SpringerLink
Log in

Intelligent environments and assistive technologies for assisting visually impaired people: a systematic literature review

  • Long Paper
  • Published:
Universal Access in the Information Society Aims and scope Submit manuscript

Abstract

Intelligent environments (IE) refer to physical spaces imbued with pervasive and seamless intelligence, created to proactively support individuals in their daily routines. Developments in technologies such as the internet of things (IoT) and artificial intelligence (AI) have taken these environments from theoretical notions to practical realities. Simultaneously, the field of ambient assisted living (AAL) has made significant strides. Evolving from AT, AAL represents an application of IE that specifically seeks to enable individuals-especially those with disabilities or the elderly-to lead healthier, more independent, and dignified lives through the assistance of technology integrated within their living environments. The confluence of IE and AAL has led to the rise of innovative solutions aimed at enhancing the lives of individuals with special needs, such as the visually impaired people (VIP). This research presents a systematic literature review investigating the utilization of IE, underpinned by AAL principles, in supporting VIPs. Initially, a pool of 14,760 studies was obtained from 9 databases, all published up to December 2022. After applying specific inclusion and exclusion criteria, this pool was reduced to 101 articles. Each of these articles was reviewed, analyzed, and categorized into four functional and operating principle categories to address five research questions. The study proposes multiple taxonomies as an approach to holistically synthesize the various technologies and devices categorized in the reviewed articles. Emerging research challenges and trends in this domain are highlighted, with a substantial trend being the escalating use of deep learning (DL) techniques. These techniques have been pivotal in the development of systems focused on object detection, path recognition, and navigation for devices, particularly smartphones, geared towards enhancing the lives of VIPs.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

References

  1. Cook, D.J., Augusto, J.C., Jakkula, V.R.: Ambient intelligence: technologies, applications, and opportunities. Pervasive Mob. Comput. 5(4), 277–298 (2009)

    Article  Google Scholar 

  2. Dohr, A., Modre-Opsrian, R., Drobics, M., Hayn, D., Schreier, G.: The internet of things for ambient assisted living. IEEE J. Inf. Technol. Biomed. 14(2), 277–284 (2010)

    Google Scholar 

  3. A.I.T.A: Assistive Technology Industry Association. Assistive Technology Industry Association (2022). https://www.atia.org/

  4. Cook, A.M., Polgar, J.M.: Assistive Technologies: Principles and Practice, 2nd edn. Mosby, St. Louis (2002)

    Google Scholar 

  5. Schneiderman, B.: The Science of Human–Computer Interaction: A Multidisciplinary Approach. CRC Press, Boca Raton (2012)

    Google Scholar 

  6. Report, W.H.O.: World Report on Vision. World Health Organization (2019). https://www.who.int/publications/i/item/9789241516570

  7. Organization, W.H.: Visual impairment and blindness. Accessed 15 July 2023 (2023). http://www.who.int/news-room/fact-sheets/detail/visual-impairment-and-blindness

  8. Organization, W.H., Fund, U.N.C.: Global Report on Assistive Technology. WHO and UNICEF (2022)

  9. Thordardottir, B., Fänge, A.M., Lethin, C., Gatta, D.R., Chiatti, C.: Acceptance and use of innovative assistive technologies among people with cognitive impairment and their caregivers: a systematic review. Biomed. Res. Int. (2019)

  10. Priscila, C., Cristina, S., Karina, C., Alexandra, B.: A systematic literature review on devices and systems for ambient assisted living: solutions and trends from different user perspectives. In: 2018 International Conference on eDemocracy e Government (ICEDEG), pp. 59–66 (2018). https://doi.org/10.1109/ICEDEG.2018.8372367

  11. Kuriakose, B., Shrestha, R., Sandnes, F.E.: Tools and technologies for blind and visually impaired navigation support: a review. IETE Tech. Rev. 39(1), 3–18 (2022). https://doi.org/10.1080/02564602.2020.1819893

    Article  Google Scholar 

  12. Rute, B., Isabel, M.A., Joao, P., Goncalves, S.A., Pacheco, R.N.: Methodological quality of user-centered usability evaluation of ambient assisted living solutions: a systematic literature review. Int. J. Environ. Res. Public Health (2021). https://doi.org/10.3390/ijerph182111507

    Article  Google Scholar 

  13. Ashraf, M.M., Hasan, N., Lewis, L., Hasan, M.R., Ray, P.: A systematic literature review of the application of information communication technology for visually impaired people. Int. J. Disabil. Manag. 11, 1–18 (2017)

    Google Scholar 

  14. Jovanovic, M., Mitrov, G., Zdravevski, E., Lameski, P., Colantonio, S., Kampel, M., Tellioglu, H., Florez-Revuelta, F.: Ambient assisted living: sco** review of artificial intelligence models, domains, technology, and concerns. J. Med. Internet Res. 24(11), 36553 (2022). https://doi.org/10.2196/36553

    Article  Google Scholar 

  15. Kitchenham, B.A., Charters, S.: Guidelines for performing systematic literature reviews in software engineering. Tech. Rep. EBSE 2007-001. Keele University and Durham University Joint Report (2007)

  16. Kitchenham, B., Pretorius, R., Budgen, D., Brereton, O.P., Turner, M., Niazi, M., Linkman, S.: Systematic literature reviews in software engineering—a tertiary study. Inf. Softw. Technol. 52(8), 792–805 (2010)

    Article  Google Scholar 

  17. Petticrew, M., Roberts, H.: Systematic Reviews in the Social Sciences: A Practical Guide, p. 352. Blackwell, Oxford (2006)

    Book  Google Scholar 

  18. Sadia, Z., Muhammad, A., Bin, A.M., Tauqeer, F., Munir, A., Adnan, K.M.: Assistive devices analysis for visually impaired persons: a review on taxonomy. IEEE Access 10, 13354–13366 (2022). https://doi.org/10.1109/ACCESS.2022.3146728

    Article  Google Scholar 

  19. Tzovaras, D., Nikolakis, G., Fergadis, G., Malassiotis, S., Stavrakis, M.: Virtual environments for the training of the visually impaired. In: Universal Access and Assistive Technology, pp. 151–160. Springer, London (2002)

  20. Shinohara, K.: Designing assistive technology for blind users. In: Proceedings of the 8th International ACM SIGACCESS Conference on Computers and Accessibility, pp. 293–294 (2006)

  21. Coroama, V.: Experiences from the design of a ubiquitous computing system for the blind. In: CHI’06 Extended Abstracts on Human Factors in Computing Systems, pp. 664–669 (2006)

  22. White, G.R., Fitzpatrick, G., McAllister, G.: Toward accessible 3d virtual environments for the blind and visually impaired. In: Proceedings of the 3rd International Conference on Digital Interactive Media in Entertainment and Arts, pp. 134–141 (2008)

  23. Narasimhan, P., Gandhi, R., Rossi, D.: Smartphone-based assistive technologies for the blind. In: Proceedings of the 2009 International Conference on Compilers, Architecture, and Synthesis for Embedded Systems, pp. 223–232 (2009)

  24. José, J., Farrajota, M., Rodrigues, J.M.F., Buf, J.M.H.: The smartvision local navigation aid for blind and visually impaired persons. Int. J. Digit. Content Technol. Appl. 5(5), 362–375 (2011)

    Google Scholar 

  25. Bălan, O., Moldoveanu, A., Moldoveanu, F., Morar, A., Asavei, V.: Assistive it for visually imapired people. J. Inf. Syst. Oper. Manag. 7(2), 391–404 (2013)

    Google Scholar 

  26. Augusto, J.C., Callaghan, V., Cook, D., Kameas, A., Satoh, I.: Intelligent environments: a manifesto. HCIS 3(1), 1–18 (2013)

    Google Scholar 

  27. Dunai, L.D., Lengua, I.L., Tortajada, I., Simon, F.B.: Obstacle detectors for visually impaired people. In: 2014 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), pp. 809–816. IEEE (2014)

  28. Kinoe, Y., Noguchi, A.: Qualitative study for the design of assistive technologies for improving quality of life of visually impaired. In: International Conference on Human Interface and the Management of Information, pp. 602–613. Springer (2014)

  29. Mahmud, N., Saha, R., Zafar, R., Bhuian, M., Sarwar, S.: Vibration and voice operated navigation system for visually impaired person. In: 2014 International Conference on Informatics, Electronics & Vision (ICIEV), pp. 1–5. IEEE (2014)

  30. Csapó, Á., Wersényi, G., Nagy, H., Stockman, T.: A survey of assistive technologies and applications for blind users on mobile platforms: a review and foundation for research. J. Multimodal User Interfaces 9(4), 275–286 (2015)

    Article  Google Scholar 

  31. Paredes, H., Fernandes, H., Sousa, A., Fernandes, L., Koch, F., Fortes, R., Filipe, V., Barroso, J.: Exploring smart environments through human computation for enhancing blind navigation. In: International Workshop on Multiagent Foundations of Social Computing, pp. 66–76. Springer (2015)

  32. Owayjan, M., Hayek, A., Nassrallah, H., Eldor, M.: Smart assistive navigation system for blind and visually impaired individuals. In: 2015 International Conference on Advances in Biomedical Engineering (ICABME), pp. 162–165. IEEE (2015)

  33. Sato, S., Yamashita, A., Matsubayashi, K.: A positioning system with rfid tags and qzss for navigating the visually impaired. In: 2016 Fifth ICT International Student Project Conference (ICT-ISPC), pp. 129–132. IEEE (2016)

  34. Poggi, M., Mattoccia, S.: A wearable mobility aid for the visually impaired based on embedded 3d vision and deep learning. In: 2016 IEEE Symposium on Computers and Communication (ISCC), pp. 208–213. IEEE (2016)

  35. Sivan, S., Darsan, G.: Computer vision based assistive technology for blind and visually impaired people. In: Proceedings of the 7th International Conference on Computing Communication and Networking Technologies, pp. 1–8 (2016)

  36. Sharma, A.: Computer vision guided navigation system for visually impaired. PhD thesis, National Institute of Technology (2016)

  37. Aggravi, M., Salvietti, G., Prattichizzo, D.: Haptic assistive bracelets for blind skier guidance. In: Proceedings of the 7th Augmented Human International Conference 2016, pp. 1–4 (2016)

  38. Filgueiras, T.S., Lima, A.C.O., Baima, R.L., Oka, G.T.R., Cordovil, L.A.Q., Bastos, M.P.: Vibrotactile sensory substitution on personal navigation: Remotely controlled vibrotactile feedback wearable system to aid visually impaired. In: 2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA), pp. 1–5. IEEE (2016)

  39. Liu, K.-C., Wu, C.-H., Tseng, S.-Y., Tsai, Y.-T.: Voice helper: a mobile assistive system for visually impaired persons. In: 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, pp. 1400–1405. IEEE (2015)

  40. Tao, Y., Ding, L., Ganz, A.: Indoor navigation validation framework for visually impaired users. IEEE Access 5, 21763–21773 (2017)

    Article  Google Scholar 

  41. Kallara, S.B., Raj, M., Raju, R., Mathew, N.J., Padmaprabha, V., Divya, D.: Indriya—a smart guidance system for the visually impaired. In: 2017 International Conference on Inventive Computing and Informatics (ICICI), pp. 26–29. IEEE (2017)

  42. Saleh, K., Zeineldin, R.A., Hossny, M., Nahavandi, S., El-Fishawy, N.A.: Navigational path detection for the visually impaired using fully convolutional networks. In: 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 1399–1404. IEEE (2017)

  43. Götzelmann, T., Kreimeier, J.: Optimization of navigation considerations of people with visual impairments through ambient intelligence: a case study. In: Proceedings of the 13th ACM International Conference on PErvasive Technologies Related to Assistive Environments, pp. 1–6 (2020)

  44. Hudec, M., Smutny, Z.: Rudo: a home ambient intelligence system for blind people. Sensors 17(8), 1926 (2017)

    Article  Google Scholar 

  45. Khder, M.A., AlZaqebah, M.A., Abazeed, A., Saifi, M.A.: Smart shoes for visually impaired/blind people. ICSF 2017 Kingdom of Bahrain, p. 479 (2017)

  46. Billah, S.M., Ashok, V., Porter, D.E., Ramakrishnan, I.: Ubiquitous accessibility for people with visual impairments: are we there yet? In: Proceedings of the 2017 Chi Conference on Human Factors in Computing Systems, pp. 5862–5868 (2017)

  47. Bine, L.M.S., Costa, Y.M., Aylon, L.B.R.: Automata classification with convolutional neural networks for use in assistive technologies for the visually impaired. In: Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference, pp. 157–164 (2018)

  48. Mahida, P.T., Shahrestani, S., Cheung, H.: Comparision of pathfinding algorithms for visually impaired people in iot based smart buildings. In: 2018 28th International Telecommunication Networks and Applications Conference (ITNAC), pp. 1–3. IEEE (2018)

  49. Hashimoto, Y., Takagi, N.: Development of audio-tactile graphic system aimed at facilitating access to visual information for blind people. In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 2283–2288. IEEE (2018)

  50. Díaz, J.E., Márquez, J.L., Sánchez, M., Sánchez-Aguilera, J.M., Sánchez, M.A., Bajo, J.: Diami: Distributed intelligent environment for blind musicians. In: International Work-Conference on Artificial Neural Networks, pp. 475–482. Springer (2009)

  51. Dutta, S., Barik, M.S., Chowdhury, C., Gupta, D.: Divya-dristi: a smartphone based campus navigation system for the visually impaired. In: 2018 Fifth International Conference on Emerging Applications of Information Technology (EAIT), pp. 1–3. IEEE (2018)

  52. Shih, M.-L., Chen, Y.-C., Tung, C.-Y., Sun, C., Cheng, C.-J., Chan, L., Varadarajan, S., Sun, M.: Dlwv2: a deep learning-based wearable vision-system with vibrotactile-feedback for visually impaired people to reach objects. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1–9. IEEE (2018)

  53. Aljahdali, M., Abokhamees, R., Bensenouci, A., Brahimi, T., Bensenouci, M.-A.: Iot based assistive walker device for frail & visually impaired people. In: 2018 15th Learning and Technology Conference (L &T), pp. 171–177. IEEE (2018)

  54. Martillano, D.A., Chowdhury, A.F.D., Dellosa, J.C.M., Murcia, A.A., Mangoma, R.J.P.: Pindots: an assistive six-dot braille cell keying device on basic notation writing for visually impaired students with iot technology. In: Proceedings of the 2018 2nd International Conference on Education and E-Learning, pp. 41–47 (2018)

  55. Suda, S., Ohnishi, K., Iwazaki, Y., Asami, T.: Robustness of machine learning pedestrian signal detection applied to pedestrian guidance device for persons with visual impairment. In: 2018 12th France-Japan and 10th Europe-Asia Congress on Mechatronics, pp. 116–121. IEEE (2018)

  56. Sowmiya, S., Valarmathi, K., Sathyavenkateshwaren, S., Gobinath, M., Thillaisivakavi, S.: Snag detection robot for visually impaired steering and blind individuals. In: 2018 International Conference on Inventive Research in Computing Applications (ICIRCA), pp. 167–171. IEEE (2018)

  57. Reda, M.M., Mohammed, N.G., Seoud, R.A.A.A.A.: Svbicomm: sign-voice bidirectional communication system for normal,“deaf/dumb” and blind people based on machine learning. In: 2018 1st International Conference on Computer Applications & Information Security (ICCAIS), pp. 1–8. IEEE (2018)

  58. Wahidin, H., Waycott, J., Baker, S.: The challenges in adopting assistive technologies in the workplace for people with visual impairments. In: Proceedings of the 30th Australian Conference on Computer–Human Interaction, pp. 432–442 (2018)

  59. Ahmed, T., Kapadia, A., Potluri, V., Swaminathan, M.: Up to a limit? Privacy concerns of bystanders and their willingness to share additional information with visually impaired users of assistive technologies. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 2(3), pp. 1–27 (2018)

  60. Chang, W.-J., Yu, Y.-X., Chen, J.-H., Zhang, Z.-Y., Ko, S.-J., Yang, T.-H., Hsu, C.-H., Chen, L.-B., Chen, M.-C.: A deep learning based wearable medicines recognition system for visually impaired people. In: 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), pp. 207–208. IEEE (2019)

  61. Vasanth, K., Macharla, M., Varatharajan, R.: A self assistive device for deaf & blind people using iot. J. Med. Syst. 43(4), 1–8 (2019)

    Article  Google Scholar 

  62. Lin, W.-J., Su, M.-C., Cheng, W.-Y., Cheng, W.-Y.: An assist system for visually impaired at indoor residential environment using faster-rcnn. In: 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI), pp. 1071–1072. IEEE (2019)

  63. Croce, D., Giarre, L., Pascucci, F., Tinnirello, I., Galioto, G.E., Garlisi, D., Valvo, A.L.: An indoor and outdoor navigation system for visually impaired people. IEEE Access 7, 170406–170418 (2019)

    Article  Google Scholar 

  64. Noman, M., Shehieb, W., Sharif, T.: Assistive technology for integrating the visually-impaired in mainstream education and society. In: 2019 Advances in Science and Engineering Technology International Conferences (ASET), pp. 1–5. IEEE (2019)

  65. Nasralla, M.M., Rehman, I.U., Sobnath, D., Paiva, S.: Computer vision and deep learning-enabled uavs: proposed use cases for visually impaired people in a smart city. In: International Conference on Computer Analysis of Images and Patterns, pp. 91–99. Springer (2019)

  66. Shekhar, S., Chhokra, A., Sun, H., Gokhale, A., Dubey, A., Koutsokos, X.: Supporting fog/edge-based cognitive assistance iot services for the visually impaired. In: Proceedings of the International Conference on Internet of Things Design and Implementation, pp. 275–276 (2019)

  67. Mascetti, S., Ahmetovic, D., Bernareggi, C.: Research to market transition of mobile assistive technologies for people with visual impairments. In: The 21st International ACM SIGACCESS Conference on Computers and Accessibility, pp. 440–445 (2019)

  68. Grewe, L., Stevenson, G.: Seeing eye drone: a deep learning, vision-based uav for assisting the visually impaired with mobility. In: Proceedings of the ACM Turing Celebration Conference-China, pp. 1–5 (2019)

  69. Alghamdi, S.: Shop** and tourism for blind people using rfid as an application of iot. In: 2019 2nd International Conference on Computer Applications & Information Security (ICCAIS), pp. 1–4. IEEE (2019)

  70. Salat, S., Habib, M.A.: Smart electronic cane for the assistance of visually impaired people. In: 2019 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), pp. 1–4. IEEE (2019)

  71. Rai, A., Maurya, A., Ranjan, A., Gupta, R., et al.: Smart traveler-for visually impaired people. In: International Conference on Information Management & Machine Intelligence, pp. 653–662. Springer (2019)

  72. Kose, U., Vasant, P.: Better campus life for visually impaired university students: intelligent social walking system with beacon and assistive technologies. Wirel. Netw. 26(7), 4789–4803 (2020)

    Article  Google Scholar 

  73. Son, H., Krishnagiri, D., Jeganathan, V.S., Weiland, J.: Crosswalk guidance system for the blind. In: 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 3327–3330. IEEE (2020)

  74. Mahida, P., Shahrestani, S., Cheung, H.: Deep learning-based positioning of visually impaired people in indoor environments. Sensors 20(21), 6238 (2020)

    Article  Google Scholar 

  75. Sarkar, T., Patel, A., Arjunan, S.P.: Design and development of a smart eye wearable for the visually impaired. In: International Conference on Information, Communication and Computing Technology, pp. 208–221. Springer (2020)

  76. Shafique, K., Khawaja, B.A., Sabir, F., Qazi, S., Mustaqim, M.: Internet of things (iot) for next-generation smart systems: a review of current challenges, future trends and prospects for emerging 5g-iot scenarios. IEEE Access 8, 23022–23040 (2020)

    Article  Google Scholar 

  77. Chang, W.-J., Chen, L.-B., Hsu, C.-H., Chen, J.-H., Yang, T.-C., Lin, C.-P.: Medglasses: a wearable smart-glasses-based drug pill recognition system using deep learning for visually impaired chronic patients. IEEE Access 8, 17013–17024 (2020)

    Article  Google Scholar 

  78. Khan, M., Khan, D., Bazai, S., Ahmed, S., Khan, H., Ejaz, N.: ullah n (2020) motion based smart assistant for visually impaired people. Indian J. Sci. Technol. 13(16), 1612–1618 (2020)

    Article  Google Scholar 

  79. Khairnar, D.P., Karad, R.B., Kapse, A., Kale, G., Jadhav, P.: Partha: a visually impaired assistance system. In: 2020 3rd International Conference on Communication System, Computing and IT Applications (CSCITA), pp. 32–37. IEEE (2020)

  80. Connier, J., Zhou, H., De Vaulx, C., Li, J.-J., Shi, H., Vaslin, P., Hou, K.M.: Perception assistance for the visually impaired through smart objects: concept, implementation, and experiment scenario. IEEE Access 8, 46931–46945 (2020)

    Article  Google Scholar 

  81. Akter, T., Ahmed, T., Kapadia, A., Swaminathan, S.M.: Privacy considerations of the visually impaired with camera based assistive technologies: misrepresentation, impropriety, and fairness. In: The 22nd International ACM SIGACCESS Conference on Computers and Accessibility, pp. 1–14 (2020)

  82. Terreran, M., Tramontano, A.G., Lock, J.C., Ghidoni, S., Bellotto, N.: Real-time object detection using deep learning for hel** people with visual impairments. In: 2020 IEEE 4th International Conference on Image Processing, Applications and Systems (IPAS), pp. 89–95. IEEE (2020)

  83. Lin, J.-Y., Chiang, C.-L., Wu, M.-J., Yao, C.-C., Chen, M.-C.: Smart glasses application system for visually impaired people based on deep learning. In: 2020 Indo-Taiwan 2nd International Conference on Computing, Analytics and Networks (Indo-Taiwan ICAN), pp. 202–206. IEEE (2020)

  84. Al-Haider, A.J., Al-Sharshani, S.M., Al-Sheraim, H.S., Subramanian, N., Al-Maadeed, S., Chaari, M.: Smart medicine planner for visually impaired people. In: 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT), pp. 361–366. IEEE (2020)

  85. Gamal, O., Thakkar, S., Roth, H.: Towards intelligent assistive system for visually impaired people: outdoor navigation system. In: 2020 24th International Conference on System Theory, Control and Computing (ICSTCC), pp. 390–397. IEEE (2020)

  86. Poornima, J., Vishnupriyan, J., Vijayadhasan, G.K., Ettappan, M.: Voice assisted smart vision stick for visually impaired. Int. J. Control Autom. 13(2), 512–519 (2020)

    Google Scholar 

  87. Rao, S.U., Ranganath, S., Ashwin, T., Reddy, G.R.M., et al.: A google glass based real-time scene analysis for the visually impaired. IEEE Access 9, 166351–166369 (2021)

    Article  Google Scholar 

  88. Wang, Z., Li, H., Chen, J., Chai, X., Zhai, Z.: A wearable vision-to-audio sensory substitution system based on deep learning for the visually impaired. In: 2021 International Conference on Digital Society and Intelligent Systems (DSInS), pp. 283–286. IEEE (2021)

  89. Khan, A., Khusro, S.: An insight into smartphone-based assistive solutions for visually impaired and blind people: issues, challenges and opportunities. Univ. Access Inf. Soc. 20(2), 265–298 (2021)

    Article  Google Scholar 

  90. Rodrigo-Salazar, L., González-Carrasco, I., Garcia-Ramirez, A.R.: An iot-based contribution to improve mobility of the visually impaired in smart cities. Computing 103(6), 1233–1254 (2021)

    Article  Google Scholar 

  91. Parikh, N., Shah, I., Vahora, S.: Android smartphone based visual object recognition for visually impaired using deep learning. In: 2018 International Conference on Communication and Signal Processing (ICCSP), pp. 0420–0425. IEEE (2018)

  92. Beingolea, J.R., Zea-Vargas, M.A., Huallpa, R., Vilca, X., Bolivar, R., Rendulich, J.: Assistive devices: technology development for the visually impaired. Designs 5(4), 75 (2021)

    Article  Google Scholar 

  93. Mejía, P., Martini, L.C., Grijalva, F., Zambrano, A.M.: Casvi: computer algebra system aimed at visually impaired people. experiments. IEEE Access 9, 157021–157034 (2021)

    Article  Google Scholar 

  94. Rao, S., Singh, V.M.: Computer vision and iot based smart system for visually impaired people. In: 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence), pp. 552–556. IEEE (2021)

  95. Mohamed, E., Sirlantzis, K., Howells, G.: Indoor/outdoor semantic segmentation using deep learning for visually impaired wheelchair users. IEEE Access 9, 147914–147932 (2021)

    Article  Google Scholar 

  96. Kanna, S.B., Kumar, T.G., Niranjan, C., Prashanth, S., Gini, J.R., Harikumar, M.: Low cost smart navigation system for the blind. In: 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), vol. 1, pp. 466–471. IEEE (2021)

  97. Abdel-Jaber, H., Albazar, H., Abdel-Wahab, A., El Amir, M., Alqahtani, A., Alobaid, M.: Mobile based iot solution for hel** visual impairment users. Adv. Internet Things 11(4), 141–152 (2021)

    Article  Google Scholar 

  98. Denić, D., Aleksov, P., Vučković, I.: Object recognition with machine learning for people with visual impairment. In: 2021 15th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS), pp. 389–392. IEEE (2021)

  99. Kumar, P., Inchara, K., Lekhashree, S., Likhith, C., Pavan, U.: Real time assistive shoe for visually impaired people. In: 2021 6th International Conference for Convergence in Technology (I2CT), pp. 1–5. IEEE (2021)

  100. Mukhiddinov, M., Cho, J.: Smart glass system using deep learning for the blind and visually impaired. Electronics 10(22), 2756 (2021)

    Article  Google Scholar 

  101. Rahman, M.W., Tashfia, S.S., Islam, R., Hasan, M.M., Sultan, S.I., Mia, S., Rahman, M.M.: The architectural design of smart blind assistant using iot with deep learning paradigm. Internet Things 13, 100344 (2021)

    Article  Google Scholar 

  102. Kuriakose, B., Shrestha, R., Eika Sandnes, F.: Towards independent navigation with visual impairment: a prototype of a deep learning and smartphone-based assistant. In: The 14th PErvasive Technologies Related to Assistive Environments Conference, pp. 113–114 (2021)

  103. Oliveira, J.D.: Using interactive agents to provide daily living assistance for visually impaired people. Master’s thesis, Pontifícia Universidade Católica do Rio Grande do Sul (2021)

  104. Saha, S., Shakal, F.H., Mahmood, M.: Visual, navigation and communication aid for visually impaired person. Int. J. Electr. Comput. Eng. 11(2), 1276 (2021)

    Google Scholar 

  105. Pachodiwale, Z.A., Brahmankar, Y., Parakh, N., Patel, D., Eirinaki, M.: Viva: a virtual assistant for the visually impaired. In: International Conference on Human–Computer Interaction, pp. 444–460. Springer (2021)

  106. Hudec, M., Smutny, Z.: Ambient intelligence system enabling people with blindness to develop electrotechnical components and their drivers. IEEE Access 10, 8539–8565 (2022)

    Article  Google Scholar 

  107. Ashiq, F., Asif, M., Ahmad, M.B., Zafar, S., Masood, K., Mahmood, T., Mahmood, M.T., Lee, I.H.: Cnn-based object recognition and tracking system to assist visually impaired people. IEEE Access 10, 14819–14834 (2022)

    Article  Google Scholar 

  108. Mallikarjuna, G.C., Hajare, R., Pavan, P.: Cognitive iot system for visually impaired: machine learning approach. Mater. Today Proc. 49, 529–535 (2022)

    Article  Google Scholar 

  109. Durgadevi, S., Komathi, C., Thirupurusundari, K., Haresh, S., Harishanker, A.: Iot based assistive system for visually impaired and aged people. In: 2022 2nd International Conference on Power Electronics & IoT Applications in Renewable Energy and Its Control (PARC), pp. 1–4. IEEE (2022)

  110. Wang, X., Calderon, J., Khoshavi, N., Jaimes, L.G.: Path and floor detection in outdoor environments for fall prevention of the visually impaired population. In: 2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), pp. 1–6. IEEE (2022)

  111. Masud, U., Saeed, T., Malaikah, H.M., Islam, F.U., Abbas, G.: Smart assistive system for visually impaired people obstruction avoidance through object detection and classification. IEEE Access 10, 13428–13441 (2022)

    Article  Google Scholar 

  112. Yang, Z., Yang, L., Kong, L., Wei, A., Leaman, J., Brooks, J., Li, B.: Seeway: vision-language assistive navigation for the visually impaired. In: 2022 IEEE International Conference on Systems, Man, and Cybernetics, pp. 52–58 (2022). https://doi.org/10.1109/SMC53654.2022.9945087

  113. Ntakolia, C., Dimas, G., Iakovidis, D.: User-centered system design for assisted navigation of visually impaired individuals in outdoor cultural environments. Univers. Access Inf. Soc. 21, 1–26 (2022). https://doi.org/10.1007/s10209-020-00764-1

    Article  Google Scholar 

  114. López, A.F., Ohmura, R.: Public transport guiding system for visually impaired users easy to deploy, maintain and extend. In: 2022 IEEE International Smart Cities Conference (ISC2), pp. 1–7 (2022). https://doi.org/10.1109/ISC255366.2022.9922280

  115. Roy, T., Boppana, L.: Interactive web-based image and graph analysis using sonification for the blind. In: 2022 IEEE Region 10 Symposium (TENSYMP), pp. 1–6 (2022). https://doi.org/10.1109/TENSYMP54529.2022.9864411

  116. Fathi, K., Darvishy, A., Venn, H.W.: Augmented reality for the visually impaired: navigation aid and scene semantics for indoor use cases. In: 2022 IEEE 12th International Conference on Consumer Electronics (ICCE-Berlin), pp. 1–6 (2022). https://doi.org/10.1109/ICCE-Berlin56473.2022.9937109

  117. Huang, C.-Y., Wu, C.-K., Liu, P.-Y.: Assistive technology in smart cities: a case of street crossing for the visually-impaired. Technol. Soc. 68, 101805 (2022). https://doi.org/10.1016/j.techsoc.2021.101805

    Article  Google Scholar 

  118. Feitl, S., Kreimeier, J., Götzelmann, T.: Accessible electrostatic surface haptics: towards an interactive audiotactile map interface for people with visual impairments. In: ND, pp. 522–531. Association for Computing Machinery, New York, NY, USA (2022). https://doi.org/10.1145/3529190.3534781

  119. Rana, L., Rehman, A.U., Javaid, S., Ali, T.M.: A novel model-driven approach for visual impaired people assistance optic ally. In: 2022 Third International Conference on Latest Trends in Electrical Engineering and Computing Technologies (INTELLECT), pp. 1–8 (2022). https://doi.org/10.1109/INTELLECT55495.2022.9969400

  120. Ahmed, E., Yaqoob, I., Gani, A., 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)

    Article  Google Scholar 

Download references

Funding

The authors did not receive support from any organization for the submitted work.

Author information

Author notes

  1. Rosemary Francisco, João Elison da Rosa Tavares and Jorge Luis Victória Barbosa have contributed equally to this work.

Authors and Affiliations

  1. Applied Computing Graduate Program (PPGCA), University of Vale do Rio dos Sinos (UNISINOS), Unisinos Avenue, 950, São Leopoldo, RS, 93022-750, Brazil

    Leandro Rossetti de Souza, João Elison da Rosa Tavares & Jorge Luis Victória Barbosa

  2. Unisinos Business School, University of Vale do Rio dos Sinos (UNISINOS), Unisinos Avenue, 950, São Leopoldo, RS, 93022-750, Brazil

    Rosemary Francisco

Authors
  1. Leandro Rossetti de Souza
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rosemary Francisco
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. João Elison da Rosa Tavares
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jorge Luis Victória Barbosa
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

R. F. This author contributed equally to this work. J. E. R. T.: This author contributed equally to this work. J. L. V. B.: This author contributed equally to this work.

Corresponding author

Correspondence to Leandro Rossetti de Souza.

Ethics declarations

Conflict of interest

The authors have no Conflict of interest to declare that are relevant to the content of this article.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Souza, L.R.d., Francisco, R., Rosa Tavares, J.E.d. et al. Intelligent environments and assistive technologies for assisting visually impaired people: a systematic literature review. Univ Access Inf Soc (2024). https://doi.org/10.1007/s10209-024-01117-y

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10209-024-01117-y

Keywords

Search

Navigation