摘要
针对已有噪音地图绘制方法的人力和时间开销较大的问题,设计并实现一种基于群智感知建立的噪音地图系统。该系统包括移动端和服务器端,移动端的智能手机通过麦克风收集所在位置的噪音程度,校正后上传服务器,服务器端汇总噪音数据,恢复缺失数据并供用户查询。实验结果表明,当该系统将移动端校正的数据与标准测量仪的误差控制在3dB以内时,能以较小的人力和时间开销建立实时细粒度的噪音地图。
Building noise maps is always accompanied with a lot of human efforts and time costs.This paper designs and implements a system based on participatory sensing.The mobile part and the server part are two key components in this system.Smart phones in mobile part measure the noise level around them.Noise data is uploaded to the server part after calibration.The server part collects these data,recovers the loosed data and builds the noise map.Users can query the noise map according to their demands.Experimental results show that the error of the calibration is less than3 dB and this system builds the real-time and fine-grand noise map with low overhand.
出处
《计算机工程》
CAS
CSCD
北大核心
2015年第10期160-164,共5页
Computer Engineering
关键词
参与式感知
智能手机
校正模块
数据恢复
矩阵分解
participatory sensing
smart phone
calibration module
data recovery
matrix decomposition
