Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
184 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Odor-Based Molecular Communications: State-of-the-Art, Vision, Challenges, and Frontier Directions (2311.17727v1)

Published 29 Nov 2023 in eess.SP, cs.SY, and eess.SY

Abstract: Humankind mimics the processes and strategies that nature has perfected and uses them as a model to address its problems. That has recently found a new direction, i.e., a novel communication technology called molecular communication (MC), using molecules to encode, transmit, and receive information. Despite extensive research, an innate MC method with plenty of natural instances, i.e., olfactory or odor communication, has not yet been studied with the tools of information and communication technologies (ICT). Existing studies focus on digitizing this sense and developing actuators without inspecting the principles of odor-based information coding and MC, which significantly limits its application potential. Hence, there is a need to focus cross-disciplinary research efforts to reveal the fundamentals of this unconventional communication modality from an ICT perspective. The ways of natural odor MC in nature need to be anatomized and engineered for end-to-end communication among humans and human-made things to enable several multi-sense augmented reality technologies reinforced with olfactory senses for novel applications and solutions in the Internet of Everything (IoE). This paper introduces the concept of odor-based molecular communication (OMC) and provides a comprehensive examination of olfactory systems. It explores odor communication in nature, including aspects of odor information, channels, reception, spatial perception, and cognitive functions. Additionally, a comprehensive comparison of various communication systems sets the foundation for further investigation. By highlighting the unique characteristics, advantages, and potential applications of OMC through this comparative analysis, the paper lays the groundwork for exploring the modeling of an end-to-end OMC channel, considering the design of OMC transmitters and receivers, and developing innovative OMC techniques.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (178)
  1. J. Wang, J. Erkoyuncu, and R. Roy, “A conceptual design for smell based augmented reality: case study in maintenance diagnosis,” Procedia CIRP, vol. 78, pp. 109–114, 2018.
  2. K. C. Persaud, S. Marco, and A. Gutierrez-Galvez, “Neuromorphic olfaction,” 2013.
  3. J. K. Wilson, A. Kessler, and H. A. Woods, “Noisy communication via airborne infochemicals,” BioScience, vol. 65, no. 7, pp. 667–677, 2015.
  4. C. E. Shannon, “A mathematical theory of communication,” The Bell system technical journal, vol. 27, no. 3, pp. 379–423, 1948.
  5. [Online]. Available: https://psynso.com/olfaction/
  6. K. C. Persaud, S. Marco, and A. Gutiérrez-Gálvez, “Engineering aspects of olfaction,” Neuromorphic olfaction, pp. 1–58, 2013.
  7. C. Qin et al., “Artificial olfactory biohybrid system: An evolving sense of smell,” Advanced Science, vol. 10, no. 5, p. 2204726, 2023.
  8. O. Technology, “The primary smells,” Oct 2020, accessed on May 4, 2023. [Online]. Available: https://www.olorama.com/the-primary-smells
  9. I. Manzini, D. Schild, and C. Di Natale, “Principles of odor coding in vertebrates and artificial chemosensory systems,” Physiological reviews, vol. 102, no. 1, pp. 61–154, 2022.
  10. L. B. Buck, “Unraveling the sense of smell,” Les Prix Nobel. The Nobel Prizes, vol. 2004, pp. 267–283, 2004.
  11. B. Patnaik, A. Batch, and N. Elmqvist, “Information olfactation: Harnessing scent to convey data,” IEEE transactions on visualization and computer graphics, vol. 25, no. 1, pp. 726–736, 2018.
  12. A. D. Cheok et al., “Digital smell interface,” Virtual Taste and Smell Technologies For Multisensory Internet and Virtual Reality, pp. 93–117, 2018.
  13. B. Malnic et al., “Combinatorial receptor codes for odors,” Cell, vol. 96, no. 5, pp. 713–723, 1999.
  14. V. Jamali et al., “Olfaction-inspired mcs: Molecule mixture shift keying and cross-reactive receptor arrays,” IEEE Transactions on Communications, vol. 71, no. 4, pp. 1894–1911, 2023.
  15. K. J. Albert et al., “Cross-reactive chemical sensor arrays,” Chemical reviews, vol. 100, no. 7, pp. 2595–2626, 2000.
  16. R. Menzel and U. Greggers, “The memory structure of navigation in honeybees,” Journal of Comparative Physiology A, vol. 201, pp. 547–561, 2015.
  17. X. Bao et al., “Grid-like neural representations support olfactory navigation of a two-dimensional odor space,” Neuron, vol. 102, no. 5, pp. 1066–1075, 2019.
  18. W. Fischler-Ruiz, “Olfactory landmarks and path integration converge to form a cognitive spatial map,” Neuron, 2019.
  19. D. Malak and O. B. Akan, “Molecular communication nanonetworks inside human body,” Nano Communication Networks, vol. 3, no. 1, pp. 19–35, 2012. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S187877891100055X
  20. M. Pierobon and I. F. Akyildiz, “A physical end-to-end model for molecular communication in nanonetworks,” IEEE Journal on Selected Areas in Communications, vol. 28, no. 4, pp. 602–611, 2010.
  21. T. Suda et al., “Exploratory research on molecular communication between nanomachines,” in Genetic and Evolutionary Computation Conference (GECCO), Late Breaking Papers, vol. 25.   Citeseer, 2005, p. 29.
  22. B. Atakan, O. B. Akan, and S. Balasubramaniam, “Body area nanonetworks with molecular communications in nanomedicine,” IEEE Communications Magazine, vol. 50, no. 1, pp. 28–34, 2012.
  23. O. B. Akan et al., “Fundamentals of molecular information and communication science,” Proceedings of the IEEE, vol. 105, no. 2, pp. 306–318, 2017.
  24. B. Atakan and O. B. Akan, “An information theoretical approach for molecular communication,” in 2007 2nd Bio-Inspired Models of Network, Information and Computing Systems, 2007, pp. 33–40.
  25. T. Nakano et al., “Molecular communication and networking: Opportunities and challenges,” IEEE Transactions on NanoBioscience, vol. 11, no. 2, pp. 135–148, 2012.
  26. N. Farsad et al., “A comprehensive survey of recent advancements in molecular communication,” IEEE Communications Surveys & Tutorials, vol. 18, no. 3, pp. 1887–1919, 2016.
  27. S. Hiyama et al., “Molecular communication,” Journal-Institute of Electronics Information and Communication Engineers, vol. 89, no. 2, p. 162, 2006.
  28. G. R. Semin et al., “Inter-and intra-species communication of emotion: chemosignals as the neglected medium,” Animals, vol. 9, no. 11, p. 887, 2019.
  29. M. H. Ferkin, “Odor communication and mate choice in rodents,” Biology, vol. 7, no. 1, p. 13, 2018.
  30. V. O. Ezenwa and A. E. Williams, “Microbes and animal olfactory communication: where do we go from here?” BioEssays, vol. 36, no. 9, pp. 847–854, 2014.
  31. A. Jürgens and M. Bischoff, “Changing odour landscapes: the effect of anthropogenic volatile pollutants on plant–pollinator olfactory communication,” Functional Ecology, vol. 31, no. 1, pp. 56–64, 2017.
  32. S. C. Roberts, J. Havlíček, and B. Schaal, “Human olfactory communication: current challenges and future prospects,” Philosophical Transactions of the Royal Society B, vol. 375, no. 1800, p. 20190258, 2020.
  33. A. J. Carthey, M. R. Gillings, and D. T. Blumstein, “The extended genotype: microbially mediated olfactory communication,” Trends in Ecology & Evolution, vol. 33, no. 11, pp. 885–894, 2018.
  34. J. A. Covington et al., “Artificial olfaction in the 21 st century,” IEEE Sensors Journal, vol. 21, no. 11, pp. 12 969–12 990, 2021.
  35. N. Ranasinghe et al., “Digital taste and smell communication,” in 6th International ICST Conference on Body Area Networks, 2012.
  36. “Digitizing the chemical senses: Possibilities & pitfalls,” International Journal of Human-Computer Studies, vol. 107, pp. 62–74, 2017.
  37. J. Gutiérrez and M. C. Horrillo, “Advances in artificial olfaction: Sensors and applications,” Talanta, vol. 124, pp. 95–105, 2014.
  38. C. Kim et al., “Artificial olfactory sensor technology that mimics the olfactory mechanism: A comprehensive review,” Biomaterials Research, vol. 26, no. 1, pp. 1–13, 2022.
  39. B. Guthrie, “Machine olfaction,” Springer Handbook of Odor, pp. 55–56, 2017.
  40. S. Marco and A. Gutierrez-Galvez, “Signal and data processing for machine olfaction and chemical sensing: A review,” IEEE Sensors Journal, vol. 12, no. 11, pp. 3189–3214, 2012.
  41. D. Harel, L. Carmel, and D. Lancet, “Towards an odor communication system,” Computational Biology and Chemistry, vol. 27, no. 2, pp. 121–133, 2003.
  42. D. T. McGuiness et al., “Parameter analysis in macro-scale molecular communications using advection-diffusion,” IEEE Access, vol. 6, pp. 46 706–46 717, 2018.
  43. S. Giannoukos et al., “A chemical alphabet for macromolecular communications,” Analytical chemistry, vol. 90, no. 12, pp. 7739–7746, 2018.
  44. S. Giannoukos et al., “Molecular communication over gas stream channels using portable mass spectrometry,” J. Am. Soc. Mass Spectrom., vol. 28, no. 11, pp. 2371–2383, 2017.
  45. D. T. McGuiness et al., “Asymmetrical inter-symbol interference in macro-scale molecular communications,” in Proceedings of the 5th ACM International Conference on Nanoscale Computing and Communication, 2018, pp. 1–6.
  46. M. Kuscu et al., “Transmitter and receiver architectures for molecular communications: A survey on physical design with modulation, coding, and detection techniques,” Proceedings of the IEEE, vol. 107, no. 7, pp. 1302–1341, 2019.
  47. J. J. Kaye, “Making scents: aromatic output for hci,” interactions, vol. 11, no. 1, pp. 48–61, 2004.
  48. D. T. McGuiness et al., “Experimental and analytical analysis of macro-scale molecular communications within closed boundaries,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 5, no. 1, pp. 44–55, 2019.
  49. P. Szyszka et al., “The speed of smell: odor-object segregation within milliseconds,” PloS one, vol. 7, no. 4, p. e36096, 2012.
  50. R. Prasad, “Human bond communication,” Wireless Personal Communications, vol. 87, pp. 619–627, 2016.
  51. R. Stocker, “Drosophila as a focus in olfactory research: Mapping of olfactory sensilla by fine structure, odor specificity, odorant receptor expression, and central connectivity,” Microscopy Research and Technique, 2001.
  52. J. Liu, “Classical olfactory conditioning in the oriental fruit fly, bactrocera dorsalis,” PLoS ONE, 2015.
  53. P. Masek, “Drosophila fatty acid taste signals through the plc pathway in sugar-sensing neurons,” PLoS Genetics, 2013.
  54. H. Spors, “Spatio-temporal dynamics of odor representations in the mammalian olfactory bulb,” Neuron, 2002.
  55. B. M. Wenzel, “Olfactory bulb ablation or nerve section and behavior of pigeons in nonolfactory learning.” Experimental neurology, 1968.
  56. I. Bell, “An olfactory-limbic model of multiple chemical sensitivity syndrome: Possible relationships to kindling and affective spectrum disorders,” Biological Psychiatry, 1992.
  57. O. B. Akan et al., “Internet of everything (ioe) - from molecules to the universe,” IEEE Communications Magazine, pp. 1–7, 2023.
  58. N. Farsad, W. Guo, and A. W. Eckford, “Tabletop molecular communication: Text messages through chemical signals,” PloS one, vol. 8, no. 12, p. e82935, 2013.
  59. H. Unterweger et al., “Experimental molecular communication testbed based on magnetic nanoparticles in duct flow,” in IEEE SPAWC, 2018, pp. 1–5.
  60. C. Kiparissides et al., “A computational systems approach to rational design of nose-to-brain delivery of biopharmaceutics,” Industrial & Engineering Chemistry Research, vol. 59, no. 6, pp. 2548–2565, 2019.
  61. S. Gänger and K. Schindowski, “Tailoring formulations for intranasal nose-to-brain delivery: A review on architecture, physico-chemical characteristics and mucociliary clearance of the nasal olfactory mucosa,” Pharmaceutics, vol. 10, no. 3, 2018. [Online]. Available: https://www.mdpi.com/1999-4923/10/3/116
  62. D. Choi et al., “Bioelectrical nose platform using odorant-binding protein as a molecular transporter mimicking human mucosa for direct gas sensing,” ACS sensors, vol. 7, no. 11, pp. 3399–3408, 2022.
  63. X. Guo et al., “Strong and tough fibrous hydrogels reinforced by multiscale hierarchical structures with multimechanisms,” Science Advances, vol. 9, no. 2, p. eadf7075, 2023.
  64. U. Tisch and H. Haick, “Nanomaterials for cross-reactive sensor arrays,” MRS Bulletin, vol. 35, no. 10, p. 797–803, 2010.
  65. C. Fan et al., “Monolithic three-dimensional integration of carbon nanotube circuits and sensors for smart sensing chips,” ACS nano, 2023.
  66. C. Koca et al., “Molecular communication theoretical modeling and analysis of sars-cov2 transmission in human respiratory system,” IEEE Trans. Mol. Biol. Multi-Scale Commun., vol. 7, no. 3, pp. 153–164, 2021.
  67. A. Sharma et al., “Sense of smell: structural, functional, mechanistic advancements and challenges in human olfactory research,” Current neuropharmacology, vol. 17, no. 9, pp. 891–911, 2019.
  68. N.-R. Kim et al., “A universal channel model for molecular communication systems with metal-oxide detectors,” in 2015 IEEE International Conference on Communications (ICC).   IEEE, 2015, pp. 1054–1059.
  69. N.-R. Kim et al., “An experimentally validated channel model for molecular communication systems,” IEEE Access, vol. 7, pp. 81 849–81 858, 2019.
  70. S. Niedenthal, “A handheld olfactory display for smell-enabled vr games,” 2019 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN), 2019.
  71. M. Civas and O. B. Akan, “Molecular communication transmitter architectures for the internet of bio-nano things,” in 2022 International Balkan Conference on Communications and Networking (BalkanCom), 2022, pp. 132–136.
  72. M. Civas et al., “Graphene and related materials for the internet of bio-nano things,” arXiv preprint arXiv:2304.03824, 2023.
  73. M. Civas and O. B. Akan, “Molecular communication transmitter architectures for the internet of bio-nano things,” in 2022 International Balkan Conference on Communications and Networking (BalkanCom).   IEEE, 2022, pp. 132–136.
  74. C. K. Nguyen et al., “Biocompatible nanomaterials based on dendrimers, hydrogels and hydrogel nanocomposites for use in biomedicine,” Advances in Natural Sciences: Nanoscience and Nanotechnology, vol. 8, no. 1, p. 015001, 2017.
  75. M. Bartunik et al., “Novel receiver for superparamagnetic iron oxide nanoparticles in a molecular communication setting,” in Proceedings of the Sixth Annual ACM International Conference on Nanoscale Computing and Communication, 2019, pp. 1–6.
  76. D. T. McGuiness et al., “Experimental results on the open-air transmission of macro-molecular communication using membrane inlet mass spectrometry,” IEEE Communications Letters, vol. 22, no. 12, pp. 2567–2570, 2018.
  77. D. T. McGuiness et al., “Modulation analysis in macro-molecular communications,” IEEE Access, vol. 7, pp. 11 049–11 065, 2019.
  78. B.-H. Koo et al., “Molecular mimo: From theory to prototype,” IEEE Journal on Selected Areas in Communications, vol. 34, no. 3, pp. 600–614, 2016.
  79. M. Kuscu and O. B. Akan, “Modeling and analysis of sinw biofet as molecular antenna for bio-cyber interfaces towards the internet of bio-nanothings,” in 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT), 2015, pp. 669–674.
  80. M. Kuscu et al., “Fabrication and microfluidic analysis of graphene-based molecular communication receiver for internet of nano things (iont),” Scientific reports, vol. 11, no. 1, p. 19600, 2021.
  81. M. Kuscu and O. B. Akan, “On the physical design of molecular communication receiver based on nanoscale biosensors,” IEEE Sensors Journal, vol. 16, no. 8, pp. 2228–2243, 2016.
  82. D. Aktas and O. B. Akan, “Weight shift keying (wsk) with practical mechanical receivers for molecular communications in internet of everything,” IEEE Journal on Selected Areas in Communications, vol. 40, no. 11, pp. 3285–3294, 2022.
  83. D. Aktas and O. B. Akan, “A mechanical transduction-based molecular communication receiver for internet of nano things (iont).”   New York, NY, USA: Association for Computing Machinery, 2021. [Online]. Available: https://doi.org/10.1145/3477206.3477453
  84. B. D. Unluturk, A. O. Bicen, and I. F. Akyildiz, “Genetically engineered bacteria-based biotransceivers for molecular communication,” IEEE Transactions on Communications, vol. 63, no. 4, pp. 1271–1281, 2015.
  85. T. Nakano et al., “Molecular communication among biological nanomachines: A layered architecture and research issues,” IEEE transactions on nanobioscience, vol. 13, no. 3, pp. 169–197, 2014.
  86. T. Khan et al., “Nanosensor networks for smart health care,” in Nanosensors for Smart Cities.   Elsevier, 2020, pp. 387–403.
  87. S. Li, “Recent developments in human odor detection technologies,” Journal of Forensic Science & Criminology, vol. 1, no. 1, pp. 1–12, 2014.
  88. B. R. Goldsmith et al., “Biomimetic chemical sensors using nanoelectronic readout of olfactory receptor proteins,” ACS nano, vol. 5, no. 7, pp. 5408–5416, 2011.
  89. H. J. Jin et al., “Nanovesicle-based bioelectronic nose platform mimicking human olfactory signal transduction,” Biosensors and Bioelectronics, vol. 35, no. 1, pp. 335–341, 2012.
  90. Z. Gao et al., “An artificial olfactory system with sensing, memory and self-protection capabilities,” Nano Energy, vol. 86, p. 106078, 2021.
  91. M. M. Shulaker et al., “Three-dimensional integration of nanotechnologies for computing and data storage on a single chip,” Nature, vol. 547, no. 7661, pp. 74–78, 2017.
  92. F. Zhou and Y. Chai, “Near-sensor and in-sensor computing,” Nature Electronics, vol. 3, no. 11, pp. 664–671, 2020.
  93. S. H. Lee et al., “Bioelectronic nose combined with a microfluidic system for the detection of gaseous trimethylamine,” Biosensors and Bioelectronics, vol. 71, pp. 179–185, 2015.
  94. G. Rebordão, S. I. Palma, and A. C. Roque, “Microfluidics in gas sensing and artificial olfaction,” Sensors, vol. 20, no. 20, p. 5742, 2020.
  95. M. Whitfield, “An electronic nose function realised by laser-induced graphitization of polyimide,” PhD thesis, University of Cambridge, March 2022.
  96. A. Smolinska, “Profiling of volatile organic compounds in exhaled breath as a strategy to find early predictive signatures of asthma in children,” PLoS ONE, vol. 9, p. 4, 2014.
  97. L. Ling, “Research progress of volatile organic compounds produced by plant endophytic bacteria in control of postharvest diseases of fruits and vegetables,” World Journal of Microbiology and Biotechnology, vol. 39, p. 149, 2023.
  98. G. Ghinea and O. A. Ademoye, “Olfaction-enhanced multimedia: perspectives and challenges,” Multimedia Tools and Applications, vol. 55, pp. 601–626, 2011.
  99. M. Chastrette, “Classification of odors and structure-odor relationships,” Olfaction, taste, and cognition, pp. 100–116, 2002.
  100. B. K. Lee et al., “A principal odor map unifies diverse tasks in human olfactory perception,” BioRxiv, pp. 2022–09, 2022.
  101. A. Sharma et al., “Olfactionbase: a repository to explore odors, odorants, olfactory receptors and odorant–receptor interactions,” Nucleic Acids Research, vol. 50, no. D1, pp. D678–D686, 2022.
  102. Z. Ye, Y. Liu, and Q. Li, “Recent progress in smart electronic nose technologies enabled with machine learning methods,” Sensors, vol. 21, no. 22, p. 7620, 2021.
  103. T. Zarra et al., “Instrumental odour monitoring system classification performance optimization by analysis of different pattern-recognition and feature extraction techniques,” Sensors, vol. 21, no. 1, p. 114, 2020.
  104. J. Yan et al., “Electronic nose feature extraction methods: A review,” Sensors, vol. 15, no. 11, pp. 27 804–27 831, 2015.
  105. H. Xu et al., “Determination of quasi-primary odors by endpoint detection,” Scientific Reports, vol. 11, no. 1, p. 12070, 2021.
  106. A. Vanarse et al., “Application of a brain-inspired spiking neural network architecture to odor data classification,” Sensors, vol. 20, no. 10, 2020. [Online]. Available: https://www.mdpi.com/1424-8220/20/10/2756
  107. T. Wen et al., “An odor labeling convolutional encoder–decoder for odor sensing in machine olfaction,” Sensors, vol. 21, no. 2, 2021. [Online]. Available: https://www.mdpi.com/1424-8220/21/2/388
  108. T. Aguilera et al., “Electronic nose based on independent component analysis combined with partial least squares and artificial neural networks for wine prediction,” Sensors, vol. 12, no. 6, pp. 8055–8072, 2012.
  109. L. Zhang et al., “Classification of multiple indoor air contaminants by an electronic nose and a hybrid support vector machine,” Sensors and Actuators B: Chemical, vol. 174, pp. 114–125, 2012.
  110. M. Meister, “On the dimensionality of odor space,” Elife, vol. 4, p. e07865, 2015.
  111. T. Weiss, “Perceptual convergence of multi-component mixtures in olfaction implies an olfactory white,” Proceedings of the National Academy of Sciences, 2012.
  112. S. M. Kurian et al., “Odor coding in the mammalian olfactory epithelium,” Cell and Tissue Research, vol. 383, no. 1, pp. 445–456, 2021.
  113. W. Wicke et al., “Pulse shaping for mc via particle size,” arXiv preprint arXiv:2201.06425, 2022.
  114. D. T. McGuiness et al., “Analysis of multi-chemical transmission in the macro-scale,” IEEE Trans. Mol. Biol. Multi-Scale Commun., vol. 6, no. 2, pp. 93–106, 2020.
  115. M. Kuscu and O. B. Akan, “Detection in molecular communications with ligand receptors under molecular interference,” Digital Signal Processing, vol. 124, p. 103186, 2022.
  116. G. Muzio, M. Kuscu, and O. B. Akan, “Selective signal detection with ligand receptors under interference in molecular communications,” in 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2018, pp. 1–5.
  117. M. Kuscu and O. B. Akan, “Maximum likelihood detection with ligand receptors for diffusion-based molecular communications in internet of bio-nano things,” IEEE Transactions on NanoBioscience, vol. 17, no. 1, pp. 44–54, 2018.
  118. B. Li et al., “Csi-independent non-linear signal detection in molecular communications,” IEEE Transactions on Signal Processing, vol. 68, pp. 97–112, 2019.
  119. D. Kilinc and O. B. Akan, “Receiver design for molecular communication,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 12, pp. 705–714, 2013.
  120. M. Civas, M. Kuscu, and O. B. Akan, “Frequency-domain detection for molecular communication with cross-reactive receptors,” 2023.
  121. W. Liu, Jiang, “Analysis of gas leakage early warning system based on kalman filter and optimized bp neural network,” IEEE Access, vol. 8, no. 1, pp. 175 180–175 193, 2020.
  122. “Neural kalman filtering,” Preprint, 2021.
  123. A. Goknil et al., “A systematic review of data quality in cps and iot for industry 4.0,” ACM Comput. Surv., vol. 55, no. 14s, jul 2023. [Online]. Available: https://doi.org/10.1145/3593043
  124. I. R. Luján, J. F. Magrinyà, and R. Huerta, “Machine learning methods in electronic nose analysis,” 2016. [Online]. Available: https://api.semanticscholar.org/CorpusID:65611019
  125. R. D. Hoehn et al., “Status of the vibrational theory of olfaction,” Frontiers in Physics, vol. 6, p. 25, 2018.
  126. M. Genva et al., “Is it possible to predict the odor of a molecule on the basis of its structure?” International journal of molecular sciences, vol. 20, no. 12, p. 3018, 2019.
  127. B. D. Young, “Smelling molecular structure,” in Perception, Cognition and Aesthetics.   Routledge, 2019, pp. 64–84.
  128. M. Khalid et al., “Communication through breath: Aerosol transmission,” IEEE Communications Magazine, vol. 57, no. 2, pp. 33–39, 2019.
  129. W. Xu et al., “Guest editorial: Task-oriented communications for future wireless networks,” IEEE Wireless Communications, vol. 30, no. 3, pp. 16–17, 2023.
  130. M. Alja’Afreh, “A qoe model for digital twin systems in the era of the tactile internet,” Ph.D. dissertation, Université d’Ottawa/University of Ottawa, 2021.
  131. S. R. Gulliver and G. Ghinea, “Defining user perception of distributed multimedia quality,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 2, no. 4, pp. 241–257, 2006.
  132. Y. Ruan et al., “Olfactory dysfunctions in neurodegenerative disorders,” Journal of neuroscience research, vol. 90, no. 9, pp. 1693–1700, 2012.
  133. J. Attems, L. Walker, and K. A. Jellinger, “Olfactory bulb involvement in neurodegenerative diseases,” Acta neuropathologica, vol. 127, pp. 459–475, 2014.
  134. X. Dan et al., “Loss of smelling is an early marker of aging and is associated with inflammation and dna damage in c57bl/6j mice,” Aging Cell, vol. 22, no. 4, p. e13793, 2023.
  135. S. Naaz et al., “Odortam: technology acceptance model for biometric authentication system using human body odor,” International Journal of Environmental Research and Public Health, vol. 19, no. 24, p. 16777, 2022.
  136. C. Hurot et al., “Bio-inspired strategies for improving the selectivity and sensitivity of artificial noses: A review,” Sensors, vol. 20, no. 6, p. 1803, 2020.
  137. A. J. Barbosa, A. R. Oliveira, and A. C. Roque, “Protein-and peptide-based biosensors in artificial olfaction,” Trends in biotechnology, vol. 36, no. 12, pp. 1244–1258, 2018.
  138. S. Thangaleela et al., “Nasal microbiota, olfactory health, neurological disorders and aging—a review,” Microorganisms, vol. 10, no. 7, p. 1405, 2022.
  139. R. L. Doty, “Olfactory dysfunction in parkinson disease,” Nature Reviews Neurology, vol. 8, no. 6, pp. 329–339, 2012.
  140. M. Naudin and B. Atanasova, “Olfactory markers of depression and alzheimer’s disease,” Neuroscience & Biobehavioral Reviews, vol. 45, pp. 262–270, 2014.
  141. K. D. Suh et al., “Olfactory function test for early diagnosis of vascular dementia,” Korean Journal of Family Medicine, vol. 41, no. 3, p. 202, 2020.
  142. E. O. Blenke et al., “Crispr-cas9 gene editing: Delivery aspects and therapeutic potential,” Journal of Controlled Release, vol. 244, pp. 139–148, 2016.
  143. M. Mustapha and C. N. M. Taib, “Mptp-induced mouse model of parkinson’s disease: A promising direction for therapeutic strategies,” Bosnian journal of basic medical sciences, vol. 21, no. 4, p. 422, 2021.
  144. M. B. Genter and R. L. Doty, “Toxic exposures and the senses of taste and smell,” Handbook of Clinical Neurology, vol. 164, pp. 389–408, 2019.
  145. R. K. Dismukes, “New concepts of molecular communication among neurons,” Behavioral and Brain Sciences, vol. 2, no. 3, pp. 409–416, 1979.
  146. L. Felicetti et al., “Applications of molecular communications to medicine: A survey,” Nano Communication Networks, vol. 7, pp. 27–45, 2016.
  147. Y. Chahibi, “Molecular communication for drug delivery systems: A survey,” Nano Communication Networks, vol. 11, pp. 90–102, 2017.
  148. Y. Chahibi, “Molecular communication for drug delivery systems: A survey,” Nano Communication Networks, vol. 11, pp. 90–102, 2017. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S1878778917300054
  149. D. Malak and O. B. Akan, “Communication theoretical understanding of intra-body nervous nanonetworks,” IEEE Communications Magazine, vol. 52, no. 4, pp. 129–135, 2014.
  150. M. T. Barros et al., “Molecular communications in viral infections research: Modeling, experimental data, and future directions,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 7, no. 3, pp. 121–141, 2021.
  151. A. Etemadi et al., “Abnormality detection and localization schemes using molecular communication systems: A survey,” IEEE Access, vol. 11, pp. 1761–1792, 2023.
  152. Y. Cevallos et al., “Health applications based on molecular communications: a brief review,” in 2019 IEEE International Conference on E-health Networking, Application & Services (HealthCom).   IEEE, 2019, pp. 1–6.
  153. I. F. Akyildiz et al., “Microbiome-gut-brain axis as a biomolecular communication network for the internet of bio-nanothings,” IEEE access, vol. 7, pp. 136 161–136 175, 2019.
  154. S. Zafar et al., “A systematic review of bio-cyber interface technologies and security issues for internet of bio-nano things,” IEEE Access, vol. 9, pp. 93 529–93 566, 2021.
  155. A. El-Fatyany, H. Wang, and S. M. Abd El-atty, “On mixing reservoir targeted drug delivery modeling-based internet of bio-nanothings,” Wireless Networks, vol. 26, pp. 3701–3713, 2020.
  156. O. B. Akan et al., “Information and communication theoretical understanding and treatment of spinal cord injuries: State-of-the-art and research challenges,” IEEE Reviews in Biomedical Engineering, vol. 16, pp. 332–347, 2023.
  157. I. F. Akyildiz et al., “The internet of bio-nano things,” IEEE Communications Magazine, vol. 53, no. 3, pp. 32–40, 2015.
  158. I. Croy, “Test-retest reliability and validity of the sniffin’ tom odor memory test.” Chemical senses, 2015.
  159. K. Kollndorfer, “Assessment of olfactory memory in olfactory dysfunction,” Perception, 2017.
  160. S. Vaglio, “Chemical communication and mother-infant recognition,” Communicative & Integrative Biology, vol. 2, pp. 279–281, 2009.
  161. S. Gelstein, “Human tears contain a chemosignal,” Science, vol. 1331, pp. 226–230, 2011.
  162. A. A. Bailey and P. L. Hurd, “Finger length ratio (2d:4d) correlates with physical aggression in men but not in women,” Biological Psychology, vol. 68, pp. 215–222, 2005.
  163. J. Balthazart, “Fraternal birth order effect on sexual orientation explained,” Proceedings of the National Academy of Sciences, vol. 115, pp. 234–236, 2018.
  164. A. Sorokowska, “Human leukocyte antigen similarity decreases partners’ and strangers’ body odor attractiveness for women not using hormonal contraception,” Hormonal Behaviours, vol. 106, pp. 144–149, 2018.
  165. O. Troisi, M. Kashef, and A. Visvizi, “Managing safety and security in the smart city: Covid-19, emergencies and smart surveillance,” in Managing Smart Cities: Sustainability and Resilience Through Effective Management.   Springer, 2022, pp. 73–88.
  166. J. Full et al., “Market perspectives and future fields of application of odor detection biosensors within the biological transformation‚Äîa systematic analysis,” Biosensors, vol. 11, no. 3, 2021. [Online]. Available: https://www.mdpi.com/2079-6374/11/3/93
  167. J. K. Olofsson et al., “Beyond smell-o-vision: Possibilities for smell-based digital media,” Simulation & Gaming, vol. 48, no. 4, pp. 455–479, 2017.
  168. N. I. of Food and Agriculture, “Researchers helping protect crops from pests — national institute of food and agriculture,” 2023, http://www.nifa.usda.gov/about-nifa/blogs/researchers-helping-protect-crops-pests [Accessed: (Jul. 07, 2023)].
  169. A. Satake, “Pollen coupling of forest trees: forming synchronized and periodic reproduction out of chaos,” J Theor Biol, vol. 2, pp. 63–84, 2000.
  170. T. D. Toth, “Engineering plant-microbe communication for synthetic symbioses,” PhD thesis, Massachusetts Institute of Technology, June 2022.
  171. N. Ranasinghe and E. Y.-L. Do, “Digital lollipop: Studying electrical stimulation on the human tongue to simulate taste sensations,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 13, no. 1, pp. 1–22, 2016.
  172. S. Mumtaz, “Guest editorial 5g tactile internet: An application for industrial automation,” IEEE Trans. Ind. Informatics, 2019.
  173. G. P. Fettweis, “The tactile internet: Applications and challenges,” IEEE vehicular technology magazine, vol. 9, no. 1, pp. 64–70, 2014.
  174. M. Civas et al., “Universal transceivers: Opportunities and future directions for the internet of everything (ioe),” Frontiers in Communications and Networks, vol. 2, p. 733664, 2021.
  175. A. U. F. Beyond, “Internet of everything,” Harnessing the Internet of Everything (IoE) for Accelerated Innovation Opportunities, p. 1, 2019.
  176. Q. Mou et al., “Efficient delivery of a dna aptamer-based biosensor into plant cells for glucose sensing through thiol-mediated uptake,” Science Advances, vol. 8, no. 26, p. eabo0902, 2022.
  177. T. A. Dixon, T. C. Williams, and I. S. Pretorius, “Sensing the future of bio-informational engineering,” Nature Communications, vol. 12, no. 1, p. 388, 2021.
  178. N. Saeed, T. Y. Al-Naffouri, and M.-S. Alouini, “Climate monitoring using internet of x-things,” arXiv preprint arXiv:2006.00231, 2020.
Citations (2)
View on Semantic Scholar

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now