In typical Wi-Fi based indoor positioning systems employing fingerprint model,plentiful fingerprints need to be trained by trained experts or technician,which extends labor costs and restricts their promotion.In this ...In typical Wi-Fi based indoor positioning systems employing fingerprint model,plentiful fingerprints need to be trained by trained experts or technician,which extends labor costs and restricts their promotion.In this paper,a novel approach based on crowd paths to solve this problem is presented,which collects and constructs automatically fingerprints database for anonymous buildings through common crowd customers.However,the accuracy degradation problem may be introduced as crowd customers are not professional trained and equipped.Therefore,we define two concepts:fixed landmark and hint landmark,to rectify the fingerprint database in the practical system,in which common corridor crossing points serve as fixed landmark and cross point among different crowd paths serve as hint landmark.Machinelearning techniques are utilized for short range approximation around fixed landmarks and fuzzy logic decision technology is applied for searching hint landmarks in crowd traces space.Besides,the particle filter algorithm is also introduced to smooth the sample points in crowd paths.We implemented the approach on off-the-shelf smartphones and evaluate the performance.Experimental results indicate that the approach can availably construct WiFi fingerprint database without reduce the localization accuracy.展开更多
There exists an inherent difficulty in the original algorithm for the construction of Dwarf, which prevents it from constructing true Dwarfs. We explained when and why it introduces suffix redundancies into the Dwarf ...There exists an inherent difficulty in the original algorithm for the construction of Dwarf, which prevents it from constructing true Dwarfs. We explained when and why it introduces suffix redundancies into the Dwarf structure. To solve this problem, we proposed a completely new algorithm called PID. It bottom-up computes partitions of a fact table, and inserts them into the Dwarf structure. If a partition is an MSV partition, coalesce its sub-Dwarf; otherwise create necessary nodes and cells. Our performance study showed that PID is efficient. For further condensing of Dwarf, we proposed Condensed Dwarf, a more com- pressed structure, combining the strength of Dwarf and Condensed Cube. By eliminating unnecessary stores of “ALL” cells from the Dwarf structure, Condensed Dwarf could effectively reduce the size of Dwarf, especially for Dwarfs of the real world, which was illustrated by our experiments. Its query processing is still simple and, only two minor modifications to PID are required for the construction of Condensed Dwarf.展开更多
基金partially sponsored by National Key Project of China (No.2012ZX03001013-003)
文摘In typical Wi-Fi based indoor positioning systems employing fingerprint model,plentiful fingerprints need to be trained by trained experts or technician,which extends labor costs and restricts their promotion.In this paper,a novel approach based on crowd paths to solve this problem is presented,which collects and constructs automatically fingerprints database for anonymous buildings through common crowd customers.However,the accuracy degradation problem may be introduced as crowd customers are not professional trained and equipped.Therefore,we define two concepts:fixed landmark and hint landmark,to rectify the fingerprint database in the practical system,in which common corridor crossing points serve as fixed landmark and cross point among different crowd paths serve as hint landmark.Machinelearning techniques are utilized for short range approximation around fixed landmarks and fuzzy logic decision technology is applied for searching hint landmarks in crowd traces space.Besides,the particle filter algorithm is also introduced to smooth the sample points in crowd paths.We implemented the approach on off-the-shelf smartphones and evaluate the performance.Experimental results indicate that the approach can availably construct WiFi fingerprint database without reduce the localization accuracy.
基金Project (No. 20030487032) supported by the Specialized Research Fund for the Doctoral Program of Higher Education, China
文摘There exists an inherent difficulty in the original algorithm for the construction of Dwarf, which prevents it from constructing true Dwarfs. We explained when and why it introduces suffix redundancies into the Dwarf structure. To solve this problem, we proposed a completely new algorithm called PID. It bottom-up computes partitions of a fact table, and inserts them into the Dwarf structure. If a partition is an MSV partition, coalesce its sub-Dwarf; otherwise create necessary nodes and cells. Our performance study showed that PID is efficient. For further condensing of Dwarf, we proposed Condensed Dwarf, a more com- pressed structure, combining the strength of Dwarf and Condensed Cube. By eliminating unnecessary stores of “ALL” cells from the Dwarf structure, Condensed Dwarf could effectively reduce the size of Dwarf, especially for Dwarfs of the real world, which was illustrated by our experiments. Its query processing is still simple and, only two minor modifications to PID are required for the construction of Condensed Dwarf.
