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In today's world, technological trend offers computing resources as services through the internet in on-demand or pay-as-you-go approach. These services are provided by different cloud service providers. Due to which trust on the any service provider is a choice of any customer. In order to choose a reputed cloud service provider a new method using the concept of fuzzy has proposed in this paper. This method enhanced the customer's satisfaction level of using cloud services by avoiding ambiguities in fuzzy interface system (FIS) through optimization. Proposed fuzzy rule-based decision support system is collaborating with advanced fuzzy system optimized using a swarm intelligent firefly algorithm that facilitates the consumers in selecting right CSP based upon their rating value. It conducts three different reviews of three different components, i.e. customer review, service provider review and public review. Results are carried out on the basis of both simple and the optimized fuzzy, and it is found that the optimized fuzzy surpasses the simple fuzzy logic.

In the recent scenario, there is a drastic improvement in transportation, infrastructure, and communication technology which increases the number of commercial as well as non-commercial vehicles. Therefore, there is also an increase in the number of accident incidence. This ultimately results in a high death rate due to a road accident. More than half of accident incidence results in death due to delayed medical aid to the victim. If medical aid or services received at the proper time, then the victim may survive. With the application of machine learning processes and communication advancements, there is scope for the development of a more accurate system. In this chapter, a model is presented based on IoT devices that can sense and predict the pre-accident/pre-collision state and generates an alarm message about the collision is going to occur. This model is designed to extracts image/video features to determine the possibility of occurrence of a collision. This model is also efficient for post-collision.

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Cloud computing has come up as a standout amongst the most encouraging &reliable advancements in the IT part. However by and by there exists a noteworthy issue of load adjusting in the distributed computing condition. This paper comprises of an answer for streamlining the heap utilizing hereditary calculation. Hereditary calculation which takes after the transformative system can build up an answer near ideal arrangement. The proposed calculation is produced by consolidating two existing calculations by considering cost an incentive as the wellness work. The workload is adjusted by the considering the mix of both the heap rate and cost estimation of the assets. Allotment of assets is performed by taking the best fit esteem and lessening the reaction time and general cost. Reenactment comes about are indicated utilizing the cloud examiner test system.