With the growing progress and embracing of smart digital technology integration for education, large amount of data is collected from informative backgrounds which has been analyzed and given motivational perceptions to the educational worker. The data-driven method for improved understanding and enhancing knowledge together with the learning situation paves the way for learning analytics to contribute to smart learning. The current learning analytics lacks knowledge awareness, an essential component in smart education—this paper analysis the smart leaning mechanism and reviews the smart leaning application development tool. The survey has been taken based on the questionnaire related to smart learning with the respondents of 100 individuals. The paper also highlights the smart classroom integrated technology development towards smart learning architecture. The analysis includes the negative and positive impact of smart application-based learning and cost-effective leaning for the middle-income sectors.
Number of vehicles increasing day by day in the world which results in traffic, air pollution, delay in reaching designation. Traffic density is increased in the roads, especially in the signals. The traffic congestion has negatively affected the efficiency, aggressiveness, and financial development of a nation. Thus, congestion control of traffic has become a significant zone of research, and a substantial number of answers for this issue left different research endeavors in the said field in recent decades. The traffic volume changing after some time, and in this way, long traffic lines are produced at the street intersections. Consequently, the Intelligent Transport System answers these related issues. It has incredible possible and ability to make transportation systems safe and smart efficiently. ITS provides the accessing and driving services of effortlessly participating transportation systems in a smart city. Traffic congestion can be managed in a proper manner by using time estimation and other route diversion in a pre-informed way. For this, we have to calculate the values of traffic congestion density and find the neighboring route. Density algorithm and distance measure algorithm were used to find the traffic density, and the Swarm algorithm was used to find the nearby path.
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