Performance Evaluation of Machine Learning Techniques Which are Used for an Automated Index of Smart City Application
In light of the "computerized city", "smart city" is broadly utilized in day by day vocation, ecological assurance, open , city administrations and different fields. In this paper, we for the most part center around ongoing exploration and the idea of "smart city", condensing the connection between "shrewd city" and "computerized city", advancing the fundamental substance of use frameworks just as the significance and trouble of the development of "keen city", and offering a concise expression of the impact of creating brilliant cities in india.As smart cities consists of many many applications in this paper we only concentrated on Impact Assessment(IA) of garbages which we can see round the cities day to day accumulation forming a hump of waste and we are suffering with a lot of incometable methods to dispose and to classify the waste which is being accumulated. So, in this project we can expect our system can classify the impact assessment of the garbage accumulated areas or zones. Machine Learning techniques like Support Vector Machine (SVM) and Maximum Likelihood(MLH) will be helpful classifiers to access the impact assessment in a particular area with optimum accuracy of IA. Imagery will be the remotely sensed data which is essential to classify the Land Cover Land Use(LCLU). Performance Evaluation can be done by comparing these two classifier(SVM & MLC) techniques to find better accuracy that will be a Novelty in this research work.