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Next generation wireless networks are expected to be greatly supported by unmanned aerial vehicles, which can act as aerial base stations and constitute a promising solution for the exorbitant rise in user demands. This is possible because of unmanned aerial vehicle characteristics such as mobility, flexibility, increased line-of-sight probability, and their ability to access unreachable locations. Extensive research is now widely performed on the deployment, performance analysis, resource management, trajectory optimization, and channel modeling in such networks. This survey article focuses on the different applications and the related algorithms for realizing aerial base stations by thoroughly reviewing each related research area. In a nutshell, this article provides key applications, challenges, and the technology used for the design and analysis of unmanned aerial vehicles as base stations.

In olden days street lights were not operated in an automatic way. Automation of street lights has become apparent these days. But we can notice that we do not require high intensity light during night hours, i.e. when there is no traffic, no people in the streets or on roads and even in the early mornings. As per requirement, the light intensity can be reduced using dimmer circuit. Light dependent resistor (LDR) sensors are used to sense the darkness and Passive Infrared (PIR) sensors are to detect the objects. Raspberry Pi (Master node) and Arduino (Slave node) will communicate each other and they help the proposed system to work more effectively. Current sensor and Voltage sensor are used to measure the current and voltage respectively. By reducing the intensity at these times, energy can be saved to some extent and the data is uploaded to the cloud. We can monitor and control the street lights in a smart way as per our requirement. Fault detection, minimization of cost, reducing the loss of electricity and man power are also possible. Hence, this proposed smart street lighting system will be helpful to the society in cost effective way.

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