Computing least air pollution exposure routes

Personalized routing counts on traveler's preferences which are usually based on different criteria, such as shortest, fastest, least traffic, or less expensive (e.g., less fuel cost, toll free). However, people are increasingly becoming concerned about the adverse health effects of exposure to air pollution in chosen routes. Exposures to elevated air pollution concentrations particularly endanger children, pregnant women, elderly people, and people with asthma and other respiratory conditions. Choosing routes with least air pollution exposure (APE) is seen as one approach to minimize the level of pollution exposed, which is a major public health issue. Routing algorithms use weights on segments of road networks to find optimum routes. While existing weights are commonly distance and time, among a few others, there is currently no weight based on APE to compute least APE routes. In this paper, we present a weight function that computes weight based on APE. Two different approaches, geostatistical and non-geostatistical, were used to compute APE weight. Each approach was evaluated, and the results indicate that the APE weight is suitable for computing least APE routes. © 2013 Taylor & Francis

Algorithm for energy-efficient and automatic configuration of pedestrian navigation services: Smartphones on clouds

Smartphones have been playing a major role as personal navigation aids to pedestrians, among other travelers. Pedestrian Navigation Services (PNSs) on smartphones face challenges such as limited battery power, relatively lower computational speed, limited storage capacities, and varying quality of available networks. Automatic configuration of PNS components is very important to address these challenges. In this paper, we present a novel approach for optimum configuration of components and computations of PNSs between smartphones and cloud platforms. An algorithm is developed based on three models, Minimum Computation (MinComp), Minimum Communication (MinComm), and Balanced Computation-Communication (BalCC), to allow smartphones to operate navigation services optimally in a distributed environment over cloud platforms. Each model was simulated by using various values for each parameter

Geocoding recommender: An algorithm to recommend optimal online geocoding services for applications

Today, many services that can geocode addresses are available to domain scientists and researchers, software developers, and end-users. For a number of reasons, including quality of reference database and interpolation technique, a given address geocoded by different services does not often result in the same location. Considering that there are many widely available and accessible geocoding services and that each geocoding service may utilize a different reference database and interpolation technique, selecting a suitable geocoding service that meets the requirements of any application or user is a challenging task. This is especially true for online geocoding services which are often used as black boxes and do not provide knowledge about the reference databases and the interpolation techniques they employ. In this article, we present a geocoding recommender algorithm that can recommend optimal online geocoding services by realizing the characteristics (positional accuracy and match rate) of the services and preferences of the user and/or their application. The algorithm is simulated and analyzed using six popular online geocoding services for different address types (agricultural, commercial, industrial, residential) and preferences (match rate, positional accuracy). © 2011 Blackwell Publishing Ltd

Health-optimal routing in pedestrian navigation services

People use various criteria for choosing routes, which may vary depending on location and time, purpose of trip, and personal preferences. Common routing criteria supported by current navigation services include shortest, fastest, least traffic, and least expensive (e.g., less fuel cost, toll free). While each optimal route is computed by using one of these criteria, there is currently no criterion that can be used to compute routes that are health-optimal. In this paper, we focus on a new routing criterion to compute health-optimal routes with the main objective of increasing physical activity. Those who are physically capable and motivated to walk can adapt a lifestyle that includes walking as a means to mitigate or prevent obesity. To that end, a routing criterion for computing health-optimal routes suitable for those who are concerned with obesity must take into account both environmental and individual factors. Computing optimal routes requires that each road segment of a road network be assigned a weight; like, distance for shortest routes and travel time for fastest routes. In this paper, we present and discuss a new weight for segments of pedestrian paths used in pedestrian navigation services to compute health-optimal routes. While health-optimal routes may address various health conditions, the objective of this work is to provide options for walking routes to increase regular physical activity as one means to help mitigate or prevent obesity. Weights are calculated by considering both environmental and individual parameters. The optimal-health weight is simulated using various scenarios. The results of the simulations show that the computed weights can be used to find health-optimal routes that are meaningful and consistent with walkability and obesity standards. © 2012 ACM