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IoT Commercial and Industrial Applications and AI-Powered IoT

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Frontiers of Quality Electronic Design (QED)

Abstract

This chapter introduces an overview on the commercial and industrial applications. The goal is to provide a comprehensive overview of IoT applications commercially and industrially. Commercial applications of IoT cover our daily life environments such as healthcare, retail, tourism and hospitality, and digital marketing. Industrial applications of IoT cover wearables, maintenance management, manufacturing, agriculture, water supply, smart cities, financial services, oil and gas mining, warehousing, transportation and telematics, and smart building. We show that the enhanced capabilities of IoT play an important role to increase commercial benefits, increase efficiency, save time, improve safety, and improve operational processes while reducing operational costs of IoT systems which make them more productive. There are also IoT data analytics, IoT security risks, threats, and privacy issues due to their importance for IoT applications. Finally, AI-powered IoT is discussed where tiny machine learning enables large AI algorithms run efficiently on low-resource devices.

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References

  1. Costa, B., Pires, P.F., Delicato, F.C., Li, W., Zomaya, A.Y.: Design and Analysis of IoT Applications: A Model-Driven Approach. In: 2016 IEEE 14th Intl Conf on Dependable, Autonomic and Secure Computing, 14th Intl Conf on Pervasive Intelligence and Computing, 2nd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech), Auckland, New Zealand, vol. 2016, pp. 392–399. https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2016.81

  2. Rusu, I.C.A.R.C.: Commercial and Industrial Internet of Things Applications with the Raspberry Pi. Apress (2020)

    Google Scholar 

  3. https://www.trialog.com/en/iot-systems-and-interoperability/ (Accessed on 03/14/2022).

  4. Jayashankara, M., Udmale, S.S., Pandey, A.K., Singh, R.S.: IoT-based data analytics for the healthcare industry techniques and applications. Intell. Data-Centric Syst., 9–29 (2021)

    Google Scholar 

  5. Baker, S., Xiang, W., Atkinson, I.: Things for Smart Healthcare: Technologies, Challenges, and Opportunities. IEEE Access (2018)

    Google Scholar 

  6. Naresh, V.S., Pericherla, S.S., Murty, P.S.R., Reddi, S.: Internet of Things in healthcare: Architecture, applications, challenges, and solutions. Comput Syst Sci Eng. 6, 411–421 (2020)

    Article  Google Scholar 

  7. Anand, G., Heuss, L.: Feasibility of breath monitoring in patients undergoing elective colonoscopy under propofol sedation: A single-center pilot study. World J Gastrointest. Endosc. 6 (2016). https://doi.org/10.4253/wjge.v6.i3.82

  8. Hashim, N., Norddin, N., Idris, F., Yusoff, S.N.I.M., Zahari, M.: IoT blood pressure monitoring system. Indonesian J. Elect. Eng. Comp. Sci. 19(3), 1384–1390. ISSN: 2502–4752 (2020). https://doi.org/10.11591/ijeecs.v19.i3.pp1384-1390

    Article  Google Scholar 

  9. Nelson, B.D., et al.: Wireless technologies for implantable devices. Sensors (Basel, Switzerland). 20(16), 4604 (2020). https://doi.org/10.3390/s20164604

    Article  Google Scholar 

  10. Ratnaparkhi, S., Khan, S., Arya, C., Khapre, S., Singh, P., Diwakar, M., Shankar, A.: Smart agriculture sensors in IOT: A review. Mater. Today: Proceed.. (In Press)

    Google Scholar 

  11. Sushanth, G., Sujatha, S.: IOT based smart agriculture system. IEEE (2018)

    Book  Google Scholar 

  12. Caro, F., Sadr, R.: The Internet of Things (IoT) in retail: Bridging supply and demand. Business Horizons. 62, 47–54 (2019)

    Article  Google Scholar 

  13. Syed, A.S., Sierra-Sosa, D., Kumar, A., Elmaghraby, A.: IoT in smart cities: A survey of technologies, practices and challenges. Smart Cities. 4, 429–475 (2021). https://doi.org/10.3390/smartcities4020024

    Article  Google Scholar 

  14. Raghuvanshi, A., Singh, U.K.: Internet of Things for smart cities- security issues and challenges. Mater. Today: Proceed. https://doi.org/10.1016/j.matpr.2020.10.849

  15. Natividad, J.G., Palaoag, T.D.: IoT based model for monitoring and controlling water distribution. Int. Conf. Inform. Technol. Digit. Appl., IOP Conf. Series: Mater. Sci. Eng. 482, 012045. IOP Publishing (2019). https://doi.org/10.1088/1757-899X/482/1/012045

    Article  Google Scholar 

  16. Daigavane, V.V., Gaikwad, M.A.: Water quality monitoring system based on IOT. Adv. Wireless Mobile Commun.., ISSN 0973–6972. 10(5), 1107–1116 (2017)

    Google Scholar 

  17. https://csrc.nist.gov/publications/detail/sp/800-61/rev-2/ (Accessed on 07/01/20).

  18. Ngo, Q.-D., Nguyen, H.-T., Le, V.-H., Nguyen, D.-H.: A survey of IoT malware and detection methods based on static features. 6(4), 280–286 (2020)

    Google Scholar 

  19. Ngo, Q.-D., Nguyen, H.-T., Le, V.-H., et al.: A survey of IoT malware and detection methods based on static features. ICT Exp. 6(4), 280–286 (2020)

    Article  Google Scholar 

  20. Plu, T.N., Hoang, L.H., Touan, N.N., Tho, N.D., Binh, N.N.: CFDVex: A novel feature extraction method for detecting cross-architecture IoT malware. In: Proceedings of the Tenth International Symposium on Information and Communication Technology, pp. 248–254 (2019)

    Google Scholar 

  21. Alasmary, H., et al.: Graph-based comparison of IoT and android malware. In: Proceedings of International Conference on Computational Social Networks, pp. 259–272 (2018)

    Google Scholar 

  22. Azmoodeh, A., et al.: Robust malware detection for Internet of (Battlefield) things devices using deep eigenspace learning. IEEE Trans. Sustain. Comput., 88–95 (2018)

    Google Scholar 

  23. Rey, V., Sánchez, P.M.S., Celdrán, A.H., Bovet, G.: Federated learning for malware detection in IoT devices. Comp. Netw. 204(26), 108693 (2022)

    Article  Google Scholar 

  24. https://www.trellix.com/en-us/security-awareness/ransomware/what-is-ransomware.html (Accessed on 05/09/2022).

  25. Wani, A., Sathiya, R.: Ransomware protection in IoT using software defined networking. Int. J. Elect. Comp. Eng. 10(3), 3166–3174

    Google Scholar 

  26. Bertino, E.: Botnets and internet of things security. Computer. 50(2), 76–79 (2017)

    Article  Google Scholar 

  27. Azmoodeh, A., Dehghantanha, A., Conti, M., Choo, K.K.R.: Detecting crypto-ransomware in IoT networks based on energy consumption footprint. J. Ambient Intell. Human. Comput. 9(4), 1141–1152 (2018)

    Article  Google Scholar 

  28. Butun, I., Osterberg, P., Song, H.: Security of the internet of things: Vulnerabilities, attacks and countermeasures. https://arxiv.org/pdf/1910.13312.pdf

  29. Li, B., Ye, R., Gao, G., Liang, R., Liu, W., Ken Cai, E.: A detection mechanism on malicious nodes in IoT. Comp. Commun. 151(1), 51–59 (2020)

    Article  Google Scholar 

  30. Jiang, J., Han, G., Zhu, C., Dong, Y., Zhang, N.: Secure localization in wireless sensor networks: A survey. J. Commun. 6(6), 460–470 (2011)

    Article  Google Scholar 

  31. Deep, S., Zheng, X., Jolfaei, A., Yu, D., Ostovari, P., Bashir, A.K.: A survey of security and privacy issues in the Internet of Things from the layered context. https://arxiv.org/pdf/1903.00846.pdf (Accessed on 05-19-2022).

  32. Prabhakar, S.: Network security in digitalization: Attacks and defence. Int. J. Res. Comput. Appl. Robot. 5, 46–52 (2017)

    Google Scholar 

  33. Conti, M., Dragoni, N., Lesyk, V.: A survey of man in the middle attacks. IEEE Commun. Surv. Tutor.

    Google Scholar 

  34. Bhosale, S.D., Sonavane, S.S.: Wormhole attack detection in internet of things. Int. J. Eng. Technol. 7(2.33), 749–751 (2018)

    Google Scholar 

  35. Fazeldehkordi, E., Amiri, I.S., Akanbi, O.A.: A study of blackhole attack solutions. Syngress. (2016)

    Google Scholar 

  36. Kibirige, G.W., Sanga, C.: A survey on detection of sinkhole attack in wireless sensor network. https://arxiv.org/ftp/arxiv/papers/1505/1505.01941.pdf#:~:text=Sinkhole%20attack %20is%20a%20type,drops%20or%20altered%20 routing%20information.

  37. Teng, L., Zhang, Y.: Secure routing algorithm against sinkhole attack for mobile wireless sensor network, in computer modeling and simulation, in proceedings of 2010. ICCMS’10. Second IEEE Int. Conf. Comp. Model. Simul. 4, 79–82 (2010)

    Google Scholar 

  38. Gupta, S., Gupta, B.B.: Cross-site scripting (XSS) attacks and defense mechanisms: Classification and state-of-the-art. Int. J. Syst. Assur. Eng. Manage. 8, 512–530 (2017). https://doi.org/10.1007/s13198-015-0376-0

    Article  Google Scholar 

  39. https://owasp.org/www-community/attacks/xss/ (Accesed on 06/18/2022).

  40. Tawalbeh, L.’a., Muheidat, F., Tawalbeh, M., Quwaider, M.: IoT privacy and security: Challenges and solutions. Appl. Sci. 10, 4102 (2020). https://doi.org/10.3390/app10124102

    Article  Google Scholar 

  41. Thierer, A.D.: The internet of things and wearable technology: Addressing privacy and security concerns without derailing innovation. Richmond J. Law Technol. XXI(2) (2015)

    Google Scholar 

  42. Nelson, J.W. (editor), Jayne, F., Mary, A. H. (Co-editors): Using Predictive Analytics to Improve Healthcare Outcomes, Wiley (2021)

    Google Scholar 

  43. Han, S., Mao, H., Dally, W.J., Deep compression: Compressing deep neural networks with pruning, trained quantization and Hufman coding, 4th international conference on learning representations, ICLR 2016, San Juan.

    Google Scholar 

  44. https://www.fujitsu.com/au/imagesgig5/IoT_solutions_UBIQUITOUSWARE_Digital_ Solutions.pdf (Accessed on 05/06/2022).

  45. https://static.googleusercontent.com/media/www.google.com/en//corporate/datacenter/dc-best-practices-google.pdf (Accessed on 05/06/2022).

  46. https://www.clariontech.com/blog/ai-and-iot-blended-what-it-is-and-why-it-matters (Accessed on 06/18/2022).

  47. https://www.rolls-royce.com/country-sites/sea/discover/2021/tapping-ai-technologies-to-create-solutions-of-tomorrow.aspx (Accessed on 05/06/2022).

  48. https://www.clariontech.com/blog/ai-and-iot-blended-what-it-is-and-why-it-matters (Accesed on 06/18/2022).

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Authors and Affiliations

  1. The British University in Egypt, El-Sherouk City, Cairo, Egypt

    Khaled Ahmed Nagaty

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  1. Khaled Ahmed Nagaty
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Correspondence to Khaled Ahmed Nagaty .

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  1. Silicon Valley Polytechnic Institute, Los Altos Hills, CA, USA

    Ali Iranmanesh

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Nagaty, K.A. (2023). IoT Commercial and Industrial Applications and AI-Powered IoT. In: Iranmanesh, A. (eds) Frontiers of Quality Electronic Design (QED). Springer, Cham. https://doi.org/10.1007/978-3-031-16344-9_12

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  • DOI: https://doi.org/10.1007/978-3-031-16344-9_12

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