Smart City Gnosys
Smart city article details
| Title | Smart City Application Based On Internet-Of-Things And Artificial Intelligence For Energy Management Dynamic Memory Modelling |
|---|---|
| ID_Doc | 50028 |
| Authors | Zearah S.A.; Al-Tahee M.; Mohammed A.; Shnawa A.H.; Harith Jameel Mahdi H.; Majeed Z. |
| Year | 2023 |
| Published | 1st International Conference on Emerging Research in Computational Science, ICERCS 2023 - Proceedings |
| DOI | http://dx.doi.org/10.1109/ICERCS57948.2023.10434196 |
| Abstract | By and by, the world ingests a lot of energy, including power, machine protection energies, water-driven energy, etc. Since power stays huge, considering world development, a few researchers have endeavored to deliver power from environmentally friendly power sources from intelligent gadget sensor's point of interaction to address family and modern energy deficiencies. To address the energy management problem during information processing on the Internet of Things (IoT) platform, an Artificial Intelligence Assisted Dynamic Memory Modelling on Internet-of-Things (AIADMM) has been designed and developed with mathematical modeling with multiple information processing sensors for domestic and industrial applications. However, These Particular gadgets, for example, the piezoelectric module, electric structure intensity to the electrical converter, and sun-powered board approach, are utilized to associate the energy stockpiling framework for power age in the standard techniques without streamlined calculations, prompting appeal in energy enhancement research. Thus, the whole energy age by environmentally friendly power sources is improved by two models planned in this exploration: the Artificial Neural Network (ANN) and the Artificial Intelligence Assisted Dynamic Memory Modelling on Internet-of-Things (AIADMM). Test results at the lab scale have been broken down in light of Factual constraints, such as Root Mean Square Error (RMSE). The R2 relationship coefficient, dependability factor, energy then, at that point, network clog, and time delay on the IoT stage shows promising outcomes. © 2023 IEEE. |
| Author Keywords | Artificial intelligence; correlation coefficient; dynamic memory; Internet of things; mean root square; piezoelectric module |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
7584  | 0.871 | Yugank H.K.; Sharma R.; Gupta S.H. | An Approach To Analyse Energy Consumption Of An Iot System | International Journal of Information Technology (Singapore), 14, 5 (2022) |
| 32375 | 0.859 | Nikpour M.; Yousefi P.B.; Jafarzadeh H.; Danesh K.; Shomali R.; Asadi S.; Lonbar A.G.; Ahmadi M. | Intelligent Energy Management With Iot Framework In Smart Cities Using Intelligent Analysis: An Application Of Machine Learning Methods For Complex Networks And Systems | Journal of Network and Computer Applications, 235 (2025) |
| 45476 | 0.854 | Li X.; Zhao H.; Feng Y.; Li J.; Zhao Y.; Wang X. | Research On Key Technologies Of High Energy Efficiency And Low Power Consumption Of New Data Acquisition Equipment Of Power Internet Of Things Based On Artificial Intelligence | International Journal of Thermofluids, 21 (2024) |
| 60724 | 0.853 | Bhuvana J.; Kant Gautam C.; Yadav D.K.; Sharma N. | Utilizing Artificial Intelligence And Iot For Enhanced Renewable Energy Management In Smart Cities | E3S Web of Conferences, 540 (2024) |
| 37643 | 0.851 | Abbas, S; Khan, MA; Falcon-Morales, LE; Rehman, A; Saeed, Y; Zareei, M; Zeb, A; Mohamed, EM | Modeling, Simulation And Optimization Of Power Plant Energy Sustainability For Iot Enabled Smart Cities Empowered With Deep Extreme Learning Machine | IEEE ACCESS, 8 (2020) |