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Today, there are increasing demands for flying drones with diverse capabilities for civilian and military uses, and there is growing attention given to this topic. When it comes to drone operations, the amount of energy they consume is a determining factor in their ability to achieve their full potential. According to the nature of the problem, it appears that it is necessary to identify the factors affecting the energy consumption of UAVs during the execution of missions as well as examine the general factors that influence the consumption of energy. The purpose of this chapter is to provide an overview of the current state of research in the area of UAV energy consumption. This is followed by general categorizations of factors affecting UAV's energy consumption as well as an investigation of different energy models.

One of the most important impacts of access to transportation infrastructure is the economic and social well-being of residents. However, it is important to know, how much of an impact it has? Which of the access routes-road, rail, or air-has more impact? What methods can be used to assess this effect? Does this effect vary from country to country? This study attempts to provide a framework to examine the correlation between the access of a country’s cities (to various types of rail, air, and road transportation networks) and the economic and social parameters of its inhabitants. For this purpose, the connection of the city to the rail network was calculated by taking into account the distance in time between the city and the nearest station. A city’s road access is calculated by finding the average road distance of a city to other cities in that country. A city’s access to air traffic is calculated based on the weekly flights of that city’s airport (if that city has an airport). To evaluate the performance of the proposed framework, a case study is conducted in Iran. The results of the case study show that the access of cities to transportation networks strongly influences economic development and population size in Iran. Pearson’s correlation coefficients between transport infrastructure and economic growth and population size are 0.641 and 0.725, respectively. It was also found that among the transport networks, road transport is more correlated with economic development and unemployment rate of Iranian cities compared to other transport modes.

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