Proffering Ranks to the Smart Cities based on the Data Received from IoT Devices using Visualization Techniques

Abstract

Innovative lifestyle in cities upgraded the smart infrastructure and sustainable significance in the countries worldwide. A new approach is proposed to analyze the smart-city indexing across the world based on the key features to proffer the city ranking. The key features like smart-mobility refers to the Intelligent movement of citizens, smart environment refers to improvement in the efficiency of inhabitance within the city, smart governance used in applying innovative technological implementation to provide service, smart economy refers to the improvement in various urban aspects and livelihood. Proposed approach focuses on classifying the smart innovative infrastructural implementation in the urban livelihood for city data visualization and proffering cluster ranks by validating the proffering with Convolutional-Neural Network (CNN). To collect the data, we used IoT sensors information by integrating the sensors of six feature metrics in city-hubs. The huge data collected from the sensors are utilized to perform the smart-city visualization. Data are analyzed using statistical procedure by grouping the similar data to applying folium cluster techniques and fuzzy mapping. A detailed description and analysis of smart indexing are grounded by proffering effectively, in addition the subsequent research analysis is recommended for the researchers.