Multi-rotor drones have witnessed a drastic usage increase in several smart city applications due to their 3D mobility, flexibility, and low cost. Collectively, they can be used to accomplish different short-and long-term missions that require low-altitude motion in urban areas. Therefore, it is important to efficiently manage the operation of the fleet to leverage its use and maximize its application performances. In this paper, we propose to investigate the path routing problem for the multiple drones in urban areas, where obstacles with different heights exist. The objective is to find the best trajectories in this 3D environment while ensuring collision-free navigation. The collision is prevented by three possible alternatives: forcing the drone to statically hover, so its peer can pass first, making it fly at a different altitude, or completely changing its path. Multiple charging stations are made available to allow the drones to recharge their batteries when needed. A mixed integer linear program is first developed to model the problem and achieve optimal navigation of the fleet. Afterward, two heuristic algorithms with different conceptual constructions are designed to solve the trajectory planning problem with faster convergence speed. The selected simulation results illustrate the performance of our framework in realistic 3D maps and show that the designed heuristic approaches provide close performances to the optimal ones. INDEX TERMS Unmanned aerial vehicles (UAVs), fleet path planning, energy management, collision avoidance, smart city.

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The demand for sustainable energy is caused by the rapid influx of the rising number of urban cities worldwide. In 2014, roughly 54 percent of the world's populations live in urban areas, and the numbers are expected to go up to 70 percent by 2050. A smart grid is considered as one energy approach to address the increasing demand for sustainable energy. Currently, the U.S. is accelerating the smart grid movement and efforts to modernize the electric grid. The authors will provide an overview of the electricity industry evolution and the emergence of smart grid. Most researchers tend to focus on the physical infrastructure and information layer of the smart grid. However, the most important aspect, which is the social aspect that fuels the advancement of any technology, is often neglected or forgotten. Customer interaction with the utility service provider is arguably one of the key factors of a successful smart grid. But, customers are considered as end users and are often the last in the communication chain to find out about changes in the energy service system, including the ongoing implementation of the smart grid. This paper presents a case study on the State of New York's latest ambitious efforts in reforming the energy vision and their strategies to be proactive in actively engaging customers in the ongoing development of the smart grid. The authors explore the customer-centricity in a smart grid and their interactions using a formalized object oriented modeling approach to reason about the problem, understand the complexity of the evolving energy service system, and communicate about the smart grid with others 1 .

Crowdsourcing is becoming an accepted method of software development for different phases in the production lifecycle. Ideally, mass parallel production through Crowdsourcing could be an option for rapid acquisition in software engineering by leveraging infinite worker resource on the internet. It is important to understand the patterns and strategies of decomposing and uploading parallel tasks to maintain a stable worker supply as well as a satisfactory task completion rate. This research report is an empirical analysis of the available tasks' lifecycle patterns in crowdsourcing. Following the waterfall model in Crowdsourced Software Development (CSD), this research identified four patterns for the sequence of task arrival per project: 1) Prior Cycle, 2) Current Cycle, 3) Orbit Cycle, and 4) Fresh Cycle.