Potential applications of internet of things: A comprehensive analysis
DOI:
https://doi.org/10.20535/SRIT.2308-8893.2024.1.01Keywords:
Internet of Things, automation, security, potential applicationsAbstract
Internet of Things (IoT) is the amalgamation of hardware, like sensors and trackers, which monitor several parameters of the environment or physical objects, and software that processes all the data gathered by hardware. Globally, the IoT market is anticipated to reach 53.8 billion USD by 2025. This enhancing demand is due to its innate ability to automate, which drives several industries to adopt IoT. In addition, minimum memory cost, processing, and storage with an increase in Big Data (BD), cloud, and conjunction of industrial networks and the internet are the added factors for the increase in IoT development. Due to this significance, IoT has applications in numerous areas like medical management, farming, wearable technology, smart energy meters, smart cities, etc. The applications are not limited to the examples mentioned above. Considering this, existing studies have considered different applications and attempted to execute them. As different applications have been focused on by these studies, the present review intends to provide a compilation of potential applications of IoT as considered by conventional research between 2018 and 2022. The study also intends to explore the advantages and disadvantages of different IoT applications (deliberated by conventional studies) through tabular analysis. Further, this review emphasizes IoT’s major key challenges and countermeasures to resolve its security issues. Finally, the study affords recommendations that will assist all IoT experts in bringing IoT products with enhanced security into the market.
References
P. Balaganesh, M. Vasudevan, R. Rameswari, and N. Natarajan, “Recent Trends in IOT-Enabled Composter for Organic Wastes,” in Sustainable Cities and Resilience, ed: Springer, 2022, pp. 445–457.
P. Gokhale, O. Bhat, and S. Bhat, “Introduction to IOT,” International Advanced Research Journal in Science, Engineering and Technology, vol. 5, pp. 41–44, 2018.
N. Sharma, M. Shamkuwar, and I. Singh, “The history, present and future with IoT,” in Internet of Things and Big Data Analytics for Smart Generation, ed: Springer, 2019, pp. 27–51.
R. Román-Castro, J. López, and S. Gritzalis, “Evolution and trends in IoT security,” Computer, vol. 51, pp. 16–25, 2018.
B.K. Chae, “The evolution of the Internet of Things (IoT): A computational text analysis,” Telecommunications Policy, vol. 43, p. 101848, 2019.
J. Wang, M.K. Lim, C. Wang, and M.-L. Tseng, “The evolution of the Internet of Things (IoT) over the past 20 years,” Computers & Industrial Engineering, vol. 155, p. 107174, 2021.
R. Krishnamurthi, A. Kumar, D. Gopinathan, A. Nayyar, and B. Qureshi, “An overview of IoT sensor data processing, fusion, and analysis techniques,” Sensors, vol. 20, p. 6076, 2020.
R. Nawaratne, D. Alahakoon, D. De Silva, P. Chhetri, and N. Chilamkurti, “Self-evolving intelligent algorithms for facilitating data interoperability in IoT environments,” Future Generation Computer Systems, vol. 86, pp. 421–432, 2018.
S. Rathore, B.W. Kwon, and J.H. Park, “BlockSecIoTNet: Blockchain-based decentralized security architecture for IoT network,” Journal of Network and Computer Applications, vol. 143, pp. 167–177, 2019.
M. El-Hajj, A. Fadlallah, M. Chamoun, and A.J.S. Serhrouchni, “A survey of internet of things (IoT) authentication schemes,” Sensors, vol. 19, p. 1141, 2019.
O. Mnushka, IOT architecture patterns and data protocols, 2018.
A. Triantafyllou, P. Sarigiannidis, and T.D. Lagkas, “Network protocols, schemes, and mechanisms for internet of things (iot): Features, open challenges, and trends,” Wireless Communications and Mobile Computing, vol. 2018, 2018. doi: 10.1155/2018/5349894.
S. Ketu, P.K. Mishra, “Enhanced Gaussian process regression-based forecasting model for COVID-19 outbreak and significance of IoT for its detection,” Applied Intelligence, vol. 51, pp. 1492–1512, 2021.
M.A. Patil, A.C. Adamuthe, and A. Umbarkar, “Smartphone and IoT based system for integrated farm monitoring,” in Techno-Societal 2018, ed: Springer, 2020, pp. 471–478.
J. Muangprathub, N. Boonnam, S. Kajornkasirat, N. Lekbangpong, A. Wanichsombat, and P. Nillaor, “IoT and agriculture data analysis for smart farm,” Computers and Electronics in Agriculture, vol. 156, pp. 467–474, 2019.
G. Arun Francis, M. S. Manikandan, V. Sundar, and E. Gowtham, “Home Automation Using Iot,” Annals of the Romanian Society for Cell Biology, pp. 9902–9908, 2021.
C. Zhang, “Design and application of fog computing and Internet of Things service platform for smart city,” Future Generation Computer Systems, vol. 112, pp. 630–640, 2020.
R. Casado-Vara, A. Martin-del Rey, S. Affes, J. Prieto, and J. M. Corchado, “IoT network slicing on virtual layers of homogeneous data for improved algorithm operation in smart buildings,” Future Generation Computer Systems, vol. 102, pp. 965–977, 2020.
T. Alsharari, S. Alresheedi, A. Fatani, and I. Maolood, “Significant role of internet of things (IoT) for designing smart home automation and privacy issues,” International Journal of Engineering & Technology, vol. 9, pp. 515–519, 2020.
C. Stolojescu-Crisan, C. Crisan, and B.-P. Butunoi, “An IoT-based smart home automation system,” Sensors, vol. 21, p. 3784, 2021.
W. Li, T. Logenthiran, V.-T. Phan, and W. L. Woo, “A novel smart energy theft system (SETS) for IoT-based smart home,” IEEE Internet of Things Journal, vol. 6, pp. 5531–5539, 2019.
D.B. Avancini, J.J. Rodrigues, R.A. Rabêlo, A.K. Das, S. Kozlov, and P. Solic, “A snew IoT based smart energy meter for smart grids”, International Journal of Energy Reserch, vol. 45, pp. 189–202, 2021.
V. Herasevich, S. Subramanian, “Tele-ICU technologies,” Critical Care Clinics, vol. 35, pp. 427–438, 2019.
Medtech and the Internet of Medical Things. 2018. Available: https: //www2.deloitte.com/content/dam/Deloitte/global/Documents/Life-Sciences-Health-Care/gx-lshc-medtech-iomt-brochure.pdf
P.P. Ray, D. Dash, K. Salah, and N. Kumar, “Blockchain for IoT-based healthcare: background, consensus, platforms, and use cases,” IEEE Systems Journal, vol. 15, pp. 85–94, 2020.
A. Onasanya, S. Lakkis, and M. Elshakankiri, “Implementing IoT/WSN based smart Saskatchewan healthcare system,” Wireless Networks, vol. 25, pp. 3999–4020, 2019.
V. Bianchi, M. Bassoli, G. Lombardo, P. Fornacciari, M. Mordonini, and I. De Munari, “IoT wearable sensor and deep learning: An integrated approach for personalized human activity recognition in a smart home environment,” IEEE Internet of Things Journal, vol. 6, pp. 8553–8562, 2019.
D. Fozoonmayeh et al., “A scalable smartwatch-based medication intake detection system using distributed machine learning,” Journal of Medical Systems, vol. 44, pp. 1–14, 2020.
H. Pang, Z. Zheng, T. Zhen, and A. Sharma, “Smart farming: An approach for disease detection implementing IoT and image processing,” International Journal of Agricultural and Environmental Information Systems (IJAEIS), vol. 12, pp. 55–67, 2021.
A. Aher, J. Kasar, P. Ahuja, and V. Jadhav, “Smart agriculture using clustering and IOT,” International Research Journal of Engineering and Technology (IRJET), vol. 5, pp. 2395–0056, 2018.
G. Scalabrini Sampaio, A. R. de A. Vallim Filho, L. Santos da Silva, and L. Augusto da Silva, “Prediction of motor failure time using an artificial neural network,” Sensors, vol. 19, p. 4342, 2019. doi: 10.3390/s19194342.
M.-Q. Tran, M. Elsisi, K. Mahmoud, M.-K. Liu, M. Lehtonen, and M.M. Darwish, “Experimental setup for online fault diagnosis of induction machines via promising IoT and machine learning: Towards industry 4.0 empowerment,” IEEE Access, vol. 9, pp. 115429–115441, 2021.
Y. Liu, T. Dillon, W. Yu, W. Rahayu, and F. Mostafa, “Noise removal in the presence of significant anomalies for industrial IoT sensor data in manufacturing,” IEEE Internet of Things Journal, vol. 7, pp. 7084–7096, 2020.
A. Čolaković, M. Hadžialić, “Internet of Things (IoT): A review of enabling technologies, challenges, and open research issues,” Computer Networks, vol. 144, pp. 17–39, 2018.
C. MacGillivray, D. Reinsel, and M. Shirer, The growth in connected iot devices is expected to generate 79.4 zb of data in 2025, According to a New IDC Forecast. Available: https://www.businesswire.com/news/home/20190618005012/en/The-Growth-in-Connected-IoT-Devices-is-Expected-to-Generate-79.4ZB-of-Data-in-2025-According-to-a-New-IDC-Forecast
A. Abdul-Ghani, D. Konstantas, “A comprehensive study of security and privacy guidelines, threats, and countermeasures: An IoT perspective,” Journal of Sensor and Actuator Networks, vol. 8, p. 22, 2019.
