Research Article
AP Deployment Optimization Based on Bluetooth Fingerprint Database Discrimination
@INPROCEEDINGS{10.4108/eai.29-6-2019.2282130, author={Haoliang Ren and Zengshan Tian and Mu Zhou and Xiaoxiao Jin and Shuai Lu}, title={AP Deployment Optimization Based on Bluetooth Fingerprint Database Discrimination}, proceedings={12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019, Weihai, China}, publisher={EAI}, proceedings_a={MOBIMEDIA}, year={2019}, month={6}, keywords={indoor positioning fingerprint database access point deployment greedy algorithm signal propagation model}, doi={10.4108/eai.29-6-2019.2282130} }- Haoliang Ren
Zengshan Tian
Mu Zhou
Xiaoxiao Jin
Shuai Lu
Year: 2019
AP Deployment Optimization Based on Bluetooth Fingerprint Database Discrimination
MOBIMEDIA
EAI
DOI: 10.4108/eai.29-6-2019.2282130
Abstract
In indoor fingerprint positioning system, Access Point (AP) deployment costs a lot of manpower and time, and the deployment efficiency of existing methods is extremely low due to the complexity and dynamics of indoor environment. In order to solve this problem, this paper proposes an optimal AP deployment algorithm. First of all, wireless signal propagation model is established from indoor environment. Then simulated fingerprint database is constructed based on initial AP deployment. Finally, greedy algorithm is selected to optimize the deployment of APs. The experimental results show that this method can be well adapted to the indoor environment with higher accuracy compared to the empirical AP deployment.
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