An Industry 4.0 Solution for the Detection of Dangerous Situations in Civil Work Scenarios

  • Borja BordelEmail author
  • Ramón Alcarria
  • Tomás Robles
  • David González
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 918)


Industry 4.0 is envisioned to apply Cyber-Physical Systems to production systems, assembling lines and other industrial solutions. However, new and innovative approaches may be also designed to solve traditional problems in a more efficient and low-cost manner. In particular, one of the most recognized problems in industry is the prevention of occupational hazards. Many different specific scenarios and risks could be identified in industrial scenarios, but nowadays the industrial sector where (probably) more risks are present is civil works. The use of heavy equipment, where drivers have a limited visual field, is a potential problem for workers at ground level. In this paper it is proposed an Industry 4.0 solution for this situation, where workers are provided with a beaming element, whose signal is received in a central node placed in the machinery. Received signal are processed and analyzed to create alarms and other messages to the driver. The proposed solution is validated in a real scenario using real heavy equipment.


Industry 4.0 Security Civil works Wireless solutions Signal processing 



The research leading to these results has received funding from the Ministry of Economy and Competitiveness through SEMOLA project (TEC2015-68284-R), from the Centre for the Development of Industrial Technology (CDTI) through PERIMETER SECURITY project (ITC-20161228) and from the Autonomous Region of Madrid through MOSI-AGIL-CM project (grant P2013/ICE-3019, co-funded by EU Structural Funds FSE and FEDER).


  1. 1.
    Bordel, B., Alcarria, R., Robles, T., Martín, D.: Cyber–physical systems: extending pervasive sensing from control theory to the Internet of Things. Pervasive Mob. Comput. 40, 156–184 (2017)CrossRefGoogle Scholar
  2. 2.
    Sánchez, B.B., Alcarria, R., de Rivera, D.S., Sánchez-Picot, A.: Enhancing process control in Industry 4.0 scenarios using cyber-physical systems. JoWUA 7(4), 41–64 (2016)Google Scholar
  3. 3.
    Bordel, B., de Rivera, D.S., Sánchez-Picot, Á., Robles, T.: Physical processes control in Industry 4.0-based systems: a focus on cyber-physical systems. In: Ubiquitous Computing and Ambient Intelligence, pp. 257–262. Springer, Cham (2016)CrossRefGoogle Scholar
  4. 4.
    Lee, J., Bagheri, B., Kao, H.A.: A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manuf. Lett. 3, 18–23 (2015)CrossRefGoogle Scholar
  5. 5.
    Theorin, A., Bengtsson, K., Provost, J., Lieder, M., Johnsson, C., Lundholm, T., Lennartson, B.: An event-driven manufacturing information system architecture for Industry 4.0. Int. J. Prod. Res. 55(5), 1297–1311 (2017)CrossRefGoogle Scholar
  6. 6.
    Bagheri, B., Yang, S., Kao, H. A., Lee, J.: Cyber-physical systems architecture for self-aware machines in industry 4.0 environment. IFAC PapersOnLine 48(3), 1622–1627 (2015)CrossRefGoogle Scholar
  7. 7.
    Stock, T., Seliger, G.: Opportunities of sustainable manufacturing in industry 4.0. Procedia CIRP 40, 536–541 (2016)CrossRefGoogle Scholar
  8. 8.
    Weyer, S., Schmitt, M., Ohmer, M., Gorecky, D.: Towards Industry 4.0-Standardization as the crucial challenge for highly modular, multi-vendor production systems. IFAC Papersonline 48(3), 579–584 (2015)CrossRefGoogle Scholar
  9. 9.
    Lasi, H., Fettke, P., Kemper, H.G., Feld, T., Hoffmann, M.: Industry 4.0. Bus. Inf. Syst. Eng. 6(4), 239–242 (2014)CrossRefGoogle Scholar
  10. 10.
    Rüßmann, M., Lorenz, M., Gerbert, P., Waldner, M., Justus, J., Engel, P., Harnisch, M.: Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries, vol. 9. Boston Consulting Group (2015)Google Scholar
  11. 11.
    Wang, S., Wan, J., Zhang, D., Li, D., Zhang, C.: Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Comput. Netw. 101, 158–168 (2016)CrossRefGoogle Scholar
  12. 12.
    Shrouf, F., Ordieres, J., Miragliotta, G.: Smart factories in Industry 4.0: a review of the concept and of energy management approached in production based on the Internet of Things paradigm. In: 2014 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pp. 697–701. IEEE (2014)Google Scholar
  13. 13.
    Lee, J., Kao, H.A., Yang, S.: Service innovation and smart analytics for industry 4.0 and big data environment. Procedia CIRP 16, 3–8 (2014)CrossRefGoogle Scholar
  14. 14.
    Gorecky, D., Schmitt, M., Loskyll, M., Zühlke, D.: Human-machine-interaction in the Industry 4.0 era. In: 2014 12th IEEE International Conference on Industrial Informatics (INDIN), pp. 289–294. IEEE (2014)Google Scholar
  15. 15.
    Kolberg, D., Zühlke, D.: Lean automation enabled by industry 4.0 technologies. IFAC-PapersOnLine 48(3), 1870–1875 (2015)CrossRefGoogle Scholar
  16. 16.
    Wan, J., Tang, S., Shu, Z., Li, D., Wang, S., Imran, M., Vasilakos, A.V.: Software-defined industrial internet of things in the context of industry 4.0. IEEE Sensors J. 16(20), 7373–7380 (2016)Google Scholar
  17. 17.
    Wootton, C.: Samsung ARTIK Reference: The Definitive Developers Guide. Apress, Berkeley (2016)CrossRefGoogle Scholar
  18. 18.
    Schelkunoff, S.A., Friis, H.T.: Antennas: theory and practice, vol. 639. Wiley, New York (1952)zbMATHGoogle Scholar
  19. 19.
    Bordel, B., Alcarria, R., Robles, T., Sánchez-Picot, Á.: Stochastic and information theory techniques to reduce large datasets and detect cyberattacks in Ambient Intelligence Environments. IEEE Access 6, 34896–34910 (2018)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Borja Bordel
    • 1
    Email author
  • Ramón Alcarria
    • 1
  • Tomás Robles
    • 1
  • David González
    • 2
  1. 1.Universidad Politécnica de MadridMadridSpain
  2. 2.Espacios Castellanos de InnovaciónToledoSpain

Personalised recommendations