More Web Proxy on the site http://driver.im/

research-article

State-of-the-Art and Research Opportunities for Next-Generation Consumer Electronics

Authors:

Chi-Tsun Cheng,

Kim Fung TsangAuthors Info & Claims

IEEE Transactions on Consumer Electronics, Volume 69, Issue 4

Pages 937 - 948

https://doi.org/10.1109/TCE.2022.3232478

Published: 01 November 2023 Publication History

Abstract

The tremendous advancement of Internet-of-Things (IoT) has proliferated the interaction between the physical and cyber worlds. Consumer electronics, as the first tier in the physical world, would play a crucial role to enable ubiquitous information exchange. The adoption of IoT technologies will inevitably enhance the maturity of consumer products and services, proliferating the market of consumer electronics. Nonetheless, the ever-growing number of uncoordinated connections and unregulated integrations of technologies would pose various challenges and threats, resulting in vulnerability to consumer electronics. Thus, there is an urgent need for defining the trusted infrastructure and research directions for consumer electronics. In this paper, the next-generation (next-gen) consumer electronics would be defined for the first time. Also, the state-of-the-art architecture of next-gen consumer electronics would be presented, in compliance with the emerging IoT standard IEEE 2668. To address the underlying challenges in next-gen consumer electronics, this paper will classify the essential research topics for consumer electronics and present future research opportunities, such as the exploitation of complex network analysis, cybersecurity measures, etc., to foster the development of consumer electronics in a reliable, efficient, safe, and secure manner.

References

[1]

M. A. Kesselman and W. Esquivel, “Technology on the move, consumer electronics show 2022: The evolving metaverse and much more,” Library Hi Tech News, vol. 39, no. 5, pp. 1–4, 2022.

[2]

J. Li, X. Zeng, and A. Stevels, “Ecodesign in consumer electronics: Past, present, and future,” Crit. Rev. Environ. Sci. Technol., vol. 45, no. 8, pp. 840–860, 2015.

[3]

B. Markwalter, “The consumer technology market-past and present [CTA insights],” IEEE Consum. Electron. Mag., vol. 8, no. 2, p. 108, Mar. 2019.

[4]

23rd Annual U.S. Consumer Technology Ownership and Market Potential Study, Consum. Technol. Assoc., Hopewell, VA, USA, May 2021.

[5]

S. P. Mohanty and F. Pescador, “Introduction consumer technologies for smart healthcare,” IEEE Trans. Consum. Electron., vol. 67, no. 1, pp. 1–2, Feb. 2021.

[6]

C. K. Wuet al., “Supply chain of things: A connected solution to enhance supply chain productivity,” IEEE Commun. Mag., vol. 57, no. 8, pp. 78–83, Aug. 2019.

Digital Library

[7]

Y. Mahadik, M. Thakre, and S. Kamble, “Electric vehicle monitoring system based on Internet of Things (IoT) technologies,” in IoT and Analytics for Sensor Networks. Singapore: Springer, 2022, pp. 311–322.

[8]

M. S. Aliero, K. N. Qureshi, M. F. Pasha, and G. Jeon, “Smart home energy management systems in Internet of Things networks for green cities demands and services,” Environ. Technol. Innov., vol. 22, May 2021, Art. no.

[9]

M. S. B. A. Rahman, E. Mohamad, and A. A. B. A. Rahman, “Development of IoT—Enabled data analytics enhance decision support system for lean manufacturing process improvement,” Concurrent Eng., vol. 29, no. 3, pp. 208–220, 2021.

[10]

S. Muralidharan, B. Yoo, and H. Ko, “Decentralized ME-centric framework—A futuristic architecture for consumer IoT,” IEEE Consum. Electron. Mag., early access, Feb. 14, 2022. 10.1109/MCE.2022.3151023.

[11]

G. Wen, W. Yu, M. Z. Q. Chen, X. Yu, and G. Chen, “Pinning a complex network to follow a target system with predesigned control inputs,” IEEE Trans. Syst., Man, Cybern., Syst., vol. 50, no. 6, pp. 2293–2304, Jun. 2020.

[12]

Y.-Y. Liu, J.-J. Slotine, and A.-L. Barabási, “Controllability of complex networks,” Nature, vol. 473, no. 7346, pp. 167–173, 2011.

[13]

G. Chen, “Searching for best network topologies with optimal synchronizability: A brief review,” IEEE/CAA J. Automatica Sinica, vol. 9, no. 4, pp. 573–577, Apr. 2022.

[14]

G.-S. Peng and J. Wu, “Optimal network topology for structural robustness based on natural connectivity,” Physica A, Stat. Mech. Appl., vol. 443, pp. 212–220, Feb. 2016.

[15]

S. Wang, D. Li, J. Geng, Y. Gu, and Y. Cheng, “Impact of network topology on the performance of DML: Theoretical analysis and practical factors,” in Proc. IEEE INFOCOM Conf. Comput. Commun., 2019, pp. 1729–1737.

[16]

C. Onosé, “Designing for consumer trust in a data-powered world,” IEEE Consum. Electron. Mag., vol. 9, no. 2, pp. 89–93, Mar. 2020.

[17]

A. Banafa, Three Major Challenges Facing IoT, IEEE Internet Things, Piscataway, NJ, USA, 2017, pp. 26–67.

[18]

T. Alladi, V. Chamola, B. Sikdar, and K.-K. R. Choo, “Consumer IoT: Security vulnerability case studies and solutions,” IEEE Consum. Electron. Mag., vol. 9, no. 2, pp. 17–25, Mar. 2020.

[19]

R. A. Abdelouahid, O. Debauche, and A. Marzak, “Internet of Things: A new interoperable IoT platform. Application to a smart building,” Procedia Comput. Sci., vol. 191, pp. 511–517, Jan. 2021.

Digital Library

[20]

S. P. Mohanty, “Security and privacy by design is key in the Internet of Everything (IoE) era,” IEEE Consum. Electron. Mag., vol. 9, no. 2, pp. 4–5, Mar. 2020.

[21]

A. Sassone, M. Grosso, M. Poncino, and E. Macii, “Smart electronic systems: An overview,” in Smart Systems Integration and Simulation. Cham, Switzerland: Springer, 2016, pp. 5–21.

[22]

K. T. Chui, K. F. Tsang, H. R. Chi, B. W. K. Ling, and C. K. Wu, “An accurate ECG-based transportation safety drowsiness detection scheme,” IEEE Trans. Ind. Informat., vol. 12, no. 4, pp. 1438–1452, Aug. 2016.

[23]

G. Şefkat and M. A. Özel, “Experimental and numerical study of energy and thermal management system for a hydrogen fuel cell-battery hybrid electric vehicle,” Energy, vol. 238, Jan. 2022, Art. no.

[24]

S. Mumtaz, V. G. Menon, A. Al-Dulaimi, M. I. Ashraf, and M. Guizani, “Guest editorial: Special issue on enabling massive IoT with 6G: Applications, architectures, challenges, and research directions,” IEEE Internet Things J., vol. 8, no. 7, pp. 5111–5113, Apr. 2021.

[25]

C. Dehury, S. N. Srirama, P. K. Donta, and S. Dustdar, “Securing clustered edge intelligence with blockchain,” IEEE Consum. Electron. Mag., early access, Apr. 4, 2022. 10.1109/MCE.2022.3164529.

[26]

Y. Liang, F. He, and X. Zeng, “3D mesh simplification with feature preservation based on whale optimization algorithm and differential evolution,” Integr. Comput.-Aided Eng., vol. 27, no. 4, pp. 417–435, 2020.

[27]

M. Adil, M. K. Khan, M. Jamjoom, and A. Farouk, “MHADBOR: AI-enabled administrative-distance-based opportunistic load balancing scheme for an agriculture Internet of Things network,” IEEE Micro, vol. 42, no. 1, pp. 41–50, Jan./Feb. 2021.

[28]

P. Corcoran, J. Lemley, C. Costache, and V. Varkarakis, “Deep learning for consumer devices and services 2—AI gets embedded at the edge,” IEEE Consum. Electron. Mag., vol. 8, no. 5, pp. 10–19, Sep. 2019.

[29]

A. K. Swain, A. K. Rajput, and K. K. Mahapatra, “Network on chip for consumer electronics devices: An architectural and performance exploration of synchronous and asynchronous network-on-chip-based systems,” IEEE Consum. Electron. Mag., vol. 8, no. 3, pp. 50–54, May 2019.

[30]

M. Sparkes, What Is a Metaverse. Amsterdam, The Netherlands: Elsevier, 2021.

[31]

G. S. Velikic, D. Maric, D. Abazovic, and J. Vidakovic, “Consumer technology and the possibilities in a gap between medicine and wellness,” IEEE Consum. Electron. Mag., vol. 10, no. 5, pp. 54–57, Sep. 2021.

[32]

W. Z. Khan, E. Ahmed, S. Hakak, I. Yaqoob, and A. Ahmed, “Edge computing: A survey,” Future Gener. Comput. Syst., vol. 97, pp. 219–235, Aug. 2019.

Digital Library

[33]

D. Puthal and X. Zhang, “Secure computing for the Internet of Things and network edges: Protecting communication in the worldwide network of devices,” IEEE Consum. Electron. Mag., vol. 7, no. 6, pp. 29–30, Nov. 2018.

[34]

E. L. C. Macedo, F. C. Delicato, L. F. M. de Moraes, and G. Fortino, “Assigning trust to devices in the context of consumer IoT applications,” IEEE Consum. Electron. Mag., early access, Feb. 24, 2022. 10.1109/MCE.2022.3154357.

[35]

H. Peng, Z. Kan, C. Liu, T. Baker, and D. Zhao, “Risk assessment of CPS composed of edge consumer electronics under intentional attack,” IEEE Consum. Electron. Mag., vol. 11, no. 2, pp. 36–41, Mar. 2022.

[36]

H. X. Zhuet al., “Smart healthcare in the era of Internet-of-Things,” IEEE Consum. Electron. Mag., vol. 8, no. 5, pp. 26–30, Sep. 2019.

[37]

H. Zhuet al., “Index of low-power wide area networks: A ranking solution toward best practice,” IEEE Commun. Mag., vol. 59, no. 4, pp. 139–144, Apr. 2021.

[38]

J.-J. Chenet al., “Realizing dynamic network slice resource management based on SDN networks,” in Proc. Int. Conf. Intell. Comput. Emerg. Appl. (ICEA), 2019, pp. 120–125.

[39]

I. F. Akyildiz, A. Kak, and S. Nie, “6G and beyond: The future of wireless communications systems,” IEEE Access, vol. 8, pp. 133995–134030, 2020.

[40]

Á. Garai and A. Adamkó, “Comprehensive healthcare interoperability framework integrating telemedicine consumer electronics with cloud architecture,” in Proc. IEEE 15th Int. Symp. Appl. Mach. Intell. Inform. (SAMI), 2017, pp. 411–416.

[41]

T. D. Mou and G. Srivastava, “Network protocols for the Internet of Health Things,” in Intelligent Internet of Things for Healthcare and Industry. Cham, Switzerland: Springer, 2022, pp. 21–66.

[42]

S. Zhao, J. Wen, S. Mumtaz, S. Garg, and B. J. Choi, “Spatially coupled codes via partial and recursive superposition for industrial IoT with high trustworthiness,” IEEE Trans. Ind. Informat., vol. 16, no. 9, pp. 6143–6153, Sep. 2020.

[43]

Z. Zhouet al., “Secure and latency-aware digital twin assisted resource scheduling for 5G edge computing-empowered distribution grids,” IEEE Trans. Ind. Informat., vol. 18, no. 7, pp. 4933–4943, Jul. 2022.

[44]

C. K. Wuet al., “An IoT tree health indexing method using heterogeneous neural network,” IEEE Access, vol. 7, pp. 66176–66184, 2019.

[45]

C. K. Wu, K. F. Tsang, Y. Liu, H. Zhu, H. Wang, and Y. Wei, “Critical Internet of Things: An interworking solution to improve service reliability,” IEEE Commun. Mag., vol. 58, no. 1, pp. 74–79, Jan. 2020.

Digital Library

[46]

J. Wu, C. K. Tse, F. C. M. Lau, and I. W. H. Ho, “Analysis of communication network performance from a complex network perspective,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 60, no. 12, pp. 3303–3316, Dec. 2013.

[47]

T. Zhang, J. Cao, Y. Chen, L. Cuthbert, and M. Elkashlan, “A small world network model for energy efficient wireless networks,” IEEE Commun. Lett., vol. 17, no. 10, pp. 1928–1931, Oct. 2013.

[48]

N. N. Y. Chu and W. Luptow, “CE standards of interest: Wearables and wireless TV [standards],” IEEE Consum. Electron. Mag., vol. 6, no. 2, pp. 114–117, Apr. 2017.

[49]

R. Olfati-Saber, J. A. Fax, and R. M. Murray, “Consensus and cooperation in networked multi-agent systems,” Proc. IEEE, vol. 95, no. 1, pp. 215–233, Jan. 2007.

[50]

Z. Li, Z. Duan, G. Chen, and L. Huang, “Consensus of multiagent systems and synchronization of complex networks: A unified viewpoint,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 57, no. 1, pp. 213–224, Jan. 2010.

Digital Library

[51]

D. A. Hahn, A. Munir, and S. P. Mohanty, “Security and privacy issues in contemporary consumer electronics [energy and security],” IEEE Consum. Electron. Mag., vol. 8, no. 1, pp. 95–99, Jan. 2019.

[52]

A. Mahmood, Y. Hong, M. K. Ehsan, and S. Mumtaz, “Optimal resource allocation and task segmentation in IoT enabled mobile edge cloud,” IEEE Trans. Veh. Technol., vol. 70, no. 12, pp. 13294–13303, Dec. 2021.

[53]

H. Liaoet al., “Blockchain and semi-distributed learning-based secure and low-latency computation offloading in space-air-ground-integrated power IoT,” IEEE J. Sel. Topics Signal Process., vol. 16, no. 3, pp. 381–394, Apr. 2022.

[54]

W. Z. Khan, M. Y. Aalsalem, M. K. Khan, and Q. Arshad, “Data and privacy: Getting consumers to trust products enabled by the Internet of Things,” IEEE Consum. Electron. Mag., vol. 8, no. 2, pp. 35–38, Mar. 2019.

[55]

X. Hu, T. Zhu, X. Zhai, W. Zhou, and W. Zhao, “Privacy data propagation and preservation in social media: A real-world case study,” IEEE Trans. Knowl. Data Eng., early access, Dec. 21, 2022. 10.1109/TKDE.2021.3137326.

Digital Library

[56]

X. Jia, L. Xing, J. Gao, and H. Wu, “A survey of location privacy preservation in social Internet of Vehicles,” IEEE Access, vol. 8, pp. 201966–201984, 2020.

[57]

M. Xue, C. Yuan, H. Wu, Y. Zhang, and W. Liu, “Machine learning security: Threats, countermeasures, and evaluations,” IEEE Access, vol. 8, pp. 74720–74742, 2020.

[58]

Q. Liu, P. Li, W. Zhao, W. Cai, S. Yu, and V. C. M. Leung, “A survey on security threats and defensive techniques of machine learning: A data driven view,” IEEE Access, vol. 6, pp. 12103–12117, 2018.

[59]

W. Guan, X. Wen, L. Wang, Z. Lu, and Y. Shen, “A service-oriented deployment policy of end-to-end network slicing based on complex network theory,” IEEE Access, vol. 6, pp. 19691–19701, 2018.

[60]

G. Vernize, A. L. P. Guedes, and L. C. P. Albini, “Malicious nodes identification for complex network based on local views,” Comput. J., vol. 58, no. 10, pp. 2476–2491, Oct. 2015.

[61]

S. I. Pérez, S. Moral-Rubio, and R. Criado, “A new approach to combine multiplex networks and time series attributes: Building intrusion detection systems (IDS) in cybersecurity,” Chaos Solitons Fractals, vol. 150, Sep. 2021, Art. no.

[62]

M. A. Niazi and A. Hussain, “Social network analysis of trends in the consumer electronics domain,” in Proc. IEEE Int. Conf. Consum. Electron. (ICCE), 2011, pp. 219–220.

Cited By

Gao HYu SIqbal MGuizani M(2024)ResFNN: Residual Structure-Based Feedforward Neural Network for Action Quality Assessment in Sports Consumer ElectronicsIEEE Transactions on Consumer Electronics10.1109/TCE.2024.348256070:4(6653-6663)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3482560
Pan TLi CJin XZhou WLiu JCai X(2024)Adaptive Learning-Based Cloud-Edge Collaborative Secure Resource Management for Blockchain-Empowered Demand ResponseIEEE Transactions on Consumer Electronics10.1109/TCE.2024.347879470:4(6568-6579)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3478794
Wang YXiao YXiao MLi N(2024)Design of Dynamic Offset Spatial Modulation MIMO for Low-Cost Consumer Electronics DevicesIEEE Transactions on Consumer Electronics10.1109/TCE.2024.345417870:4(7526-7534)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3454178
Show More Cited By

Index Terms

State-of-the-Art and Research Opportunities for Next-Generation Consumer Electronics

Index terms have been assigned to the content through auto-classification.

Recommendations

Research Note Consumer Addressability and Customized Pricing

The increasing availability of customer information is giving many firms the ability to reach and customize price and other marketing efforts to the tastes of the individual consumer. This ability is labeled as consumer addressability. Consumer ...
Consumer Addressability and Customized Pricing

The increasing availability of customer information is giving many firms the ability to reach and customize price and other marketing efforts to the tastes of the individual consumer. This ability is labeled as consumer addressability. Consumer ...
Shopping Behavior and Consumer Preference for Store Price Format: Why "Large Basket" Shoppers Prefer EDLP

<P>In recent years, the supermarket industry has become increasingly competitive. One outcome has been the proliferation of a variety of pricing formats, and considerable debate among academics and practitioners about how these formats affect consumers' ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image IEEE Transactions on Consumer Electronics

IEEE Transactions on Consumer Electronics Volume 69, Issue 4

Nov. 2023

522 pages

ISSN:0098-3063

Issue’s Table of Contents

1558-4127 © 2022 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

Publisher

IEEE Press

Publication History

Published: 01 November 2023

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

57
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 20 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Gao HYu SIqbal MGuizani M(2024)ResFNN: Residual Structure-Based Feedforward Neural Network for Action Quality Assessment in Sports Consumer ElectronicsIEEE Transactions on Consumer Electronics10.1109/TCE.2024.348256070:4(6653-6663)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3482560
Pan TLi CJin XZhou WLiu JCai X(2024)Adaptive Learning-Based Cloud-Edge Collaborative Secure Resource Management for Blockchain-Empowered Demand ResponseIEEE Transactions on Consumer Electronics10.1109/TCE.2024.347879470:4(6568-6579)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3478794
Wang YXiao YXiao MLi N(2024)Design of Dynamic Offset Spatial Modulation MIMO for Low-Cost Consumer Electronics DevicesIEEE Transactions on Consumer Electronics10.1109/TCE.2024.345417870:4(7526-7534)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3454178
Zhu SLu CQiu XGao SDing XKim YZhao Y(2024)Mitigating RC-Delay Induced Accuracy Loss in Analog In-Memory Computing: A Non-Compromising ApproachIEEE Transactions on Consumer Electronics10.1109/TCE.2024.344534170:4(7544-7550)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3445341
Zhang XWang YPeng XDong MOta KXu L(2024)OHMA: An Edge-Based Lightweight Occluded Target Re-Identification Framework for Exploring Abundant Feature ExpressionIEEE Transactions on Consumer Electronics10.1109/TCE.2024.344333670:4(7424-7435)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3443336
Guo DFeng ZZhang ZKhan FChen CBai ROmar MKumar S(2024)Causal Effects of Adversarial Attacks on AI Models in 6G Consumer ElectronicsIEEE Transactions on Consumer Electronics10.1109/TCE.2024.344332870:3(5804-5813)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3443328
Thakur VKumar ADas JDev KMagarini M(2024)Quantum Error Correction Codes in Consumer Technology: Modeling and AnalysisIEEE Transactions on Consumer Electronics10.1109/TCE.2024.344247270:4(7102-7111)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3442472
Al-Obiedollah HBany Salameh HBenkhelifa E(2024)Jamming-Resilient Fairness-Oriented Resource Allocation Technique for IRS-Assisted NOMA 6G-Enabled IoT NetworksIEEE Transactions on Consumer Electronics10.1109/TCE.2024.343459670:3(5796-5803)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3434596
Liu YShou PSun YYan CZheng Z(2024)Expand, Pool and Confine: Reliably Detaching Salient Objects From the BackgroundIEEE Transactions on Consumer Electronics10.1109/TCE.2024.343035470:3(5353-5362)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3430354
Saxena MDev KKumar S(2024)Dynamic CPU Frequency Scaling for Efficient Resource Allocation in Heterogeneous Fog Networks for CIoT ApplicationsIEEE Transactions on Consumer Electronics10.1109/TCE.2024.342772570:4(7365-7372)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3427725
Show More Cited By

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents