Smart City Management based Data applications using Improved Seagull Optimization algorithm with Dense Net 121

Recently, rapid growth of information technology, has progressively entered the daily life of combinations. Smart city management is the innovative technology by combining Internet of Things (IoT), cloud computing and mobile Internet technologies to achieve modern living experience. By analyzing the current situation of smart city this research presented Improved Seagull Optimization Algorithm with Dense Net -121 (ISOA-Dense Net-121) to improve processes in digitalization economy. The suggested model involves sensor-integrated systems to optimize by generating accurate predictions. ISOA is utilized to simulate the seagull migration for global exploration, resulting in better weight initialization. Then, DenseNet-121 utilized to improve the performance in difficult image recognition tasks. By removing the unnecessary data applications, these hybridized model ISOA-DenseNet-121 reduce the environmental effects in SWM. According to the result it illustrated that when compared to existing models such as ResNeXt, SWM and Smart Waste Bin Management System (SWBMS) the proposed ISOA-Dense Net-121 recommended strategy outperformed the others in terms of accuracy, f-score of 99.3%, precision of 99.4% and recall of 99.2%.