Smart City Gnosys

Smart city article details

Title	Inclusive Smart Cities: Iot-Cloud Solutions For Enhanced Energy Analytics And Safety
ID_Doc	31106
Authors	Almazroi A.A.; Alsubaei F.S.; Ayub N.; Jhanjhi N.Z.
Year	2024
Published	International Journal of Advanced Computer Science and Applications, 15, 5
DOI	http://dx.doi.org/10.14569/IJACSA.2024.01505128
Abstract	Securing smart cities in the evolving Internet of Things (IoT) demands innovative security solutions that extend beyond conventional theft detection. This study introduces temporal convolutional networks and gated recurrent units (TCGR), a pioneering model tailored for the dynamic IoT-SM dataset, addressing eight distinct forms of theft. In contrast to conventional techniques, TCGR utilizes Jaya tuning (TCGRJ), ensuring improved accuracy and computational efficiency. The technique employs ResNeXt for feature extraction to extract important patterns from IoT device-generated data and Edited Nearest Neighbors for data balancing. Empirical evaluations validate TCGRJ’s greater precision (96.7%) and accuracy (97.1%) in detecting theft. The model significantly aids in preventing theftrelated risks and is designed for real-time Internet of Things applications in smart cities, aligning with the broader goal of creating safer spaces by reducing hazards associated with unauthorized electrical connections. TCGRJ promotes sustainable energy practices that benefit every resident, particularly those with disabilities, by discouraging theft and encouraging economical power consumption. This research underscores the crucial role of advanced theft detection technologies in developing smart cities that prioritize inclusivity, accessibility, and an enhanced quality of life for all individuals, including those with disabilities. © (2024) Science and Information Organization. All rights reserved.
Author Keywords	cloud computing; disability support; IoT Security; smart cities; theft detection

Similar Articles

Id	Similarity	Authors	Title	Published
8606	0.885	Quasim M.T.; Nisa K.; Khan M.Z.; Husain M.S.; Alam S.; Shuaib M.; Meraj M.; Abdullah M.	An Internet Of Things Enabled Machine Learning Model For Energy Theft Prevention System (Etps) In Smart Cities	Journal of Cloud Computing, 12, 1 (2023)
23957	0.882	Hashim M.; Khan L.; Javaid N.; Ullah Z.; Shaheen I.	Enhancing Smart City Functions Through The Mitigation Of Electricity Theft In Smart Grids: A Stacked Ensemble Method	International Transactions on Electrical Energy Systems, 2024 (2024)
23955	0.875	Rao S.P.C.; Swarnam S.; Kumar N.; Sheikameer Batcha S.; Sivalanka V.; Chakravarthi A.V.D.	Enhancing Smart City Efficiency By Mitigating Electricity Theft In Smart Grids Using Lightweight Dnn And Smo	3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025 (2025)
32932	0.867	Simisterra-Batallas C.; Pico-Valencia P.; Sayago-Heredia J.; Quiñónez-Ku X.	Internet Of Things And Deep Learning For Citizen Security: A Systematic Literature Review On Violence And Crime	Future Internet, 17, 4 (2025)
17981	0.867	Himdi T.; Ishaque M.	Deep Learning-Enhanced Anomaly Detection For Iot Security In Smart Cities	ARPN Journal of Engineering and Applied Sciences, 19, 6 (2024)
8616	0.865	Nandhini N.; Manikandan V.; Elango S.	An Interpretable Generalized Additive Neural Networks For Electricity Theft Detection In Smart Cities Using Balanced Data And Intelligent Grid Management	Energy and Buildings, 346 (2025)
17907	0.862	Liloja; Ranjana P.	Deep Learning Methodology For Detecting Breaches To Improve Security In Smart Cities	2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023 (2023)
33842	0.86	Sharma P.; Raglin A.	Iot In Smart Cities: Exploring Information Theoretic And Deep Learning Models To Improve Parking Solutions	Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019 (2019)
3390	0.859	Gupta B.B.; Chui K.T.; Gaurav A.; Arya V.; Chaurasia P.	A Novel Hybrid Convolutional Neural Network- And Gated Recurrent Unit-Based Paradigm For Iot Network Traffic Attack Detection In Smart Cities	Sensors (Basel, Switzerland), 23, 21 (2023)
8003	0.858	Xie R.	An Energy Theft Detection Framework With Privacy Protection For Smart Grid	Proceedings of the International Joint Conference on Neural Networks, 2023-June (2023)