Secure smart home architecture for ambient-assisted living using a multimedia Internet of Things based system in smart cities

Ridha Ouni; Kashif Saleem; Ridha Ouni; Kashif Saleem

doi:10.3934/mbe.2024153

Mathematical Biosciences and Engineering

2024, Volume 21, Issue 3: 3473-3497. doi: 10.3934/mbe.2024153

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Secure smart home architecture for ambient-assisted living using a multimedia Internet of Things based system in smart cities

Ridha Ouni ¹,
Kashif Saleem ^{2
,
,}

1.
Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia
2.
Center of Excellence in Information Assurance (CoEIA), King Saud University, Riyadh 11653, Saudi Arabia

Academic Editor: José M Jimenez

Received: 09 December 2023 Revised: 20 January 2024 Accepted: 23 January 2024 Published: 05 February 2024

Recent advances in smartphones and remote monitoring based on the Internet of Things (IoT) have enabled improved multidimensional intelligent services. The advent of IoT-based wearable and multimedia sensors has prevented millions of mishaps through seamless and systematic monitoring. An IoT-based monitoring system is composed of several sensor devices to measure vital signs, fall detection, energy consumption, and visual recognition. As the data collected by the sensors are transmitted to cloud storage through the Internet, data security is a major concern when transmitting data from remote locations. To improve data security and prediction accuracy, in this study, we proposed a smart and secure multimedia IoT monitoring system for smart homes backed up by smart grid supervisory control and data acquisition (SCADA). The proposed system employs state-of-the-art IoT microcontrollers and hardware devices and integrates them in a manner that significantly affects the accuracy and speed of the entire system. Furthermore, the information gathered from IoT is securely transferred through private channels and stored on the cloud, which can be accessed authentically and reliably using an information system built into an IoT application. The output was extensively compared in terms of power consumption and delivery ratio, which were based on the values collected with sequence numbers. The comparative analysis demonstrated that the proposed approach provides increased prediction accuracy and better security. Hence, the proposed power-efficient prototype model monitors the entire smart home environment in real time and serves as an early warning system for critical situations.
- Internet of Things,
- remote sensing system,
- data security,
- smart homes
Citation: Ridha Ouni, Kashif Saleem. Secure smart home architecture for ambient-assisted living using a multimedia Internet of Things based system in smart cities[J]. Mathematical Biosciences and Engineering, 2024, 21(3): 3473-3497. doi: 10.3934/mbe.2024153

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Abstract

Recent advances in smartphones and remote monitoring based on the Internet of Things (IoT) have enabled improved multidimensional intelligent services. The advent of IoT-based wearable and multimedia sensors has prevented millions of mishaps through seamless and systematic monitoring. An IoT-based monitoring system is composed of several sensor devices to measure vital signs, fall detection, energy consumption, and visual recognition. As the data collected by the sensors are transmitted to cloud storage through the Internet, data security is a major concern when transmitting data from remote locations. To improve data security and prediction accuracy, in this study, we proposed a smart and secure multimedia IoT monitoring system for smart homes backed up by smart grid supervisory control and data acquisition (SCADA). The proposed system employs state-of-the-art IoT microcontrollers and hardware devices and integrates them in a manner that significantly affects the accuracy and speed of the entire system. Furthermore, the information gathered from IoT is securely transferred through private channels and stored on the cloud, which can be accessed authentically and reliably using an information system built into an IoT application. The output was extensively compared in terms of power consumption and delivery ratio, which were based on the values collected with sequence numbers. The comparative analysis demonstrated that the proposed approach provides increased prediction accuracy and better security. Hence, the proposed power-efficient prototype model monitors the entire smart home environment in real time and serves as an early warning system for critical situations.

References

[1]	P. Muruganantham, S. Wibowo, S. Grandhi, N. H. Samrat, N. Islam, A systematic literature review on crop yield prediction with deep learning and remote sensing, Remote Sens., 14 (2022), 1990. https://doi.org/10.3390/rs14091990 doi: 10.3390/rs14091990
[2]	N. Casagli, E. Intrieri, V. Tofani, G. Gigli, F. Raspini, Landslide detection, monitoring and prediction with remote-sensing techniques, Nat. Rev. Earth Environ., 4 (2023), 51–64. https://doi.org/10.1038/s43017-022-00373-x doi: 10.1038/s43017-022-00373-x
[3]	A. Chakraborty, M. Islam, F. Shahriyar, S. Islam, H. U. Zaman, M. Hasan, Smart home system: a comprehensive review, J. Electr. Comput. Eng., 2023 (2023), 7616683. https://doi.org/10.1155/2023/7616683 doi: 10.1155/2023/7616683
[4]	B. Hammi, S. Zeadally, R. Khatoun, J. Nebhen, Survey on smart homes: vulnerabilities, risks, and countermeasures, Comput. Secur., 117, (2022), 102677. https://doi.org/10.1016/j.cose.2022.102677 doi: 10.1016/j.cose.2022.102677
[5]	A. Kekre, S. K. Gawre, Solar photovoltaic remote monitoring system using IOT, in 2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE), Bhopal, India, (2017), 619–623. https://doi.org/10.1109/RISE.2017.8378227
[6]	M. Manoj, V. D. Kumar, M. Arif, E. R. Bulai, P. Bulai, O. Geman, State of the Art techniques for water quality monitoring systems for fish ponds using IoT and underwater sensors: a review, Sensors, 22 (2022), 2088. https://doi.org/10.3390/s22062088 doi: 10.3390/s22062088
[7]	J. Puustjärvi, L. Puustjärvi, The role of smart data in smart home: health monitoring case, Procedia Comput. Sci., 69 (2015), 143–151. https://doi.org/10.1016/j.procs.2015.10.015 doi: 10.1016/j.procs.2015.10.015
[8]	S. V. N. Sreenivasu, T. S. Kumar, O. B. Hussain, A. R. Yeruva, S. R. Kabat, A. Chaturvedi, Cloud based electric vehicle's temperature monitoring system using IOT, Cybern. Syst., (2023) 1–16. https://doi.org/10.1080/01969722.2023.2176649 doi: 10.1080/01969722.2023.2176649
[9]	A. A. Khan, A. A. Laghari, A. A. Shaikh, Z. A. Shaikh, A. K. Jumani, Innovation in multimedia using IoT systems, in Multimedia Computing Systems and Virtual Reality, Taylor & Francis, (2022), 171–187. http://dx.doi.org/10.1201/9781003196686-8
[10]	V. Upadrista, S. Nazir, H. Tianfield, Secure data sharing with blockchain for remote health monitoring applications: a review, J. Reliab. Intell. Environ., 9 (2023), 349–368. https://doi.org/10.1007/s40860-023-00204-w doi: 10.1007/s40860-023-00204-w
[11]	K. Saleem, H. Abbas, J. Al-Muhtadi, M. A. Orgun, R. Shankaran, G. Zhang, Empirical studies of ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm in E-health sensor platform, in 2016 IEEE 41st Conference on Local Computer Networks Workshops (LCN Workshops), Dubai, United Arab Emirates, (2016), 236–240. https://doi.org/10.1109/LCN.2016.053
[12]	P. Morsali, S. Dey, A. Mallik, A. Akturk, Switching modulation optimization for efficiency maximization in a single-stage series resonant DAB-based DC-AC converter, IEEE J. Emerging Sel. Top. Power Electron., 11 (2023), 5454–5469. https://doi.org/10.1109/JESTPE.2023.3302839 doi: 10.1109/JESTPE.2023.3302839
[13]	M. S. Akbar, Z. Hussain, M. Sheng, R. Shankaran, Wireless body area sensor networks: survey of MAC and routing protocols for patient monitoring under IEEE 802.15.4 and IEEE 802.15.6, Sensors, 22 (2022), 8279. https://doi.org/10.3390/s22218279 doi: 10.3390/s22218279
[14]	D. D. Olatinwo, A. M. Abu-Mahfouz, G. P. Hancke, H. C. Myburgh, Energy efficient priority-based hybrid MAC protocol for IoT-enabled WBAN systems, IEEE Sens. J., 23 (2023), 13524–13538. https://doi.org/10.1109/JSEN.2023.3273427 doi: 10.1109/JSEN.2023.3273427
[15]	K. Saleem, F. Y. Alfariheedi, R. Ouni, J. Al-Muhtadi, Cellular IoT based secure monitoring system for smart environments, in 2022 IEEE International Conference on E-health Networking, Application & Services (HealthCom), Genoa, Italy, (2022), 1–5. https://doi.org/10.1109/HealthCom54947.2022.9982776
[16]	A. H. Montazeri, S. K. Emami, M. R. Zaghiyan, S. Eslamian, Stochastic learning algorithms, in Handbook of Hydroinformatic, Elsevier, (2023), 385–410. http://dx.doi.org/10.1016/B978-0-12-821285-1.00016-6
[17]	B. G. Mohammed, D. S. Hasan, Smart healthcare monitoring system using IoT, Int. J. Interact. Mob. Technol., 17 (2023), 141–152. https://doi.org/10.3991/ijim.v17i01.34675 doi: 10.3991/ijim.v17i01.34675
[18]	G. Alandjani, IoT enabled healthcare monitoring system using convolutional neural network, ARPN J. Eng. Appl. Sci., 18 (2023), 245–250. http://dx.doi.org/10.59018/022343 doi: 10.59018/022343
[19]	R. Alharbi, H. Alhichri, R. Ouni, Y. Bazi, M. Alsabaan, Improving remote sensing scene classification using quality-based data augmentation, Int. J. Remote Sens., 44 (2023), 1749–1765. https://doi.org/10.1080/01431161.2023.2184213 doi: 10.1080/01431161.2023.2184213
[20]	M. A. Razzaque, S. S. Javadi, Y. Coulibaly, M. T. Hira, QoS-aware error recovery in wireless body sensor networks using adaptive network coding, Sensors, 15 (2015), 440–464. https://doi.org/10.3390/s150100440 doi: 10.3390/s150100440
[21]	S. D. Suganthi, R. Anitha, V. Sureshkumar, S. Harish, S. Agalya, End to end light weight mutual authentication scheme in IoT-based healthcare environment, J. Reliab. Intell. Environ., 6 (2020), 3–13. https://doi.org/10.1007/s40860-019-00079-w doi: 10.1007/s40860-019-00079-w
[22]	G. Manikandan, D. Karunkuzhali, D. Geetha, V. Kavitha, Design of an IoT approach for security surveillance system for industrial process monitoring using Raspberry-Pi, in AIP Conference Proceedings, 2519 (2022), 030024. https://doi.org/10.1063/5.0109769
[23]	H. Meddeb, Z. Abdellaoui, F. Houaidi, Development of surveillance robot based on face recognition using Raspberry-PI and IOT, Microprocess. Microsyst., 96 (2023), 104728. https://doi.org/10.1016/j.micpro.2022.104728 doi: 10.1016/j.micpro.2022.104728
[24]	S. Shreya, K. Chatterjee, A. Singh, A smart secure healthcare monitoring system with Internet of Medical Things, Comput. Electr. Eng., 101 (2022), 107969. https://doi.org/10.1016/j.compeleceng.2022.107969 doi: 10.1016/j.compeleceng.2022.107969
[25]	K. Sangeethalakshmi, S. P. Angel, U. Preethi, S. Pavithra, V. S. Priya, Patient health monitoring system using IoT, Mater. Today: Proc., 80 (2023), 2228–2231. https://doi.org/10.1016/j.matpr.2021.06.188 doi: 10.1016/j.matpr.2021.06.188
[26]	J. Xie, X. Xiao, Y. Xu, B. Jin, An IoT assisted early warning system for smart grid, J. Phys.: Conf. Ser., 2218 (2022), 012027. https://doi.org/10.1088/1742-6596/2218/1/012027 doi: 10.1088/1742-6596/2218/1/012027
[27]	H. Albataineh, M. Nijim, S. Ballampalli, The design of a novel smart home control system using a smart grid based on edge and cloud computing, Int. J. Smart Grid Clean Energy, 11 (2022), 57–71. https://doi.org/10.1109/SEGE49949.2020.9181961 doi: 10.1109/SEGE49949.2020.9181961
[28]	L. Nasraoui A. Cabani, H. Trimech, Implementing lightweight key exchange solutions for WSN with LoRa connectivity, Int. J. Sens. Netw., 39 (2022), 192–204. https://dx.doi.org/10.1504/IJSNET.2022.124569 doi: 10.1504/IJSNET.2022.124569
[29]	K. Sangeethalakshmi, S. J. Ganesh, K. Dhivya, V. Kannagi, M. Rajkumar, Internet of Things assisted wireless environment monitoring system using smart sensors supportivity, in 2022 International Conference on Electronics and Renewable Systems (ICEARS), Tuticorin, India, (2022), 628–632. https://doi.org/10.1109/ICEARS53579.2022.9751994
[30]	T. Nguyen-Tan, C. Dang-Ngoc, Q. Le-Trung. A smart agriculture solution includes intelligent irrigation and security, in Industrial Networks and Intelligent Systems, INISCOM 2023, Springer Nature, (2023), 3–18. https://doi.org/10.1007/978-3-031-47359-3_1
[31]	D. Hercog, T. Lerher, M. Truntič, O. Težak, Design and implementation of ESP32-based IoT devices, Sensors, 23 (2023), 6739. https://doi.org/10.3390/s23156739 doi: 10.3390/s23156739

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