Adaptive Block Partition of Geographic Map Based on Road Coverage in Urban Environment

Abstract

Smart cities try to deploy new sensors or controller to existing hardware infrastructure to improve the efficiency of city life. How to effectively utilize geographic information to deploy ubiquitous facilities (such as street light control unit) in the urban environment increasingly becomes an important issue. Calculating the minimum block number for facility deployment in a city is similar to the maximum clique problem which belongs to the NP-hard problems. In this paper, we propose an algorithm to find the near minimum block number of geographic map based on road coverage in the urban environment. In the algorithm, we first exploit the Google map as the geographic information to calculate the road coverage of a city and then partitioning the map into numerous partitions according to a given lights (road coverage). We also conduct some experiments to evaluate the performance and accuracy to demonstrate the feasibility of the system. The result shows that the proposed algorithm is effective and efficient.