Skip to main content
SpringerLink
Log in

User oriented smart connected product and smart environment: a systematic literature review

  • Critical Review
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

Smart Connected Product(SCP) and Smart Environment(SE), typical product-service integrated system under intelligent manufacturing context, have attracted significant attentions from both researchers and practitioners owning to its effectiveness in enabling user interaction and improving user satisfaction. In this paper, we conduct a systematical literature review to summarize the current user-oriented SCP or SE researches. A totally 102 journal articles are fully analyzed to illustrate the current research concentration and highlight future research directions. Different from existing review articles that focus on specific SCP or SE, our research incorporates diverse SCPs or SEs and proposes an objective-based taxonomy, which distinguishes three objective dimensions, that is, integrated optimization within system, vertically iterative optimization of the system and the horizontally collaborative optimization between systems. Besides, we distill five user-oriented indictors, that is, user need identification, user interaction optimization, serve special group, user security protection as well as energy consumption improvement and combine them with three research objectives to unveil the mainstream research concentration. Finally, we summarize the research gap of existing works and propose seven future research directions for scholars and practitioners.

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

Access this article

Log in via an institution

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
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Meyer GG, Främling K, Holmström J (2009) Intelligent products: a survey. Comput Ind 60(3):137–148

    Google Scholar 

  2. Porter ME, Heppelmann JE (2014) How smart, connected products are transforming competition. Harv Bus Rev 92(11):64–88

    Google Scholar 

  3. Jin X, Yu S, Zheng P, Liu Q, Xun X (2018) Cloud-based approach for smart product personalization. Procedia CIRP 72:922–927

    Google Scholar 

  4. Zhang H, Qin S, Li R, Zou YS, Ding GF (2020) Environment interaction model-driven smart products through-life design framework. Int J Comput Integr Manuf 33(4):360–376

    Google Scholar 

  5. Zhou T, Chen Z, Cao Y, Miao R, Ming XG (2022) An integrated framework of user experience-oriented smart service requirement analysis for smart product service system development. Adv Eng Inform 51:101458

    Google Scholar 

  6. Gaba GS, Kumar G, Monga H, King T, Kumar P (2020) Robust and lightweight mutual authentication scheme in distributed smart environments. IEEE Access 8:69722–69733

    Google Scholar 

  7. Cicirelli F, Fortino G, Guerrieri A, Spezzano G, Vinci A (2017) Metamodeling of smart environments: from design to implementation. Adv Eng Inform 33:274–284

    Google Scholar 

  8. Gu W, Liu S, Zhang Z, Li Y (2022) A distributed physical architecture and data-based scheduling method for smart factory based on intelligent agents. J Manuf Syst 65:785–801

    Google Scholar 

  9. Panchatcharam P, Vivekanandan S (2019) Internet of things (IOT) in healthcare-smart health and surveillance, architectures, security analysis and data transfer: a review. Int J Softw Innov 7(2):21–40

    Google Scholar 

  10. Ardolino M, Rapaccini M, Saccani N, Gaiardelli P, Crespi G, Ruggeri C (2018) The role of digital technologies for the service transformation of industrial companies. Int J Prod Res 56(6):2116–2132

    Google Scholar 

  11. Zhang Y, Ren S, Liu Y, Si S (2017) A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products. J Clean Prod 142:626–641

    Google Scholar 

  12. Zheng P, Liu Y, Tao F, Chen CH (2019) Smart product-service systems solution design via hybrid crowd sensing approach. IEEE Access 7:128463–128473

    Google Scholar 

  13. Chan A, Cohen R, Robinson KM, Bhardwaj D, Gregson G, Jutai JW, Millar J, Rincón AR, Fekr AR (2022) Evidence and user considerations of home health monitoring for older adults: scoping review. JMIR Aging 5(4):e40079

    Google Scholar 

  14. Li Z, Zhang J, Li M, Huang J, Wang X (2020) A review of smart design based on interactive experience in building systems. Sustainability 12(17):6760

    Google Scholar 

  15. Ellavarason E, Guest R, Deravi F, Sanchez-Riello R, Corsetti B (2020) Touch-dynamics based behavioural biometrics on mobile devices-a review from a usability and performance perspective. ACM Comput Surv 53(6):1–36

    Google Scholar 

  16. Rus-Calafell M, Schneider S (2020) Are we there yet?!-a literature review of recent digital technology advances for the treatment of early psychosis. Mhealth 6

  17. França C, Santos F, Martins F, Lopes H, Gouveia B, Gonçalves F, Campos P, Marques A, Ihle A, Gonçalves T, Gouveia ÉR (2022) Digital health in schools: a systematic review. Sustainability 14(21):13848

    Google Scholar 

  18. Spanakis EG, Santana S, Tsiknakis M, Marias K, Sakkalis V, Teixeira A, Janssen JH, Jong HD, Tziraki C (2016) Technology-based innovations to foster personalized healthy lifestyles and well-being: a targeted review. J Med Internet Res 18(6):e4863

    Google Scholar 

  19. Real S, Araujo A (2019) Navigation systems for the blind and visually impaired: past work, challenges, and open problems. Sensors 19(15):3404

    Google Scholar 

  20. Meredith J (1993) Theory building through conceptual methods. Int J Oper Prod Manage 13(5):3–11

    Google Scholar 

  21. Mayring P (2004) Qualitative content analysis. Companion Qual Res 1(2):159–176

    Google Scholar 

  22. Yadav VS, Singh AR, Raut RD, Mangla SK, Luthra S, Kumar A (2022) Exploring the application of Industry 4.0 technologies in the agricultural food supply chain: a systematic literature review. Comput Ind Eng 108304

  23. Ghadimi P, Wang C, Lim MK (2019) Sustainable supply chain modeling and analysis: past debate, present problems and future challenges. Resour Conserv Recycl 140:72–84

    Google Scholar 

  24. Smart P, Hemel S, Lettice F, Adams R, Evans S (2017) Pre-paradigmatic status of industrial sustainability: a systematic review. Int J Oper Prod Manage 37(10):1425–1450

    Google Scholar 

  25. Sassanelli C, Rosa P, Terzi S (2021) Supporting disassembly processes through simulation tools: a systematic literature review with a focus on printed circuit boards. J Manuf Syst 60:429– 448

  26. Yadav VS, Singh AR, Gunasekaran A, Raut RD, Narkhede BE (2022) A systematic literature review of the agro-food supply chain: challenges, network design, and performance measurement perspectives. Sustain Prod Consump 29:685–704

    Google Scholar 

  27. Wang W, Wei T, Zhang Y, Wang Y (2019) A method of intelligent product design cue construction based on customer touchpoint correlation analysis and positive creativity theory. Adv Mech Eng 11(1):1687814018819347

    Google Scholar 

  28. Du Y, Liu D, Duan H (2022) A textual data-driven method to identify and prioritise user preferences based on regret/rejoicing perception for smart and connected products. Int J Prod Res 60(13):4176–4196

    Google Scholar 

  29. Zheng P, Xu X, Chen CH (2020) A data-driven cyber-physical approach for personalised smart, connected product co-development in a cloud-based environment. J Intell Manuf 31(1):3–18

    Google Scholar 

  30. Zheng P, Lin Y, Chen CH, Xu X (2019) Smart, connected open architecture product: an IT-driven co-creation paradigm with lifecycle personalization concerns. Int J Prod Res 57(8):2571–2584

    Google Scholar 

  31. Zhang X, Ming X (2022) Comprehensive understanding of smart product service system from multi-dimension and multi-perspective: an innovative service model for Customer-product Interaction Life Cycle (CILC). Adv Eng Inform 52:101619

    Google Scholar 

  32. Bu L, Chen CH, Zhang G, Liu B, Dong G, Yuan X (2020) A hybrid intelligence approach for sustainable service innovation of smart and connected product: a case study. Adv Eng Inform 46:101163

    Google Scholar 

  33. Gouin-Vallerand C, Abdulrazak B, Giroux S, Dey AK (2013) A context-aware service provision system for smart environments based on the user interaction modalities. J Ambient Intell Smart Environ 5(1):47–64

    Google Scholar 

  34. Yachir A, Amirat Y, Chibani A, Badache N (2015) Event-aware framework for dynamic services discovery and selection in the context of ambient intelligence and Internet of Things. IEEE Trans Autom Sci Eng 13(1):85–102

    Google Scholar 

  35. Gullà F, Menghi R, Papetti A, Carulli M, Bordegoni M, Gaggioli A, Germani M (2019) Prototyping adaptive systems in smart environments using virtual reality. Int J Interact Des Manuf 13:597–616

    Google Scholar 

  36. Iqbal MZ, Campbell AG (2021) From luxury to necessity: progress of touchless interaction technology. Technol Soc 67:101796

    Google Scholar 

  37. Jung ES, Im Y (2015) Touchable area: an empirical study on design approach considering perception size and touch input behavior. Int J Ind Ergon 49:21–30

    Google Scholar 

  38. Fierrez J, Pozo A, Martinez-Diaz M, Galbally J, Morales A (2018) Benchmarking touchscreen biometrics for mobile authentication. IEEE Trans Inf Forensic Secur 13(11):2720–2733

    Google Scholar 

  39. Teo KR, BT B, Zhou J, Chen JM (2021) Categorizing touch-input locations from touchscreen device interfaces via on-board mechano-acoustic transducers. Appl Sci-Basel 11(11):4834

  40. Wang X, Liu A, Kara S (2022) Machine learning for engineering design toward smart customization: a systematic review. J Manuf Syst 65:391–405

    Google Scholar 

  41. Liu Y, Feng T, Peng M, Jiang Z, Xu Z, Guan J (2020) COMP: online control mechanism for profit maximization in privacy-preserving crowdsensing. IEEE J Sel Areas Commun 38(7):1614–1628

    Google Scholar 

  42. Li Q, Cao G (2015) Providing privacy-aware incentives in mobile sensing systems. IEEE Trans Mob Comput 15(6):1485–1498

    Google Scholar 

  43. Park E (2020) User acceptance of smart wearable devices: an expectation-confirmation model approach. Telemat Inform 47:101318

    Google Scholar 

  44. Lee H (2020) A study on the development of a user-focused multi-functional convergence-smart-fashion product. Heliyon 6(1):e03130

    Google Scholar 

  45. Lin KY, Chien CF, Kerh R (2016) UNISON framework of data-driven innovation for extracting user experience of product design of wearable devices. Comput Ind Eng 99:487–502

    Google Scholar 

  46. Yoon H, Park SH, Lee KT (2016) Lightful user interaction on smart wearables. Pers Ubiquit Comput 20:973–984

    Google Scholar 

  47. Kerber F, Gehring S, Krüger A, Löchtefeld M (2017) Adding expressiveness to smartwatch notifications through ambient illumination. Int J Hum Comput Int 9(4):1–14

    Google Scholar 

  48. Paay J, Kjeldskov J, Aaen I, Bank M (2022) User-centred iterative design of a smartwatch system supporting spontaneous reminiscence therapy for people living with dementia. Health Inform J 28(2):14604582221106002

    Google Scholar 

  49. Celic L, Magjarevic R (2020) Seamless connectivity architecture and methods for IoT and wearable devices. Automatika 61(1):21–34

    Google Scholar 

  50. Liu D, Chen J, Deng Q, Konate A, Tian Z (2017) Secure pairing with wearable devices by using ambient sound and light. Wuhan Univ J Nat Sci 22(4):329–336

    Google Scholar 

  51. Imbesi S, Corzani M, Lopane G, Mincolelli G, Chiari L (2022) User-centered design methodologies for the prototype development of a smart harness and related system to provide haptic cues to persons with parkinson’s disease. Sensors 22(21):8095

    Google Scholar 

  52. Mazilu S, Blanke ULF, Dorfman M, Gazit E, Mirelman A, Hausdorff JM, Tröster G (2015) A wearable assistant for gait training for Parkinson’s disease with freezing of gait in out-of-the-lab environments. ACM Trans Interact Intell Syst 5(1):1–31

    Google Scholar 

  53. Mahesh PCS, Hemalatha S (2022) An efficient android malware detection using adaptive red fox optimization based CNN. Wirel Pers Commun 126(1):679–700

    Google Scholar 

  54. Alani MM (2017) Android users privacy awareness survey. Int J Inter Mob Tec 11(3)

  55. Wang H, He H, Song C, Tang H, Sun Y, Qiao Y, Zhang W (2022) Who is using the phone? representation-learning-based continuous authentication on smartphones. Secu Commun Netw 6339407

  56. Yan X, Zhang J, Elahi H, Jiang M, Gao H (2021) A personalized search query generating method for safety-enhanced vehicle-to-people networks. IEEE Trans Veh Technol 70(6):5296–5307

    Google Scholar 

  57. YK L, CG K (2012) An enhanced touch event processing on Android. IEICE Electron Express 9(6):509–514

    Google Scholar 

  58. Guo J, Wang L (2022) Application of style transfer algorithm in interactive art design of mobile phone interface. Mob Inf Syst 7469090

  59. Lin YD, Chu ETH, Chang E, Lai YC (2017) Smoothed graphic user interaction on smartphones with motion prediction. IEEE Trans Syst Man Cybern-Syst 50(4):1429–1441

    Google Scholar 

  60. Nam C, Shin DR (2018) Force-touch measurement methodology based on user experience. Int J Distrib Sens Netw 14(4):1550147718767794

    Google Scholar 

  61. Kim T, Jung ES, Im Y (2014) Optimal control location for the customer-oriented design of smart phones. Inf Sci 257:264– 275

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

    Google Scholar 

  63. Kim HK, Han SH, Park J, Park J (2016) The interaction experiences of visually impaired people with assistive technology: a case study of smartphones. Int J Ind Ergon 55:22–33

    Google Scholar 

  64. Belimpasakis P, Walsh R (2011) A combined mixed reality and networked home approach to improving user interaction with consumer electronics. IEEE Trans Consum Electron 57(1):139– 144

  65. Frank JA, Brill A, Kapila V (2016) Mounted smartphones as measurement and control platforms for motor-based laboratory test-beds. Sensors 16(8):1331

    Google Scholar 

  66. Ahmed D (2021) Anthropomorphizing artificial intelligence: towards a user-centered approach for addressing the challenges of over-automation and design understandability in smart homes. Intell Build Int 13(4):227–240

    MathSciNet  Google Scholar 

  67. Cho Y, Choi A (2020) Application of affordance factors for user-centered smart homes: a case study approach. Sustainability 12(7):3053

    Google Scholar 

  68. Palanca J, Val E, Garcia-Fornes A, Billhardt H, Corchado JM, Julián V (2018) Designing a goal-oriented smart-home environment. Inf Syst Front 20:125–142

    Google Scholar 

  69. Wobbrock JO, Morris MR, Wilson AD (2009) User-defined gestures for surface computing. In: Proceedings of the SIGCHI conference on human factors in computing systems pp 1083–1092

  70. Kühnel C, Westermann T, Hemmert F, Kratz S, Müller A, Möller S (2011) I’m home: Defining and evaluating a gesture set for smart-home control. Int J Hum-Comput Stud 69(11):693–704

    Google Scholar 

  71. Nijholt A, Zwiers J, Peciva J (2009) Mixed reality participants in smart meeting rooms and smart home environments. Pers Ubiquitous Comput 13:85–94

    Google Scholar 

  72. Rashid KM, Louis J, Fiawoyife KK (2019) Wireless electric appliance control for smart buildings using indoor location tracking and BIM-based virtual environments. Autom Constr 101:48–58

    Google Scholar 

  73. Wu CL, Fu LC (2011) Design and realization of a framework for human-system interaction in smart homes. IEEE Trans Syst Man Cybern Paart A-Syst Hum 42(1):15–31

    Google Scholar 

  74. Bissoli A, Lavino-Junior D, Sime M, Encarnação L, Bastos-Filho T (2019) A human-machine interface based on eye tracking for controlling and monitoring a smart home using the internet of things. Sensors 19(4):859

    Google Scholar 

  75. Blasco R, Marco Á, Casas R, Cirujano D, Picking R (2014) A smart kitchen for ambient assisted living. Sensors 14(1):1629–1653

    Google Scholar 

  76. Borelli E, Paolini G, Antoniazzi F, Barbiroli M, Benassi F, Chesani F, Chiari L, Fantini M, Fuschini F, Galassi A, Giacobone GA, Imbesi S, Licciardello M, Loreti D, Marchi M, Masotti D, Mello P, Mellone S, Mincolelli G, Raffaelli C, Roffia L, Cinotti TS, Tacconi C, Tamburini P, Zoli M, Costanzo A (2019) HABITAT: an IoT solution for independent elderly. Sensors 19(5): 1258

  77. Johnson DO, Cuijpers RH, Juola JF, Torta E, Simonov M, Frisiello A, Bazzani M, Yan W, Weber C, Wermter S, Meins N, Oberzaucher J, Panek P, Edelmayer G, Mayer P, Beck C (2014) Socially assistive robots: a comprehensive approach to extending independent living. Int J Soc Robot 6:195–211

    Google Scholar 

  78. Orpwood R, Gibbs C, Adlam T, Faulkner R, Meegahawatte D (2005) The design of smart homes for people with dementia–user-interface aspects. Universal Access Inf 4:156–164

    Google Scholar 

  79. Tiersen F, Batey P, Harrison MJC, Naar L, Serban AI, Daniels SJC, Calvo RA (2021) Smart home sensing and monitoring in households with dementia: user-centered design approach. JMIR Aging 4(3):e27047

    Google Scholar 

  80. Zhu S, Xu Z, Dong Y, Xiong N, Wang Y (2022) What will the future kitchen look like? an exploratory laboratory study of the future expectations of Chinese Generation Z. Int J Ind Ergon 87:103259

    Google Scholar 

  81. Ali S, Rehman AU, Wadud Z, Khan I, Murawwat S, Hafeez G, Albogamy FR, Khan S, Samuel O (2022) Demand response program for efficient demand-side management in smart grid considering renewable energy sources. IEEE Access 10:53832–53853

    Google Scholar 

  82. Dashtaki AA, Khaki M, Zand M, Nasab MA, Sanjeevikumar P, Samavat T, Nasab MA, Khan B (2022) A day ahead electrical appliance planning of residential units in a smart home network using ITS-BF algorithm. Int T Electr Energy 2549887

  83. Kim MJ, Cho ME, Jun HJ (2020) Developing design solutions for smart homes through user-centered scenarios. Front Psychol 11:335

    Google Scholar 

  84. Seo DW, Kim H, Kim JS, Lee JY (2016) Hybrid reality-based user experience and evaluation of a context-aware smart home. Comput Ind 76:11–23

    Google Scholar 

  85. Rashidi P, Cook DJ (2009) Keeping the resident in the loop: adapting the smart home to the user. IEEE Trans Syst Man Cybern Paart A-Syst Hum 39(5):949–959

    Google Scholar 

  86. Reisinger MR, Prost S, Schrammel J, Fröhlich P (2019) User requirements for the design of smart homes: dimensions and goals. Ambient Intelligence: 15th European Conference 41-57

  87. Wu C, Aghajan H (2010) User-centric environment discovery with camera networks in smart homes. IEEE Trans Syst Man Cybern Paart A-Syst Hum 41(2):375–383

    Google Scholar 

  88. Lertlakkhanakul J, Choi JW, Kim MY (2008) Building data model and simulation platform for spatial interaction management in smart home. Automat Constr 17(8):948–957

    Google Scholar 

  89. Yener B, Taşcıkaraoğlu A, Erdinç O, Baysal M, Catalão JPS (2017) Design and implementation of an interactive interface for demand response and home energy management applications. Appl Sci-Basel 7(6):641

    Google Scholar 

  90. Zimmermann V, Gerber P, Marky K, Böck L, Kirchbuchner F (2019) Assessing users’ privacy and security concerns of smart home technologies. I-com 18(3):197–216

    Google Scholar 

  91. Subahi A, Theodorakopoulos G (2019) Detecting IoT user behavior and sensitive information in encrypted IoT-app traffic. Sensors 19(21):4777

    Google Scholar 

  92. Hayashi VT, Ruggiero WV (2022) Hands-free authentication for virtual assistants with trusted IoT device and machine learning. Sensors 22(4):1325

    Google Scholar 

  93. Cobb C, Bhagavatula S, Garrett KA, Hoffman A, Rao V, Bauer L (2021) I would have to evaluate their objections: privacy tensions between smart home device owners and incidental users. Proc Priv Enh Technol 4:54–75

  94. Heartfield R, Loukas G, Bezemskij A, Bezemskij A, Panaousis E (2020) Self-configurable cyber-physical intrusion detection for smart homes using reinforcement learning. IEEE Trans Inf Forensic Secur 16:1720–1735

    Google Scholar 

  95. Hjorth TS, Torbensen R (2012) Trusted domain: a security platform for home automation. Comput Secur 1(8):940–955

    Google Scholar 

  96. Mangini AM, Roccotelli M, Rinaldi A (2021) A novel application based on a heuristic approach for planning itineraries of one-day tourist. Appl Sci-Basel 11(19):8989

    Google Scholar 

  97. García GC, Ruiz IL, Gómez-Nieto MÁ (2017) Tailored platform for the development of NFC tourist services. J Ambient Intell Smart Environ 9(4):501–520

    Google Scholar 

  98. Zhou WW (2022) Building an urban smart community system based on association rule algorithms. Secur Commun Netw 8773259

  99. Yuan Y, Huh JH (2018) A case study analysis of clothing shopping mall for customer design participation service and development of customer editing user interface. Mob Inf Syst 1–19

  100. Thakker D, Yang-Turner F, Despotakis D (2016) User interaction with linked data: an exploratory search approach. Int J Distrib Syst T 7(1):79–91

    Google Scholar 

  101. Zhang L, Chen S, Dong H, Saddik AE (2018) Visualizing Toronto city data with Hololens: using augmented reality for a city model. IEEE Consum Electron Mag 7(3):73–80

    Google Scholar 

  102. Preston S, Mazhar MU, Bull R (2020) Citizen engagement for co-creating low carbon smart cities: practical lessons from Nottingham City council in the UK. Energies 13(24):6615

    Google Scholar 

  103. Xu H, Zhu W (2021) Evaluating the impact mechanism of citizen participation on citizen satisfaction in a smart city. Env Plan B-Urban Anal City Sci 48(8):2466–2480

    MathSciNet  Google Scholar 

  104. Sauer S (2012) Do smart cities produce smart entrepreneurs? J Theor Appl Electron Commer Res 7(3):63–73

    Google Scholar 

  105. Simonofski A, Vallé T, Serral E, Wautelet Y (2021) Investigating context factors in citizen participation strategies: a comparative analysis of Swedish and Belgian smart cities. Int J Inf Manage 56:102011

    Google Scholar 

  106. An S, Kim S, Kim S (2020) Necessity of the needs map in the service design for smart cities. Front Psychol 11:202

    Google Scholar 

  107. Mutule A, Domingues M, Ulloa-Vásquez F, Carrizo D, García-Santander L, Dumitrescu AM, Issicaba D, Melo L (2021) Implementing smart city technologies to inspire change in consumer energy behaviour. Energies 14(14):4310

    Google Scholar 

  108. Schuurman D, Baccarne B, De Marez L, Mechant P (2012) Smart ideas for smart cities: investigating crowdsourcing for generating and selecting ideas for ICT innovation in a city context. J Theor Appl Electron Commer Res 7(3):49–62

    Google Scholar 

  109. Jeong YJ, Kim CW, Jeong SC (2015) The citizens’ acceptance factors to the ubiquitous services of U-city project. ICIC Expr Lett B Appl 6(3):791–796

    Google Scholar 

  110. Cavallo F, Limosani R, Fiorini L, Esposito R, Furferi R, Governi L, Carfagni M (2018) Design impact of acceptability and dependability in assisted living robotic applications. Int J Interact Des Manuf 12:1167–1178

    Google Scholar 

  111. Paliokas I, Tsoniotis N, Votis K, Tzovaras D (2019) A blockchain platform in connected medical-device environments: trustworthy technology to guard against cyberthreats. IEEE Consum Electron Mag 8(4):50–55

    Google Scholar 

  112. Wang Z, Cui L, Guo W, Zhao L, Yuan X, Gu X, Tang W, Bu L, Huang W (2022) A design method for an intelligent manufacturing and service system for rehabilitation assistive devices and special groups. Adv Eng Inform 51:101504

    Google Scholar 

  113. Bendig J, Wolf AS, Mark T, Frank A, Mathiebe J, Scheibe M, Mer G, Müller Stahr, Schmitt J, Reichmann H, Loewenbrück KF, Falkenburger BH (2022) Feasibility of a multimodal telemedical intervention for patients with Parkinson’s disease-a pilot study. J Clin Med 11(4):1074

    Google Scholar 

  114. Yoo S, Hwang H, Jheon S (2016) Hospital information systems: experience at the fully digitized Seoul National University Bundang Hospital. J Thorac Dis 8(Suppl 8):S637

    Google Scholar 

  115. Elagan SK, Abdelwahab SF, Zanaty EA, Alkinani MH, Alotaibi H, Zanaty MEA (2021) Remote diagnostic and detection of coronavirus disease (COVID-19) system based on intelligent healthcare and internet of things. Results Phys 22:103910

    Google Scholar 

  116. Poongodi M, Sharma A, Hamdi M, Maode M, Chilamkurti N (2021) Smart healthcare in smart cities: wireless patient monitoring system using IoT. J Supercomput 1–26

  117. Müllner R, Riener A (2011) An energy efficient pedestrian aware Smart Street Lighting system. Int J Pervasive Comp 7(2):147–161

    Google Scholar 

  118. Gao G, Jiang C, Chen T, Hui C, Wu L, Huang H (2018) An internet of vehicles system for remote monitoring and fault diagnosis of automobiles. J Automation Control Eng 6

  119. Kocsis M, Zöllner R, Mogan G (2022) Interactive system for package delivery in pedestrian areas using a self-developed fleet of autonomous vehicles. Electronics 11(5):748

    Google Scholar 

  120. Cao J, Lin L, Zhang J, Zhang L, Wang Y, Wang J (2021) The development and validation of the perceived safety of intelligent connected vehicles scale. Accident Anal Prev 154:106092

    Google Scholar 

  121. Li J, Dong Y, Fang S, Zhang H, Xu D (2020) User context detection for relay attack resistance in passive keyless entry and start system. Sensors 20(16):4446

    Google Scholar 

  122. He F, Ong SK, Nee AYC (2019) A mobile solution for augmenting a manufacturing environment with user-generated annotations. Information 10(2):60

    Google Scholar 

  123. Brunetti D, Gena C, Vernero F (2022) Smart interactive technologies in the human-centric factory 5.0: a survey. Appl Sci-Basel 12(16):7965

    Google Scholar 

  124. Kim H, Jang S, Jang J (2015) A study on development of engine fault diagnostic system. Math Probl Eng 271374

  125. Amjad Z, Shah MA, Maple C, Khattak HA, Ameer Z, Asghar MN, Mussadiq S (2020) Towards energy efficient smart grids using bio-inspired scheduling techniques. IEEE Access 8:158947–158960

    Google Scholar 

  126. Zhang J, Wang S, He W, Li J, Cao Z, Wei B (2022) Projected augmented reality assembly assistance system supporting multi-modal interaction. Int J Adv Manuf Tech 123(3–4):1353–1367

    Google Scholar 

  127. Tao Y, Guo S, Shi C, Chu D (2019) User behavior analysis by cross-domain log data fusion. IEEE Access 8:400–406

    Google Scholar 

  128. Liu J, Zhi Q, Ji H, Li B, Lei S (2021) Wheel hub customization with an interactive artificial immune algorithm. J Intell Manuf 32:1305–1322

    Google Scholar 

  129. Oksuz K, Cam BC, Kalkan S, Akbas E (2020) Imbalance problems in object detection: a review. IEEE T Pattern Anal 43(10):3388–3415

    Google Scholar 

  130. Manzil HHR, Naik SM (2023) Detection approaches for android malware: taxonomy and review analysis. Expert Syst Appl 238:122255

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 72271070, 71871076, 72001064), Natural Science Foundation of Anhui Province (Nos. 2208085J07, 2208085MG179, 2022AH051341), the Fundamental Research Funds for the Central Universities (Nos. JZ2022HGTB0303, JZ2022HGQA0128, JZ2022HGTA0354).

Author information

Authors and Affiliations

  1. School of Management, Hefei University of Technology, Hefei, Anhui, 230009, People’s Republic of China

    Lulu Xia, Kai Li, Tao Zhou, Limin Zhang & Weizhong Fu

  2. Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, Anhui, 230009, People’s Republic of China

    Kai Li

Authors
  1. Lulu Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kai Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tao Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Limin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Weizhong Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kai Li.

Ethics declarations

Conflicts of interest

The authors have no relevant financial or non-financial interests to disclose.

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

Xia, L., Li, K., Zhou, T. et al. User oriented smart connected product and smart environment: a systematic literature review. Int J Adv Manuf Technol 130, 1017–1038 (2024). https://doi.org/10.1007/s00170-023-12725-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-023-12725-y

Keywords

Search

Navigation