Efficient energy management for the internet of things in smart cities

The drastic increase in urbanization over the past few years requires sustainable, efficient, and smart solutions for transportation, governance, environment, quality of life, and so on. The Internet of Things offers many sophisticated and ubiquitous applications for smart cities. The energy demand of IoT applications is increased, while IoT devices continue to grow in both numbers and requirements. Therefore, smart city solutions must have the ability to efficiently utilize energy and handle the associated challenges. Energy management is considered as a key paradigm for the realization of complex energy systems in smart cities. In this article, we present a brief overview of energy management and challenges in smart cities. We then provide a unifying framework for energy-efficient optimization and scheduling of IoT-based smart cities. We also discuss the energy harvesting in smart cities, which is a promising solution for extending the lifetime of low-power devices and its related challenges. We detail two case studies. The first one targets energy-efficient scheduling in smart homes, and the second covers wireless power transfer for IoT devices in smart cities. Simulation results for the case studies demonstrate the tremendous impact of energy-efficient scheduling optimization and wireless power transfer on the performance of IoT in smart cities

Coverage and mobile sensor placement for vehicles on predetermined routes: a greedy heuristic approach

Road potholes are not only nuisance but can also damage vehicles and pose serious safety risks for drivers. Recently, a number of approaches have been developed for automatic pothole detection using equipment such as accelerometers, image sensors or LIDARs. Mounted on vehicles, such as taxis or buses, the sensors can automatically detect potholes as the vehicles carry out their normal operation. While prior work focused on improving the performance of a standalone device, it simply assumed that the sensors would be installed on the entire fleet of vehicles. When the number of sensors is limited it is important to select an optimal set of vehicles to make sure that they do not cover similar routes in order to maximize the total coverage of roads inspected by sensors. The paper investigates this problem for vehicles that follow pre-determined routes, formulates it as a linear optimization problem and proposes a solution based on a greedy heuristic. The proposed approach has been tested on an official London bus route dataset containing 713 routes and showed up to 78% improvement compared to a random sensor placement selected as a baseline algorithm

A Racial Impact Analysis of HB 869/SB 274

Virginia is growing. Between 1990 and 2000, Virginia’s population rose by over 14% - the largest population growth experienced by the state in a single decade (Pollard, 2007). And the state continues to grow. It has been estimated that by 2030, Virginia’s total population may exceed 9.8 million people (Pollard, 2007). Along with population growth, land development has increased which in turn affects transportation, housing and job placement across the Commonwealth. In fact, in many parts of the state, development has outpaced population growth. According to Pollard, “If current patterns continue, Virginia will develop more land in the next 40 years than in the previous 400 years (p.8).” In an effort to curb sprawling development and decrease transportation expenditure, the Virginia General Assembly passed House Bill 3202 in 2007. One major outcome of this multifaceted legislation was the introduction of mandatory Urban Development Areas (UDAs). The goal of UDAs was for localities to concentrate growth and development in order to reduce the cost of transportation and increase opportunities to build multi-use developments and expand affordable housing. In 2012, the General Assembly passed House Bill 869 and Senate Bill 274 which effectively make UDAs no longer mandatory but optional for all localities in the Commonwealth. In this paper, we analyze the racial impact and explore the political history of HB 869/SB 274 while addressing the larger issue of sprawl across the Commonwealth. Smart Growth policies are known to positively impact the environment but they also positively impact low-income and minority communities by increasing access to housing, transportation and ultimately jobs. The story behind Urban Development Areas in the Commonwealth is one of politics and regulation but issues as critical as housing, transportation and job access should be focused much more on the citizens of the Commonwealth. The friction created by the UDA policy between the localities and the state has the potential to spark a statewide conversation about land use and more importantly - the need for people-centered solutions to a growing problem