Dear Manvitha Gali,

the integration of IoT, Deep Learning and Cloud Computing will be realized in future when developing Digital Twins (DTs). Using different DTs can improve the efficiency and effectiveness of Smart City systems. In a Smart City as an Ecosystem, several DTs - especially City/Urban DT, Energy DT and Manufacturing DT - have to be integrated in a special way. This integration leads to the formation of the Digital Twin Federation of a Smart City.

For more information, see:

https://www.researchgate.net/publication/366167747_Digital_Twins_in_IoT

I would like to highlight the following figures there:

Fig 8 shows an example for Application of DTs in Smart Cities to Monitor Building Safety using virtual Sensors and virtual Actuators,

Fig. 10 shows a Smart City as an Ecosystem: City/Urban DTE, Energy DT and Manufacturing DT form a Digital Twin Federation of the Smart City

Best regards

Anatol Badach

Dear, Prof: Anatol Badach

Thank you for you Response!!!

I read the DT’s article you mentioned, And This digital twin Approach is very much Impressed!!

Conclusion: It can be equipped with virtual sensors that collect data about the building's structural integrity, such as the temperature, humidity, and vibrations. The data collected by the sensors can be analyzed using machine learning algorithms to detect any abnormalities or potential safety hazards.

Hi Manvitha,

This integration is taking place in many applications, even today. To better explain, let's briefly explain what each part is:

• IoT or Internet of Things is about connecting different devices over wireless technologies or internet and as a result automatically collecting data, using sensors
• Deep learning is a subset of machine learning, which facilitates analysing huge data, collected in an IoT system. Information or knowledge which is obtained from this data analysis will be used for different purposes. For instance, in case of smart cities, this information can be used for power supply, water or waste management.
• Cloud computing is about offering faster and more flexible computing services (e.g. storage, database, ...) over the internet.

Therefore, these parts are all needed to work hand-in-hand, so that an IoT system can function as smoothly as possible, with low latency.

Hi,

Please take a look at my papers in the IoT. In the first paper I used Machine Learning with IoT:

■ A. Abusukhon Intelligent Shoes for Detecting Blind Falls Using the Internet of Things. KSII Transactions on Internet and Information Systems. Vol. 17, Issue 9. 2023

■ A. Abusukhon, A. Al-Fuqaha, B. Hawashin, A Novel Technique for Detecting Underground Water Pipeline Leakage Using the Internet of Things. Journal of Universal Computer Science (JUCS). Vol. 29, No. 8.

■ A. Abusukhon, IOT Bracelets for Guiding Blind People in an Indoor Environment, in Journal of Communications Software and Systems, vol. 19, no. 2, pp. 114-125, April 2023, doi: 10.24138/jcomss-2022-0160.

■ A. Abusukhon (2021) Towards Achieving a Balance between the User Satisfaction and the Power Conservation in the Internet of Things, IEEE Internet of Things Journal, doi: 10.1109/JIOT.2021.3051764. impact factor 9.936. Published by IEEE. https://ieeexplore.ieee.org/document/9326414. [Science Citation Index].

■ Ahmad Abusukhon, Bilal Hawashin and Mohammad Lafi (2021) An Efficient Algorithm for Reducing the Power Consumption in Offices Using the Internet of Things, International Journal of Advances in Soft Computing and its Applications (IJASCA). http://ijasca.zuj.edu.jo/Volumes.aspx

■ A. Abusukhon, Z. Mohammad, A. Al-Thaher (2021) An authenticated, secure, and mutable multiple-session-keys protocol based on elliptic curve cryptography and text_to-image encryption algorithm. Concurrency and computation practice and experience. [Science Citation Index].

■ B. Hawashin, A. Abusukhon An Efficient Course Recommender Using Deep Enriched Hidden Student Aptitudes. ICIC Express Letters, Part B: Applications, 2022.

■ A. Abusukhon, N. Anwar, M. Mohammad, Z., Alghanam, B. (2019) A hybrid network security algorithm based on Diffie Hellman and Text-to-Image Encryption algorithm. Journal of Discrete Mathematical Sciences and Cryptography. 22(1) pp. 65- 81. (SCOPUS). https://www.tandfonline.com/doi/abs/10.1080/09720529.2019.1569821

■ A. Abusukhon, B.Wawashin, B. (2015) A secure network communication protocol based on text to barcode encryption algorithm. International Journal of Advanced Computer Science and Applications (IJACSA). (ISI indexing). https://thesai.org/Publications/ViewPaper?Volume=6&Issue=12&Code=IJACSA&Seri alNo=9

■ A. Abusukhon, Talib, M., and Almimi, H. (2014) Distributed Text-to-Image Encryption Algorithm. International Journal of Computer Applications (IJCA), 106 (1). [ available online at : https://www.semanticscholar.org/paper/Distributed-Text-to-Image-Encryption-Algorithm-Ahmad-Mohammad/0764b3bd89e820afc6007b048dac159d98ba5326]

■ A. Abusukhon (2013) Block Cipher Encryption for Text-to-Image Algorithm. International Journal of Computer Engineering and Technology (IJCET). 4(3) , 50-59. http://www.zuj.edu.jo/portal/ahmad-abu-alsokhon/wpcontent/uploads/sites/15/BLOCK-CIPHER-ENCRYPTION-FOR-TEXT-TO-IMAGE ALGORITHM.pdf

■ A. Abusukhon, Talib, M. and Nabulsi, M. (2012) Analyzing the Efficiency of Text-to-Image Encryption Algorithm. International Journal of Advanced Computer Science and Applications ( IJACSA )(ISI indexing) , 3(11), 35 – 38. https://thesai.org/Publications/ViewPaper?Volume=3&Issue=11&Code=IJACSA&Seri alNo=6

■ A. Abusukhon, Talib M., Issa, O. (2012) Secure Network Communication Based on Text to Image Encryption. International Journal of Cyber-Security and Digital Forensics (IJCSDF), 1(4). The Society of Digital Information and Wireless Communications (SDIWC) 2012. https://www.semanticscholar.org/paper/SECURE NETWORK-COMMUNICATION-BASED-ON-TEXT-TO-IMAGE-Abusukhon-Talib/1d122f280e0d390263971842cc54f1b044df8161