 2012 10th International Conference on Frontiers of Information Technology (FIT): Proceedings, (Institute of Electrical and Electronics Engineers Inc, Islamabad, 2012), pp. 257–260Google Scholar
  35. 35.
    D.H. Kim, J.Y. Cho, S. Kim, J. Lim, A study of developing security requirements for internet of things (IoT). Adv. Sci. Tech. 87, 94–99 (2015). Art, culture, game, graphics, broadcasting and digital contentsGoogle Scholar
  36. 36.
    Kimberly-Clark, Kimberly-Clark connecting with startup innovation at CES 2015 (2014)Google Scholar
  37. 37.
    D.R. Krause, R.B. Handfield, B.B. Tyler, The relationships between supplier development, commitment, social capital accumulation and performance improvement. J. Oper. Manag. 25(2), 528–545 (2007)CrossRefGoogle Scholar
  38. 38.
    A. Kumar, F. Niu, C. Ré, Hazy: making it easier to build and maintain big-data analytics. Commun. ACM 56(3), 40–49 (2013)CrossRefGoogle Scholar
  39. 39.
    M.T. Lazarescu, Design of a WSN platform for long-term environmental monitoring for IoT applications. IEEE J. Emerging Sel. Top. Circuits Syst. 3(1), 45–54 (2013)CrossRefGoogle Scholar
  40. 40.
    I. Lee, The internet of things (IoT) for supply chain innovation: a conceptual framework and analysis of fortune 200 companies. Asia Pac. J. Innov. Entrep. 9(1), 81–103 (2015)Google Scholar
  41. 41.
    I. Lee, K. Lee, The internet of things (IoT): applications, investments, and challenges for enterprises. Bus. Horiz. 58(4), 431–440 (2015)CrossRefGoogle Scholar
  42. 42.
    J. Lee, Y. Kim, Effect of partnership quality on IS outsourcing success: conceptual framework and empirical validation. J. Manag. Inf. Syst. 15(4), 29–61 (1999)CrossRefGoogle Scholar
  43. 43.
    F. Al-Turjman, S. Alturjman, Context-sensitive access in industrial internet of things (IIoT) healthcare applications. IEEE Trans Ind Inf 14(6), 2736–2744 (2018)CrossRefGoogle Scholar
  44. 44.
    L. Mainetti, L. Patrono, A. Vilei, Evolution of wireless sensor networks towards the internet of things: a survey. 2011 19th international conference on Software, Telecommunications and Computer Networks (SoftCOM), 1–6 (2011)Google Scholar
  45. 45.
    J. Mariani, E. Quasney, M.E. Raynor, Forging links into loops: the internet of things’ potential to recast supply chain management. Deloitte Review, 17 (2015)Google Scholar
  46. 46.
    H. Mendelson, R. Pillai, Clockspeed and information response: evidence from the information technology sector. Inf. Syst. Res. 9(4), 415–433 (1998)CrossRefGoogle Scholar
  47. 47.
    J.T. Mentzer, S. Min, Z.G. Zacharia, The nature of interfirm partnering in supply chain management. J. Retail. 76(4), 549–568 (2000)CrossRefGoogle Scholar
  48. 48.
    R.E. Miles, C.C. Snow, Organization theory and supply chain management: an evolving research perspective. J. Oper. Manag. 25(2), 459–463 (2007)CrossRefGoogle Scholar
  49. 49.
    J. Mineraud, O. Mazhelis, X. Su, S. Tarkoma, A gap analysis of internet-of-things platforms. Comput. Commun. 89-90, 5–16 (2016)CrossRefGoogle Scholar
  50. 50.
    F. Al-Turjman, S. Alturjman, 5G/IoT-enabled UAVs for multimedia delivery in industry-oriented applications. Multimed Tools Appl J (2018). s11042-018-6288-7
  51. 51.
    R. Patnayakuni, A. Rai, N. Seth, Relational antecedents of information flow integration for supply chain coordination. J. Manag. Inf. Syst. 23(1), 13–49 (2006). CrossRefGoogle Scholar
  52. 52.
    K.J. Petersen, G.L. Ragatz, R.M. Monczka, An examination of collaborative planning effectiveness and supply chain performance. J. Supply Chain Manag. 41(2), 14–25 (2005)CrossRefGoogle Scholar
  53. 53.
    L. Ping, Q. Liu, Z. Zhou, H. Wang, Agile Supply Chain Management over the Internet of Things, in 2011 International Conference on Management and Service Science (MASS), (Wuhan, 2011), pp. 1–4Google Scholar
  54. 54.
    K. Pramatari, Collaborative supply chain practices and evolving technological approaches. Supply Chain Manag. 12(3), 210–220 (2007)CrossRefGoogle Scholar
  55. 55.
    R.V. Priya, A. Vadivel, S. Thakur, Maximal pattern mining using fast CP-tree for knowledge discovery. Int. J. Inf. Syst. Soc. Chang. 3(1), 56–74 (2012)CrossRefGoogle Scholar
  56. 56.
    P.J. Reaidy, A. Gunasekaran, A. Spalanzani, Bottom-up approach based on internet of things for order fulfillment in a collaborative warehousing environment. Int. J. Prod. Econ. 159, 29–40 (2015)CrossRefGoogle Scholar
  57. 57.
    R. Roman, J. Zhou, J. Lopez, On the features and challenges of security and privacy in distributed internet of things. Comput. Netw. 57(10), 2266–2279 (2013)CrossRefGoogle Scholar
  58. 58.
    D. Singh, G. Tripathi, A.J. Jara, A survey of internet-of-things: future vision, architecture, challenges and services. 2014 IEEE world forum on internet of things (WF-IoT) (2014)Google Scholar
  59. 59.
    H. Sundmaeker, P. Guillemin, P. Friess, S. Woelfflé, Vision and challenges for realising the internet of things, CERP-IoT – Cluster of European Research Projects on the Internet of Things. 2014 (2010)Google Scholar
  60. 60.
    F. Tao, Y. Zuo, L.D. Xu, L. Zhang, IoT based intelligent perception and access of manufacturing resource towards cloud manufacturing. IEEE Transactions on Industrial Informatics 10(2), 1547–1557 (2014)CrossRefGoogle Scholar
  61. 61.
    C.-W. Tsai, C.-F. Lai, M.-C. Chiang, L.T. Yang, Data mining for internet of things: a survey. IEEE Commun. Surv. Tutorials 16(1), 77–97 (2014)CrossRefGoogle Scholar
  62. 62.
    H. Wang, T. Zhang, Y. Quan, R. Dong, Research on the framework of the environmental internet of things. Int J Sust Dev World 20(3), 199–204 (2013)CrossRefGoogle Scholar
  63. 63.
    C.C. White III, T. Cheong, In-transit perishable product inspection. Res. E Logist. Transp. Rev. 48(1), 310–330 (2012)CrossRefGoogle Scholar
  64. 64.
    B. Xu, L.D. Xu, H. Cai, C. Xie, J. Hu, F. Bu, Ubiquitous data accessing method in IoT-based information system for emergency medical services. IEEE Trans. Ind. Inf. 10(2), 1578–1586 (2014)CrossRefGoogle Scholar
  65. 65.
    M. Porter, The value chain and competitive advantage, Chapter 2 in competitive advantage: creating and sustaining superior performance (Free Press, New York, 1985), pp. 33–61CrossRefGoogle Scholar
  66. 66.
    Z. Zhou, Z. Zhou, Application of internet of things in agriculture products supplies chain management. International Conference on Control Engineering and Communication Technology (ICCECT) (2012)Google Scholar
  67. 67.
    L.J. Krajewski, L.P. Ritzman, M.K. Malhotra, Operations Management: Processes and Supply Chains, 10th edn. (Pearson, 2013)Google Scholar
  68. 68.
    C. Brian Gibson, C. Defee, H. Chen, J.B. Hanna, The Definitive Guide to Integrated Supply Chain Management: Optimize the Interaction between Supply Chain Processes, Tools, and Technologies (Council of Supply Chain Management Professionals), 1st edn. (Prentice Hall Inc, 2014)Google Scholar
  69. 69.
    Miguel Gastón Cedillo-Campos, Supply chain clustering: The next logistics frontier?, International Congress on Logistics & Supply Chain, CiLOG2014Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • S. Kanimozhi Suguna
    • 1
  • Suresh Nanda Kumar
    • 2
  1. 1.Department of CSE, School of ComputingSASTRA Deemed to be UniversityThanjavurIndia
  2. 2.CII Institute of LogisticsChennaiIndia

Personalised recommendations