How to Increase Occupants Safety with No Architectural Modifications: Defining Effective Wayfinding Systems

Chapter
First Online:
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Abstract

Wayfinding is ones of the most significant issues during a fire evacuation in Historical Buildings, mainly because of possible building layout complexity, level of occupants’ familiarity with the architectural spaces, and potential environmental modifications due to fire effects. Proper wayfinding systems could be able to increase safety levels for occupants by reducing the egress time. Furthermore, these solutions are generally able to maintain a low impact on the building itself (and on its layout). However, according to a Behavioral design (BD) approach, they should be designed in order to effective provide the needed assistance to evacuees, by “interacting” with their behaviours. This chapter firstly offers an organization of existing wayfinding strategies, by mainly distinguishing active and passive systems (since they can bring or not “dynamic” directional information to the evacuees). The attention is focused on the interaction with human behaviors and the possibility to apply the systems (and related building components) to Building Heritage scenarios. Methodologies to evaluate the evacuation facilities effectiveness are outlined according to previous researches and BD studies recommendations.

Keywords

Fire Safety Evacuation Time Near Field Communication Architectural Space Building Heritage 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.

References

  1. 1.
    Elsorady DA (2013) Assessment of the compatibility of new uses for heritage buildings: the example of Alexandria National Museum, Alexandria. Egypt J Cultural Herit 15:511–521. doi: 10.1016/j.culher.2013.10.011 CrossRefGoogle Scholar
  2. 2.
    Marrion CE (2016) More effectively addressing fire/disaster challenges to protect our cultural heritage. J Cultural Herit 20:746–749. doi: 10.1016/j.culher.2016.03.013 CrossRefGoogle Scholar
  3. 3.
    Bernardini G, Azzolini M, D-Orazio M, et al (2016) Intelligent evacuation guidance systems for improving fire safety of Italian-style historical theatres without altering their architectural characteristics. J Cultural Heri. doi: 10.1016/j.culher.2016.06.008
  4. 4.
    Naziris IA, Lagaros ND, Papaioannou K (2016) Optimized fire protection of cultural heritage structures based on the analytic hierarchy process. J Build Eng. doi: 10.1016/j.jobe.2016.08.007
  5. 5.
    Ran H, Sun L, Gao X (2014) Influences of intelligent evacuation guidance system on crowd evacuation in building fire. Autom Constr 41:78–82. doi: 10.1016/j.autcon.2013.10.022 CrossRefGoogle Scholar
  6. 6.
    Wong LT, Lo KC (2007) Experimental study on visibility of exit signs in buildings. Build Environ 42:1836–1842. doi: 10.1016/j.buildenv.2006.02.011 CrossRefGoogle Scholar
  7. 7.
    Jeon G-Y, Kim J-Y, Hong W-H, Augenbroe G (2011) Evacuation performance of individuals in different visibility conditions. Build Environ 46:1094–1103. doi: 10.1016/j.buildenv.2010.11.010 CrossRefGoogle Scholar
  8. 8.
    Carattin E, Brannigan V (2012) Controlled evacuation in historical and cultural structures: requirements, limitations and the potential for evacuation models. In: Proceedings of the 5th international symposium on human behavior in fire 2012. Interscience Comms, London, UK, pp 447–459Google Scholar
  9. 9.
    Tuomisaari M (1997) Visibility of exit signs and low-location lighting in smoky conditions. VTT Build Technol 13:389–396Google Scholar
  10. 10.
    Kobes M, Helsloot I, de Vries B et al (2010) Way finding during fire evacuation; an analysis of unannounced fire drills in a hotel at night. Build Environ 45:537–548. doi: 10.1016/j.buildenv.2009.07.004 CrossRefGoogle Scholar
  11. 11.
    Pu S, Zlatanova S (2005) Evacuation route calculation of inner buildings. In: Research book chapter in geo-information for disaster management. Springer, pp 1143–1161Google Scholar
  12. 12.
    Chu L (2010) A RFID-Based hybrid building fire evacuation system on mobile phone. In: Sixth international conference on intelligent information hiding and multimedia signal processing. pp 155–158. doi: 10.1109/IIHMSP.2010.46
  13. 13.
    Veichtlbauer A, Pfeiffenberger T (2013) Dynamic evacuation guidance as safety critical application in building automation. In: S. Bologna et al. (ed) CRITIS 2011. Springer, pp 58–69Google Scholar
  14. 14.
    Van Willigen WH, Neef RM, Lieburg a. Van, Schut MC, (2009) WILLEM: A wireless intelligent evacuation method. I: Third international conference on sensor technologies and applications. pp 382–387. doi: 10.1109/SENSORCOMM.2009.64
  15. 15.
    International Organization for Standardization (2004) ISO 16069:2004. Graphical symbols - Safety signs - Safety way guidance systems (SWGS)Google Scholar
  16. 16.
    Government I (2015) Occupational Safety and Healthcare on work places (D.lgs. 9 aprile 2008, n. 81, Testo coordinato con il D.Lgs. 3 agosto 2009, n. 106) (in Italian). http://www.puntosicuro.it/_resources/files/TU81-08-Ed.Settembre2015.pdf. Accessed 8 Oct 2010
  17. 17.
    Italian Organization for Standardization (UNI) (2004) UNI 7543:2004 - Safety colours and safety signsGoogle Scholar
  18. 18.
    International Organization for Standardization (2011) ISO 3864-1:2011 - Annex A, Relationship between dimensions of safety signs and distance of observationGoogle Scholar
  19. 19.
    US department of Labour (2014) Subpart E - Means of Egress. Design and construction requirements for exit routes. Occupational Safety and Health Standards. https://www.osha.gov/pls/oshaweb/owadisp.show_document?p_table=STANDARDS&p_id=9724. Accessed 6 Oct 2016
  20. 20.
    Parliament of the United Kingdom (1996) Health and Safety (Safety Signs and Signals) Regulation 1996. http://www.legislation.gov.uk/uksi/1996/341/pdfs/uksi_19960341_en.pdf. Accessed 10 Oct 2016
  21. 21.
    German Institute for Standardization (2009). DIN 67510, Photoluminescent pigments and productsGoogle Scholar
  22. 22.
    London Fire Brigade (2015). heritage and buildings of special interest (GN 80). http://www.london-fire.gov.uk/Documents/GN_80.pdf. Accessed 10 Oct 2016
  23. 23.
    Confederation of Fire Protection Associations Europe (2013) Managing fire protection of historic buildings. http://cfpa-e.eu/wp-content/uploads/files/guidelines/CFPA_E_Guideline_No_30_2013_F.pdf. Accessed 8 Oct 2016
  24. 24.
    Italian Government (1996) DM 19/08/1996: Fire safety criteria for entertainment public spaces (Regola tecnica di prevenzione incendi per la progettazione, costruzione ed esercizio dei locali di intrattenimento e di pubblico spettacolo). http://www.vigilfuoco.it/aspx/ReturnDocument.aspx-IdDocumento=52. Accessed 30 July 2016
  25. 25.
    Occhialini M, Bernardini G, Ferracuti F et al (2016) Fire exit signs: the use of neurological activity analysis for quantitative evaluations on their perceptiveness in a virtual environment. Fire Saf J 82:63–75. doi: 10.1016/j.firesaf.2016.03.003 CrossRefGoogle Scholar
  26. 26.
    Proulx G, Bnichou N (2009) Photoluminescent stairway installation for evacuation in office buildings. Fire Technol. 46:471–495. doi: 10.1007/s10694-009-0102-z CrossRefGoogle Scholar
  27. 27.
    Kobes M, Helsloot I, de Vries B, Post JG (2010) Building safety and human behaviour in fire: a literature review. Fire Saf. J 45:1–11. doi: 10.1016/j.firesaf.2009.08.005 CrossRefGoogle Scholar
  28. 28.
    Carattin E (2011) Wayfinding architectural criteria for the design of complex environments in emergency scenarios. In: Capote JA, Alvear D (eds) Evacuation and human behavior in emergency situations. Advanced research workshop proceedings. Universitad de Cantabria, Santander, pp 209–222Google Scholar
  29. 29.
    Fahy RF, Proulx G (2001) Toward creating a database on delay times to start evacuation and walking speeds for use in evacuation modeling. In: 2nd International symposium on human behaviour in fire. MA, USA, Boston, pp 175–183Google Scholar
  30. 30.
    D’Orazio M, Bernardini G, Tacconi S et al (2016) Fire safety in Italian-style historical theatres: how photoluminescent wayfinding can improve occupants- evacuation with no architecture modifications. J Cultural Herit 19:492–501. doi: 10.1016/j.culher.2015.12.002 CrossRefGoogle Scholar
  31. 31.
    Nassar K (2011) Sign visibility for pedestrians assessed with agent-based simulation. Transp Res Rec: J Transp Res Board 2264:18–26. doi: 10.3141/2264-03 CrossRefGoogle Scholar
  32. 32.
    Xie H, Filippidis L, Gwynne S, Galea ER, Blackshields D, Lawrence PJ (2007) Signage legibility distances as a function of observation angle. J Fire Protect Eng 17:41–64. doi: 10.1177/1042391507064025 CrossRefGoogle Scholar
  33. 33.
    Xie H, Filippidis L, Galea ER et al (2012) Experimental analysis of the effectiveness of emergency signage and its implementation in evacuation simulation. Fire Mater 36:367–382. doi: 10.1002/fam.1095
  34. 34.
    Simeone D (2015) Simulating human behaviours in buildings. A previsional model (Simulare il comportamento umano negli edifici. Un modello previsionale-in Italian). Gangemi Editore per le lettere le scienze e le arti, Rome, ItalyGoogle Scholar
  35. 35.
    Marmot A (2002) Architectural determinism. Does design change behaviour? Br J Gen Pract 52:252–253Google Scholar
  36. 36.
    Bernardini G, D’Orazio M, Quagliarini E (2016) Towards a “behavioural design” approach for seismic risk reduction strategies of buildings and their environment. Saf Sci 86:273–294. doi: 10.1016/j.ssci.2016.03.010 CrossRefGoogle Scholar
  37. 37.
    Yu E, Giorgini P, Maiden N, Mylopoulos J (2011) Social modeling for requirements engineering. The MIT Press, CambridgeGoogle Scholar
  38. 38.
    Sagun A, Bouchlaghem D, Anumba CJ (2011) Computer simulations vs. building guidance to enhance evacuation performance of buildings during emergency events. Simul Modell Pract Theory 19:1007–1019. doi: 10.1016/j.simpat.2010.12.001 CrossRefGoogle Scholar
  39. 39.
    Samah KAFA, Hussin B, Basari ASH (2014) The effectiveness of dynamic signage for autonomous evacuation navigation system: an experimental study. In: 3rd international conference on circuits, systems, communications, computers and applications (CSCCA -14), pp 1–9Google Scholar
  40. 40.
    Ministry of Interior (Italy) (1992) D.M. 20-05-1992 n. 569 - Fire safety in historical buildings used as museum and art galleries. www.vigilfuoco.it/sitiVVF/ascolipiceno/downloadFile.aspx?s=85&f=11286. Accessed 10 Oct 2016
  41. 41.
    British Standards Institution (2000) BS 5499-4:2000-Safety signs, including fire safety signs. Code of practice for escape route signing, 2000Google Scholar
  42. 42.
    PSA/PSPA (2008). PSA/PSPA Guide to the Use of Photoluminescent Safety Markings. http://www.everglow.us/pdf/photoluminescent-egress-markings-guide-exit-stairs-psa-pspa.pdf. Accessed 30 Oct 2016
  43. 43.
    Liao J-H, Shaw D (2013) The use of laser scattering and energy harvesting technology for fire evacuation. Saf Sci 55:165–172. doi: 10.1016/j.ssci.2013.01.013 CrossRefGoogle Scholar
  44. 44.
    Ferreira TM, Vicente R, Mendes Raimundo, da Silva JA et al (2016) Urban fire risk: Evaluation and emergency planning. J Cultural Herit. 181–189. doi: 10.1016/j.culher.2016.01.011
  45. 45.
    Paulsen T (1994) The effect of escape route lnforemation on mobility and way finding under smoke logged conditions. In: Proceedings of fourth international symposium on fire safety science. pp 693–704Google Scholar
  46. 46.
    Jeon G-Y, Hong W-H (2009) An experimental study on how phosphorescent guidance equipment influences on evacuation in impaired visibility. J Loss Prevent Process Ind 22:934–942. doi: 10.1016/j.jlp.2009.08.008 CrossRefGoogle Scholar
  47. 47.
    Yenumula K, Kolmer C, Pan J, Su X (2015) BIM-controlled signage system for building evacuation. Procedia Eng 118:284–289. doi: 10.1016/j.proeng.2015.08.428 CrossRefGoogle Scholar
  48. 48.
    Nelson HE, Mowrer FW (2002) Emergency movement. In: SFPE handbook of fire protection engineering. National Fire Protection Association, pp 367–380Google Scholar
  49. 49.
    Seyfried A, Steffen B, Klingsch W, Boltes M (2005) The fundamental diagram of pedestrian movement revisited. J Stat Mech 2005:1–13CrossRefGoogle Scholar
  50. 50.
    Teixeira T, Dublon G, Savvides A (2010) A survey of human-sensing: methods for detecting presence, count, location, track, and identity. ACM computing surveys. http://thiagot.com/papers/teixeira_techrep10_survey_of_human_sensing.pdf. Accessed 24 Oct 2016
  51. 51.
    Guan Q, Li C, Guo X, Wang G (2014) Compressive classification of human motion using pyroelectric infrared sensors. Pattern Recognit Lett 49:231–237. doi: 10.1016/j.patrec.2014.07.018 CrossRefGoogle Scholar
  52. 52.
    Kuipers M, Tom A, Pinheiro T et al (2014) Building space-use analysis system - A multi location/multi sensor platform. Autom Constr 47:10–23. doi: 10.1016/j.autcon.2014.07.001 CrossRefGoogle Scholar
  53. 53.
    D’Orazio M, Longhi S, Olivetti P, Bernardini G (2015) Design and experimental evaluation of an interactive system for pre-movement time reduction in case of fire. Autom Constr 52:16–28. doi: 10.1016/j.autcon.2015.02.015 CrossRefGoogle Scholar
  54. 54.
    Chu L, Wu S-J (2012) A real-time fire evacuation system with cloud computing. J Converg Inf Technol 7:208–215. doi: 10.4156/jcit.vol7.issue7.26 Google Scholar
  55. 55.
    Groner NE (2016) A decision model for recommending which building occupants should move where during fire emergencies. Fire Saf J 80:20–29. doi: 10.1016/j.firesaf.2015.11.002 CrossRefGoogle Scholar
  56. 56.
    Ahn J, Han R (2012) An indoor augmented-reality evacuation system for the smartphone using personalized pedometry. Human-centric Comput Inf Sci 2:18. doi: 10.1186/2192-1962-2-18 CrossRefGoogle Scholar
  57. 57.
    Wang J, Zhao H, Winter S (2015) Integrating sensing, routing and timing for indoor evacuation. Fire Saf J 78:111–121. doi: 10.1016/j.firesaf.2015.08.009 CrossRefGoogle Scholar
  58. 58.
    Kobes M, Helsloot I, de Vries B, Post J (2010) Exit choice, (pre-)movement time and (pre-)evacuation behaviour in hotel fire evacuation - Behavioural analysis and validation of the use of serious gaming in experimental research. Procedia Eng 3:37–51. doi: 10.1016/j.proeng.2010.07.006 CrossRefGoogle Scholar
  59. 59.
    Øien K, Utne IB, Tinmannsvik RK, Massaiu S (2011) Building safety indicators: Part 2 - application, practices and results. Saf Sci 49:162–171. doi: 10.1016/j.ssci.2010.05.015
  60. 60.
    Doncaster clinical commissioning group (2014) Fire Safety Policy. http://www.doncasterccg.nhs.uk/wp-content/uploads/2015/07/Fire-Safety-Policy-2014.pdf. Accessed 30 Oct 2016
  61. 61.
    Korhonen T, Hostikka S (2010) Fire dynamics simulator with evacuation: FDS + Evac technical reference and user’s guide. VTT Working Papers 119. https://pdfs.semanticscholar.org/f25c/089e83048beefc756bf17a210f0efff0b8b3.pdf. Accessed 12 Oct 2016
  62. 62.
    D’Orazio M, Spalazzi L, Quagliarini E, Bernardini G (2014) Agent-based model for earthquake pedestrians- evacuation in urban outdoor scenarios: behavioural patterns definition and evacuation paths choice. Saf Sci 62:450–465. doi: 10.1016/j.ssci.2013.09.014 CrossRefGoogle Scholar
  63. 63.
    Ronchi E, Kuligowski ED, Reneke PA, et al (2013) The process of verification and validation of building fire evacuation models. NIST Technical Note (n.1822)Google Scholar
  64. 64.
    Helbing D, Johansson AF (2010) Pedestrian, crowd and evacuation dynamics. In: Encyclopedia of complexity and systems science. Springer, pp 6476–6495Google Scholar
  65. 65.
    D’Orazio M, Quagliarini E, Bernardini G, Spalazzi L (2014) EPES-Earthquake pedestrians’ evacuation simulator: a tool for predicting earthquake pedestrians’ evacuation in urban outdoor scenarios. Int J Disaster Risk Reduct 10:153–177. doi: 10.1016/j.ijdrr.2014.08.002 CrossRefGoogle Scholar
  66. 66.
    Johansson A, Helbing D, Al-Abideen HZ, Al-Bosta S (2008) From crowd dynamics to crowd safety: a video-based analysis. Adv Complex Syst 11:497–527CrossRefMATHGoogle Scholar
  67. 67.
    Shiwakoti N, Sarvi M (2013) Understanding pedestrian crowd panic: a review on model organisms approach. J Transp Geogr 26:12–17. doi: 10.1016/j.jtrangeo.2012.08.002 CrossRefGoogle Scholar
  68. 68.
    Averill JD, Mileti DS, Peacock RD et al (2005) World Trade Center Disaster Occupant Behavior, Egress, and Emergency Communications (NIST NCSTAR 1-7). U.S. Government printing office, Washington, D.C. https://www.nist.gov/node/599651?pub_id=101046. Accessed 10 Oct 2016
  69. 69.
    Yang X, Wu Z (2012) Civilian monitoring video records for earthquake intensity: a potentially unbiased online information source of macro-seismology. Nat Hazards 65:1765–1781. doi: 10.1007/s11069-012-0447-3 CrossRefGoogle Scholar
  70. 70.
    Gwynne SMV, Boyce KE, Kuligowski ED, et al (2016) Pros and cons of egress drills. In: Interflam 2016. Fire science and engineering conference. Interscience Comms, Windsor, UK, pp 1657–1670Google Scholar
  71. 71.
    Ministry of Interior (Italy) (2015) DM 03/08/2015: Fire safety criteria (Approvazione di norme tecniche di prevenzione incendi, ai sensi dell’articolo 15 del decreto legislativo 8 marzo 2006, n. 139.). http://www.vigilfuoco.it/sitiVVF/ascolipiceno/downloadFile.aspx?s=85&f=56102. Accessed 26 Sept 2016
  72. 72.
    Shi L, Xie Q, Cheng X et al (2009) Developing a database for emergency evacuation model. Build Environ 44:1724–1729. doi: 10.1016/j.buildenv.2008.11.008 CrossRefGoogle Scholar
  73. 73.
    Kinateder M, Ronchi E, Nilsson D (2014) Virtual reality for fire evacuation research. In: Federated conference on computer science and information systems. pp 319–321Google Scholar
  74. 74.
    Cosma G, Ronchi E, Nilsson D (2016) Way-finding lighting systems for rail tunnel evacuation: a virtual reality experiment with Oculus Rift. J Transp Saf Sec 8:101–117. doi: 10.1080/19439962.2015.1046621 Google Scholar
  75. 75.
    Vilar E, Rebelo F, Noriega P et al (2014) Effects of competing environmental variables and signage on route-choices in simulated everyday and emergency wayfinding situations. Ergonomics 57:511–524. doi: 10.1080/00140139.2014.895054 CrossRefGoogle Scholar
  76. 76.
    McConnell NC, Boyce KE, Shields J et al (2010) The UK 9/11 evacuation study: analysis of survivors- recognition and response phase in WTC1. Fire Saf J 45:21–34. doi: 10.1016/j.firesaf.2009.09.001 CrossRefGoogle Scholar
  77. 77.
    Helbing D, Farkas JI, Molnar P, Vicsek T (2002) Simulation of pedestrian crowds in normal and evacuation situations. In: Pedestrian and evacuation dynamics. Berlin, pp 21–58Google Scholar
  78. 78.
    Riad JK, Norris FH, Ruback RB (1999) Predicting evacuation in two major disasters: risk perception, social influence, and access to resources1. J Appl Soc Psychol 29:918–934CrossRefGoogle Scholar
  79. 79.
    Babrauskas V, Fleming JM, Russell BD (2010) RSET/ASET, a flawed concept for fire safety assessment. Fire Mater 34:341–355. doi: 10.1002/fam CrossRefGoogle Scholar
  80. 80.
    Confederation of Fire Protection Associations Europe (2009) Fire safety engineering concerning evacuation from buildings - Guidelines No 19:2009. http://www.cfpa-e.eu/wp-content/uploads/files/guidelines/CFPA_E_Guideline_No_19_2009.pdf. Accessed 30 July 2016
  81. 81.
    Zheng X, Zhong T, Liu M (2009) Modeling crowd evacuation of a building based on seven methodological approaches. Build Environ 44:437–445. doi: 10.1016/j.buildenv.2008.04.002 CrossRefGoogle Scholar
  82. 82.
    Thompson P, Nilsson D, Boyce K, McGrath D (2015) Evacuation models are running out of time. Fire Saf J 78:251–261. doi: 10.1016/j.firesaf.2015.09.004 CrossRefGoogle Scholar
  83. 83.
    Schadschneider A, Klingsch W, Klpfel H et al (2009) Evacuation dynamics: empirical results, modeling and applications. Encycl Complex Syst Sci, pp 3142–3176 la-englishGoogle Scholar
  84. 84.
    Zipf GK (1950) Human behavior and the principle of least effort. J Clin Psychol 6:306. doi: 10.1002/1097-4679(195007)6:3<306::AID-JCLP2270060331>3.0.CO;2-7 Google Scholar
  85. 85.
    Lakoba TI, Kaup DJ, Finkelstein NM (2005) Modifications of the Helbing-Molnar-Farkas-Vicsek social force model for pedestrian evolution. Simulation 81:339–352. doi: 10.1177/0037549705052772 CrossRefGoogle Scholar
  86. 86.
    Rabiaa C, Foudil C (2010) Crowd simulation influenced by agent’s socio-psychological state. J Comput 2:48–54Google Scholar
  87. 87.
    Proulx G (2002) Movement of people: the evacuation timing. In: SFPE handbook of fire protection engineering. National Fire Protection Association, pp 342–366Google Scholar
  88. 88.
    Villagran De Leon JC (2006) Vulnerability: a conceptual and methodological review. http://collections.unu.edu/eserv/UNU:1871/pdf3904.pdf. Accessed 14 Sept 2016
  89. 89.
    Yi-fan L, Jun-min C, Jie J et al (2011) Analysis of crowded degree of emergency evacuation at “Bottleneck” position in subway station based on stairway level of service. Procedia Eng 11:242–251. doi: 10.1016/j.proeng.2011.04.653 CrossRefGoogle Scholar
  90. 90.
    Fruin JJ (1971) Designing for pedestrians: a level of service concept. Highw Res Rec 355:1–15Google Scholar
  91. 91.
    Klpfel T, Meyer-Knig H (2014) PedGo Guardian: an assistant for evacuation decision making. In: Weidmann U, Kirsch U, Schreckenberg M (eds) Pedestrian and evacuation dynamics 2012. Springer International Publishing, pp 445–454Google Scholar
  92. 92.
    Kunwar B, Simini F, Johansson A (2014) Large scale pedestrian evacuation modeling framework using volunteered geographical information. Transp Res Procedia 2:813–818. doi: 10.1016/j.trpro.2014.09.092 CrossRefGoogle Scholar
  93. 93.
    Purser DA (1995) Toxicity assessment of combustion products. In: National Fire Protection Association (ed) SFPE handbook of fire protection engineering, 2nd edn. Quincy, MA, pp 2/28–2/146Google Scholar
  94. 94.
    Hull TR, Stec AA (2010) Introduction to fire toxicity. In: Fire toxicity. Elsevier, pp 3–25Google Scholar

Copyright information

© The Author(s) 2017

Authors and Affiliations

  1. 1.Department of Construction, Civil Engineering and ArchitectureUniversità Politecnica delle MarcheAnconaItaly

Personalised recommendations