Abstract: The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.
Abstract: This paper demonstrates the bus location system for
the route bus through the experiment in the real environment. A
bus location system is a system that provides information such as
the bus delay and positions. This system uses actual services and
positions data of buses, and those information should match data
on the database. The system has two possible problems. One, the
system could cost high in preparing devices to get bus positions.
Two, it could be difficult to match services data of buses. To avoid
these problems, we have developed this system at low cost and short
time by using the smart phone with GPS and the bus route system.
This system realizes the path planning considering bus delay and
displaying position of buses on the map. The bus location system
was demonstrated on route buses with smart phones for two months.
Abstract: With the increase of economic behavior and the upgrade
of living standar, the ratio for people in Taiwan who own automobiles
and motorcycles have recently increased with multiples. Therefore,
parking issues will be a big challenge to facilitate traffic network and
ensure urban life quality. The Parking Guidance and Information
System is one of important systems for Advanced Traveler Information
Services (ATIS). This research proposes a parking guidance and
information system which integrates GPS and 3G network for a map on
the Geographic Information System to solution inadequate of roadside
information kanban. The system proposed in this study mainly includes
Parking Host, Parking Guidance and Information Server, Geographic
Map and Information System as well as Parking Guidance and
Information Browser. The study results show this system can increase
driver-s efficiency to find parking space and efficiently enhance
parking convenience in comparison with roadside kanban system.
Abstract: Dengue is a mosquito-borne infection that has peaked to an alarming rate in recent decades. It can be found in tropical and sub-tropical climate. In Malaysia, dengue has been declared as one of the national health threat to the public. This study aimed to map the spatial distributions of dengue cases in the district of Hulu Langat, Selangor via a combination of Geographic Information System (GIS) and spatial statistic tools. Data related to dengue was gathered from the various government health agencies. The location of dengue cases was geocoded using a handheld GPS Juno SB Trimble. A total of 197 dengue cases occurring in 2003 were used in this study. Those data then was aggregated into sub-district level and then converted into GIS format. The study also used population or demographic data as well as the boundary of Hulu Langat. To assess the spatial distribution of dengue cases three spatial statistics method (Moran-s I, average nearest neighborhood (ANN) and kernel density estimation) were applied together with spatial analysis in the GIS environment. Those three indices were used to analyze the spatial distribution and average distance of dengue incidence and to locate the hot spot of dengue cases. The results indicated that the dengue cases was clustered (p < 0.01) when analyze using Moran-s I with z scores 5.03. The results from ANN analysis showed that the average nearest neighbor ratio is less than 1 which is 0.518755 (p < 0.0001). From this result, we can expect the dengue cases pattern in Hulu Langat district is exhibiting a cluster pattern. The z-score for dengue incidence within the district is -13.0525 (p < 0.0001). It was also found that the significant spatial autocorrelation of dengue incidences occurs at an average distance of 380.81 meters (p < 0.0001). Several locations especially residential area also had been identified as the hot spots of dengue cases in the district.