Advertisement

Secure ambient intelligence prototype for airports

  • 16 Accesses

Abstract

Nowadays, many technological advances applied to the Internet of Things (IoT) make the introduction of innovative sensors aimed to deploy efficient wireless sensor networks possible. In order to improve the environment and people’s lives, real time analysis of certain environmental variables may favour the reduction of health risks related to the deterioration of air quality. To this respect, the proposed system implements a particular prototype of IoT device characterized by the assembly of ambient sensors capable of measuring pollutant gases, temperature and humidity. For this purpose, Raspberry Pi and Arduino platforms are used. Several security methods are introduced to ensure the integrity of air quality data by implementing Merkle Trees on each IoT node and on the Cloud server. Besides, the authenticity of IoT devices and the confidentiality of communications are guaranteed by implementing HTTPS requests. Finally, authentication tokens are used to identify system users, and different security rules are applied to manage database operations.

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

Access options

Buy single article

Instant unlimited access to the full article PDF.

US$ 39.95

Price includes VAT for USA

Subscribe to journal

Immediate online access to all issues from 2019. Subscription will auto renew annually.

US$ 99

This is the net price. Taxes to be calculated in checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

References

  1. Aarts E, Wichert R (2009) Ambient intelligence. In: Bullinger HJ (ed) Technology guide. Springer, Berlin, Heidelberg, pp 244–249

  2. AENA (2018) Informe anual 2018, aena. http://www.aena.es/csee/ccurl/792/416/Informe2018_provisionales.pdf. Accessed 17 May 2019 (online)

  3. Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. Comput Netw 38(4):393–422

  4. Android (2019) Android developers. https://developer.android.com/?hl=es-419. Accessed 17 May 2019 (online)

  5. Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54(15):2787–2805

  6. Bernstein JA, Alexis N, Bacchus H, Bernstein IL, Fritz P, Horner E, Li N, Mason S, Nel A, Oullette J et al (2008) The health effects of nonindustrial indoor air pollution. J Allergy Clin Immunol 121(3):585–591

  7. Brown NJ (2019) Indoor air quality [Electronic version]. Cornell University, Workplace Health and Safety Program, Ithaca, NY

  8. Caballero-Gil C, Caballero-Gil P, Molina-Gil J (2015) Self-organized clustering architecture for vehicular ad hoc networks. Int J Distrib Sens Netw 11(8):1–12

  9. Cooper D, Santesson S, Farrell S, Boeyen S, Housley R, Polk W (2008) Internet x. 509 public key infrastructure certificate and certificate revocation list (crl) profile. Tech. rep

  10. Dang QH (2015) Secure hash standard. No. Federal Inf. Process. Stds. (NIST:FIPS)-180-4

  11. de Madrid C (2018) Calidad del ambiente interior en edificios de uso público. http://www.madrid.org/bvirtual/BVCM020191.pdf. Accessed 17 May 2019 (online)

  12. ExpressJS (2019) Expressjs. https://expressjs.com/es/. Accessed 17 May 2019 (online)

  13. Fang L, Clausen G, Fanger PO (1998) Impact of temperature and humidity on the perception of indoor air quality. Indoor Air 8(2):80–90

  14. INSHT (2001) Instituto nacional de seguridad e higiene en el trabajo. http://www.insht.es/InshtWeb/Contenidos/Documentacion/FichasTecnicas/NTP/Ficheros/601a700/ntp_607.pdf. Accessed 17 May 2019 (online)

  15. Leff A, Rayfield JT (2001) Web-application development using the model/view/controller design pattern. In: Enterprise Distributed Object Computing Conference, 2001. EDOC’01. Proceedings Fifth IEEE International, IEEE, Seattle, WA, USA, 4–7 Sept 2001, pp 118–127. https://doi.org/10.1109/EDOC.2001.950428

  16. Li H, Lu R, Zhou L, Yang B, Shen X (2014) An efficient merkle-tree-based authentication scheme for smart grid. IEEE Syst J 8(2):655–663

  17. Lombardo L, Corbellini S, Parvis M, Elsayed A, Angelini E, Grassini S (2018) Wireless sensor network for distributed environmental monitoring. IEEE Trans Instrum Meas 67(5):1214–1222

  18. MCP3008 (2008) Analog to digital converter. https://cdn-shop.adafruit.com/datasheets/MCP3008.pdf. Accessed 17 May 2019 (online)

  19. Mao J, Zhang Y, Li P, Li T, Wu Q, Liu J (2017) A position-aware merkle tree for dynamic cloud data integrity verification. Soft Comput 21(8):2151–2164

  20. Merkle RC (1980) Protocols for public key cryptosystems. In: 1980 IEEE symposium on security and privacy. IEEE Computer Society, Atlanta, CA, USA, pp 122–134

  21. Morawska L, Thai PK, Liu X, Asumadu-Sakyi A, Ayoko G, Bartonova A, Bedini A, Chai F, Christensen B, Dunbabin M et al (2018) Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone? Environ Int 116:286–299

  22. NodeJS (2019) Nodejs. https://nodejs.org/es/. Accessed 17 May 2019 (online)

  23. OMS (2005) Guía de calidad del aire de la oms. https://apps.who.int/iris/bitstream/handle/10665/69478/WHO_SDE_PHE_OEH_06.02_spa.pdf;jsessionid=8A662DDB35BCFC8C37FA4EE87654486D?sequence=1. Accessed 17 May 2019 (online)

  24. OWASP (2019) Open web application security project. https://www.owasp.org/index.php/Main_Page. Accessed 17 May 2019 (online)

  25. Oliver M, Teruel M, Molina J, Romero-Ayuso D, González P (2018) Ambient intelligence environment for home cognitive telerehabilitation. Sensors 18(11):3671

  26. Przydatek B, Song D, Perrig A (2003) SIA: secure information aggregation in sensor networks. In: Proceedings of the 1st international conference on embedded networked sensor systems. ACM, pp 255–265. https://doi.org/10.1145/958491.958521

  27. Schlenker W, Walker WR (2015) Airports, air pollution, and contemporaneous health. Rev EconStud 83(2):768–809

  28. Scott DW (2009) Sturges’ rule. Wiley Interdiscip Rev Comput Stat 1(3):303–306

  29. Sipani JP, Patel RH, Upadhyaya T, Desai A (2018) Wireless sensor network for monitoring & control of environmental factors using arduino. Int J Interact Mobile Technol 12(2)

  30. Stergiou C, Psannis KE, Kim BG, Gupta B (2018) Secure integration of iot and cloud computing. Future Gen Comput Syst 78:964–975

  31. Tapia DI, Abraham A, Corchado JM, Alonso RS (2010) Agents and ambient intelligence: case studies. J Ambient Intell Humaniz Comput 1(2):85–93

  32. Trasande L, Thurston GD (2005) The role of air pollution in asthma and other pediatric morbidities. J Allergy Clin Immunol 115(4):689–699

  33. VueJS (2019) Vuejs—Javascript framework. https://vuejs.org/. Accessed 17 May 2019 (online)

Download references

Acknowledgements

Research supported by the Spanish Ministry of Science, Innovation and Universities, the FEDER Fund, the Centre for the Development of Industrial Technology and the CajaCanarias Foundation, under Projects RTI2018-097263-B-I00, C2017/3-9, IDI-20160465 and DIG02-INSITU.

Author information

Correspondence to Pino Caballero-Gil.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rodríguez-Pérez, N., Toledo-Castro, J., Caballero-Gil, P. et al. Secure ambient intelligence prototype for airports. J Ambient Intell Human Comput (2020) doi:10.1007/s12652-020-01683-y

Download citation

Keywords

  • Air quality
  • Wireless sensor networks
  • Merkle trees
  • Security
  • Airports